mych02.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "path = 'ch02/usagov_bitly_data2012-03-16-1331923249.txt'\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'{ \"a\": \"Mozilla\\\\/5.0 (Windows NT 6.1; WOW64) AppleWebKit\\\\/535.11 (KHTML, like Gecko) Chrome\\\\/17.0.963.78 Safari\\\\/535.11\", \"c\": \"US\", \"nk\": 1, \"tz\": \"America\\\\/New_York\", \"gr\": \"MA\", \"g\": \"A6qOVH\", \"h\": \"wfLQtf\", \"l\": \"orofrog\", \"al\": \"en-US,en;q=0.8\", \"hh\": \"1.usa.gov\", \"r\": \"http:\\\\/\\\\/www.facebook.com\\\\/l\\\\/7AQEFzjSi\\\\/1.usa.gov\\\\/wfLQtf\", \"u\": \"http:\\\\/\\\\/www.ncbi.nlm.nih.gov\\\\/pubmed\\\\/22415991\", \"t\": 1331923247, \"hc\": 1331822918, \"cy\": \"Danvers\", \"ll\": [ 42.576698, -70.954903 ] }\\n'"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 读取文件的第一行\n",
    "open(path).readline()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# 使用python内置模块json讲json字符串转换成python字典对象\n",
    "import json\n",
    "records = [json.loads(line) for line in open(path)]  # 列表推倒"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "collapsed": false,
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{u'a': u'Mozilla/5.0 (Windows NT 6.1; WOW64) AppleWebKit/535.11 (KHTML, like Gecko) Chrome/17.0.963.78 Safari/535.11',\n",
       " u'al': u'en-US,en;q=0.8',\n",
       " u'c': u'US',\n",
       " u'cy': u'Danvers',\n",
       " u'g': u'A6qOVH',\n",
       " u'gr': u'MA',\n",
       " u'h': u'wfLQtf',\n",
       " u'hc': 1331822918,\n",
       " u'hh': u'1.usa.gov',\n",
       " u'l': u'orofrog',\n",
       " u'll': [42.576698, -70.954903],\n",
       " u'nk': 1,\n",
       " u'r': u'http://www.facebook.com/l/7AQEFzjSi/1.usa.gov/wfLQtf',\n",
       " u't': 1331923247,\n",
       " u'tz': u'America/New_York',\n",
       " u'u': u'http://www.ncbi.nlm.nih.gov/pubmed/22415991'}"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "records[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "u'America/New_York'"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "records[0]['tz']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "# 查出数据集中最常出现的时区（tz字段）\n",
    "time_zones = [rec for rec in records]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "ename": "TypeError",
     "evalue": "list indices must be integers, not str",
     "output_type": "error",
     "traceback": [
      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[1;31mTypeError\u001b[0m                                 Traceback (most recent call last)",
      "\u001b[1;32m<ipython-input-9-5f7b59c99066>\u001b[0m in \u001b[0;36m<module>\u001b[1;34m()\u001b[0m\n\u001b[1;32m----> 1\u001b[1;33m \u001b[0mtime_zones\u001b[0m\u001b[1;33m[\u001b[0m\u001b[1;34m'tz'\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m",
      "\u001b[1;31mTypeError\u001b[0m: list indices must be integers, not str"
     ]
    }
   ],
   "source": [
    "time_zones['tz']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# 不是所有记录都有时区字段， 所以需要判断\n",
    "time_zones = [rec['tz'] for rec in records if 'tz' in rec]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[u'America/New_York',\n",
       " u'America/Denver',\n",
       " u'America/New_York',\n",
       " u'America/Sao_Paulo',\n",
       " u'America/New_York',\n",
       " u'America/New_York',\n",
       " u'Europe/Warsaw',\n",
       " u'',\n",
       " u'',\n",
       " u'']"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "time_zones[:10]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "# 对时区进行计数\n",
    "# 原始python函数写法\n",
    "def get_counts(sequence):\n",
    "    counts = {}\n",
    "    for x in sequence:\n",
    "        if x in counts:\n",
    "            counts[x] +=1\n",
    "        else:\n",
    "            counts[x] =1\n",
    "    return counts\n",
    "\n",
    "# 使用Python标准库\n",
    "from collections import defaultdict\n",
    "def get_counts2(sequence):\n",
    "    counts = defaultdict(int) # 所有值均会被初始化为0\n",
    "    for x in sequence:\n",
    "        counts[x] +=1\n",
    "    return counts"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "counts = get_counts(time_zones)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1251"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "counts['America/New_York']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "3440"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(time_zones)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# 获得前10位的时区及其计数值\n",
    "def top_counts(count_dict, n=10):\n",
    "    value_key_pairs = [(count, tz) for tz, count in count_dict.items()]\n",
    "    value_key_pairs.sort()\n",
    "    return value_key_pairs[-n:]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[(33, u'America/Sao_Paulo'),\n",
       " (35, u'Europe/Madrid'),\n",
       " (36, u'Pacific/Honolulu'),\n",
       " (37, u'Asia/Tokyo'),\n",
       " (74, u'Europe/London'),\n",
       " (191, u'America/Denver'),\n",
       " (382, u'America/Los_Angeles'),\n",
       " (400, u'America/Chicago'),\n",
       " (521, u''),\n",
       " (1251, u'America/New_York')]"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "top_counts(counts)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# 用pandas对时区进行计数\n",
    "from pandas import DataFrame, Series"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "frame = DataFrame(records)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>_heartbeat_</th>\n",
       "      <th>a</th>\n",
       "      <th>al</th>\n",
       "      <th>c</th>\n",
       "      <th>cy</th>\n",
       "      <th>g</th>\n",
       "      <th>gr</th>\n",
       "      <th>h</th>\n",
       "      <th>hc</th>\n",
       "      <th>hh</th>\n",
       "      <th>kw</th>\n",
       "      <th>l</th>\n",
       "      <th>ll</th>\n",
       "      <th>nk</th>\n",
       "      <th>r</th>\n",
       "      <th>t</th>\n",
       "      <th>tz</th>\n",
       "      <th>u</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>NaN</td>\n",
       "      <td>Mozilla/5.0 (Windows NT 6.1; WOW64) AppleWebKi...</td>\n",
       "      <td>en-US,en;q=0.8</td>\n",
       "      <td>US</td>\n",
       "      <td>Danvers</td>\n",
       "      <td>A6qOVH</td>\n",
       "      <td>MA</td>\n",
       "      <td>wfLQtf</td>\n",
       "      <td>1.331823e+09</td>\n",
       "      <td>1.usa.gov</td>\n",
       "      <td>NaN</td>\n",
       "      <td>orofrog</td>\n",
       "      <td>[42.576698, -70.954903]</td>\n",
       "      <td>1.0</td>\n",
       "      <td>http://www.facebook.com/l/7AQEFzjSi/1.usa.gov/...</td>\n",
       "      <td>1.331923e+09</td>\n",
       "      <td>America/New_York</td>\n",
       "      <td>http://www.ncbi.nlm.nih.gov/pubmed/22415991</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>NaN</td>\n",
       "      <td>GoogleMaps/RochesterNY</td>\n",
       "      <td>NaN</td>\n",
       "      <td>US</td>\n",
       "      <td>Provo</td>\n",
       "      <td>mwszkS</td>\n",
       "      <td>UT</td>\n",
       "      <td>mwszkS</td>\n",
       "      <td>1.308262e+09</td>\n",
       "      <td>j.mp</td>\n",
       "      <td>NaN</td>\n",
       "      <td>bitly</td>\n",
       "      <td>[40.218102, -111.613297]</td>\n",
       "      <td>0.0</td>\n",
       "      <td>http://www.AwareMap.com/</td>\n",
       "      <td>1.331923e+09</td>\n",
       "      <td>America/Denver</td>\n",
       "      <td>http://www.monroecounty.gov/etc/911/rss.php</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>NaN</td>\n",
       "      <td>Mozilla/4.0 (compatible; MSIE 8.0; Windows NT ...</td>\n",
       "      <td>en-US</td>\n",
       "      <td>US</td>\n",
       "      <td>Washington</td>\n",
       "      <td>xxr3Qb</td>\n",
       "      <td>DC</td>\n",
       "      <td>xxr3Qb</td>\n",
       "      <td>1.331920e+09</td>\n",
       "      <td>1.usa.gov</td>\n",
       "      <td>NaN</td>\n",
       "      <td>bitly</td>\n",
       "      <td>[38.9007, -77.043098]</td>\n",
       "      <td>1.0</td>\n",
       "      <td>http://t.co/03elZC4Q</td>\n",
       "      <td>1.331923e+09</td>\n",
       "      <td>America/New_York</td>\n",
       "      <td>http://boxer.senate.gov/en/press/releases/0316...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>NaN</td>\n",
       "      <td>Mozilla/5.0 (Macintosh; Intel Mac OS X 10_6_8)...</td>\n",
       "      <td>pt-br</td>\n",
       "      <td>BR</td>\n",
       "      <td>Braz</td>\n",
       "      <td>zCaLwp</td>\n",
       "      <td>27</td>\n",
       "      <td>zUtuOu</td>\n",
       "      <td>1.331923e+09</td>\n",
       "      <td>1.usa.gov</td>\n",
       "      <td>NaN</td>\n",
       "      <td>alelex88</td>\n",
       "      <td>[-23.549999, -46.616699]</td>\n",
       "      <td>0.0</td>\n",
       "      <td>direct</td>\n",
       "      <td>1.331923e+09</td>\n",
       "      <td>America/Sao_Paulo</td>\n",
       "      <td>http://apod.nasa.gov/apod/ap120312.html</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>NaN</td>\n",
       "      <td>Mozilla/5.0 (Windows NT 6.1; WOW64) AppleWebKi...</td>\n",
       "      <td>en-US,en;q=0.8</td>\n",
       "      <td>US</td>\n",
       "      <td>Shrewsbury</td>\n",
       "      <td>9b6kNl</td>\n",
       "      <td>MA</td>\n",
       "      <td>9b6kNl</td>\n",
       "      <td>1.273672e+09</td>\n",
       "      <td>bit.ly</td>\n",
       "      <td>NaN</td>\n",
       "      <td>bitly</td>\n",
       "      <td>[42.286499, -71.714699]</td>\n",
       "      <td>0.0</td>\n",
       "      <td>http://www.shrewsbury-ma.gov/selco/</td>\n",
       "      <td>1.331923e+09</td>\n",
       "      <td>America/New_York</td>\n",
       "      <td>http://www.shrewsbury-ma.gov/egov/gallery/1341...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>NaN</td>\n",
       "      <td>Mozilla/5.0 (Windows NT 6.1; WOW64) AppleWebKi...</td>\n",
       "      <td>en-US,en;q=0.8</td>\n",
       "      <td>US</td>\n",
       "      <td>Shrewsbury</td>\n",
       "      <td>axNK8c</td>\n",
       "      <td>MA</td>\n",
       "      <td>axNK8c</td>\n",
       "      <td>1.273673e+09</td>\n",
       "      <td>bit.ly</td>\n",
       "      <td>NaN</td>\n",
       "      <td>bitly</td>\n",
       "      <td>[42.286499, -71.714699]</td>\n",
       "      <td>0.0</td>\n",
       "      <td>http://www.shrewsbury-ma.gov/selco/</td>\n",
       "      <td>1.331923e+09</td>\n",
       "      <td>America/New_York</td>\n",
       "      <td>http://www.shrewsbury-ma.gov/egov/gallery/1341...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>NaN</td>\n",
       "      <td>Mozilla/5.0 (Windows NT 5.1) AppleWebKit/535.1...</td>\n",
       "      <td>pl-PL,pl;q=0.8,en-US;q=0.6,en;q=0.4</td>\n",
       "      <td>PL</td>\n",
       "      <td>Luban</td>\n",
       "      <td>wcndER</td>\n",
       "      <td>77</td>\n",
       "      <td>zkpJBR</td>\n",
       "      <td>1.331923e+09</td>\n",
       "      <td>1.usa.gov</td>\n",
       "      <td>NaN</td>\n",
       "      <td>bnjacobs</td>\n",
       "      <td>[51.116699, 15.2833]</td>\n",
       "      <td>0.0</td>\n",
       "      <td>http://plus.url.google.com/url?sa=z&amp;n=13319232...</td>\n",
       "      <td>1.331923e+09</td>\n",
       "      <td>Europe/Warsaw</td>\n",
       "      <td>http://www.nasa.gov/mission_pages/nustar/main/...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>NaN</td>\n",
       "      <td>Mozilla/5.0 (Windows NT 6.1; rv:2.0.1) Gecko/2...</td>\n",
       "      <td>bg,en-us;q=0.7,en;q=0.3</td>\n",
       "      <td>None</td>\n",
       "      <td>NaN</td>\n",
       "      <td>wcndER</td>\n",
       "      <td>NaN</td>\n",
       "      <td>zkpJBR</td>\n",
       "      <td>1.331923e+09</td>\n",
       "      <td>1.usa.gov</td>\n",
       "      <td>NaN</td>\n",
       "      <td>bnjacobs</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0</td>\n",
       "      <td>http://www.facebook.com/</td>\n",
       "      <td>1.331923e+09</td>\n",
       "      <td></td>\n",
       "      <td>http://www.nasa.gov/mission_pages/nustar/main/...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>NaN</td>\n",
       "      <td>Opera/9.80 (X11; Linux zbov; U; en) Presto/2.1...</td>\n",
       "      <td>en-US, en</td>\n",
       "      <td>None</td>\n",
       "      <td>NaN</td>\n",
       "      <td>wcndER</td>\n",
       "      <td>NaN</td>\n",
       "      <td>zkpJBR</td>\n",
       "      <td>1.331923e+09</td>\n",
       "      <td>1.usa.gov</td>\n",
       "      <td>NaN</td>\n",
       "      <td>bnjacobs</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0</td>\n",
       "      <td>http://www.facebook.com/l.php?u=http%3A%2F%2F1...</td>\n",
       "      <td>1.331923e+09</td>\n",
       "      <td></td>\n",
       "      <td>http://www.nasa.gov/mission_pages/nustar/main/...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>NaN</td>\n",
       "      <td>Mozilla/5.0 (Windows NT 6.1; WOW64) AppleWebKi...</td>\n",
       "      <td>pt-BR,pt;q=0.8,en-US;q=0.6,en;q=0.4</td>\n",
       "      <td>None</td>\n",
       "      <td>NaN</td>\n",
       "      <td>zCaLwp</td>\n",
       "      <td>NaN</td>\n",
       "      <td>zUtuOu</td>\n",
       "      <td>1.331923e+09</td>\n",
       "      <td>1.usa.gov</td>\n",
       "      <td>NaN</td>\n",
       "      <td>alelex88</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0</td>\n",
       "      <td>http://t.co/o1Pd0WeV</td>\n",
       "      <td>1.331923e+09</td>\n",
       "      <td></td>\n",
       "      <td>http://apod.nasa.gov/apod/ap120312.html</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>NaN</td>\n",
       "      <td>Mozilla/5.0 (Windows NT 6.1; WOW64; rv:10.0.2)...</td>\n",
       "      <td>en-us,en;q=0.5</td>\n",
       "      <td>US</td>\n",
       "      <td>Seattle</td>\n",
       "      <td>vNJS4H</td>\n",
       "      <td>WA</td>\n",
       "      <td>u0uD9q</td>\n",
       "      <td>1.319564e+09</td>\n",
       "      <td>1.usa.gov</td>\n",
       "      <td>NaN</td>\n",
       "      <td>o_4us71ccioa</td>\n",
       "      <td>[47.5951, -122.332603]</td>\n",
       "      <td>1.0</td>\n",
       "      <td>direct</td>\n",
       "      <td>1.331923e+09</td>\n",
       "      <td>America/Los_Angeles</td>\n",
       "      <td>https://www.nysdot.gov/rexdesign/design/commun...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>NaN</td>\n",
       "      <td>Mozilla/5.0 (Macintosh; U; Intel Mac OS X 10.4...</td>\n",
       "      <td>en-us,en;q=0.5</td>\n",
       "      <td>US</td>\n",
       "      <td>Washington</td>\n",
       "      <td>wG7OIH</td>\n",
       "      <td>DC</td>\n",
       "      <td>A0nRz4</td>\n",
       "      <td>1.331816e+09</td>\n",
       "      <td>1.usa.gov</td>\n",
       "      <td>NaN</td>\n",
       "      <td>darrellissa</td>\n",
       "      <td>[38.937599, -77.092796]</td>\n",
       "      <td>0.0</td>\n",
       "      <td>http://t.co/ND7SoPyo</td>\n",
       "      <td>1.331923e+09</td>\n",
       "      <td>America/New_York</td>\n",
       "      <td>http://oversight.house.gov/wp-content/uploads/...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>NaN</td>\n",
       "      <td>Mozilla/5.0 (Windows NT 6.1; WOW64; rv:10.0.2)...</td>\n",
       "      <td>en-us,en;q=0.5</td>\n",
       "      <td>US</td>\n",
       "      <td>Alexandria</td>\n",
       "      <td>vNJS4H</td>\n",
       "      <td>VA</td>\n",
       "      <td>u0uD9q</td>\n",
       "      <td>1.319564e+09</td>\n",
       "      <td>1.usa.gov</td>\n",
       "      <td>NaN</td>\n",
       "      <td>o_4us71ccioa</td>\n",
       "      <td>[38.790901, -77.094704]</td>\n",
       "      <td>1.0</td>\n",
       "      <td>direct</td>\n",
       "      <td>1.331923e+09</td>\n",
       "      <td>America/New_York</td>\n",
       "      <td>https://www.nysdot.gov/rexdesign/design/commun...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>1.331923e+09</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>NaN</td>\n",
       "      <td>Mozilla/5.0 (Windows; U; Windows NT 6.1; en-US...</td>\n",
       "      <td>en-us,en;q=0.5</td>\n",
       "      <td>US</td>\n",
       "      <td>Marietta</td>\n",
       "      <td>2rOUYc</td>\n",
       "      <td>GA</td>\n",
       "      <td>2rOUYc</td>\n",
       "      <td>1.255770e+09</td>\n",
       "      <td>1.usa.gov</td>\n",
       "      <td>NaN</td>\n",
       "      <td>bitly</td>\n",
       "      <td>[33.953201, -84.5177]</td>\n",
       "      <td>1.0</td>\n",
       "      <td>direct</td>\n",
       "      <td>1.331923e+09</td>\n",
       "      <td>America/New_York</td>\n",
       "      <td>http://toxtown.nlm.nih.gov/index.php</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>NaN</td>\n",
       "      <td>Mozilla/5.0 (Windows NT 6.1) AppleWebKit/535.1...</td>\n",
       "      <td>zh-TW,zh;q=0.8,en-US;q=0.6,en;q=0.4</td>\n",
       "      <td>HK</td>\n",
       "      <td>Central District</td>\n",
       "      <td>nQvgJp</td>\n",
       "      <td>00</td>\n",
       "      <td>rtrrth</td>\n",
       "      <td>1.317318e+09</td>\n",
       "      <td>j.mp</td>\n",
       "      <td>NaN</td>\n",
       "      <td>walkeryuen</td>\n",
       "      <td>[22.2833, 114.150002]</td>\n",
       "      <td>1.0</td>\n",
       "      <td>http://forum2.hkgolden.com/view.aspx?type=BW&amp;m...</td>\n",
       "      <td>1.331923e+09</td>\n",
       "      <td>Asia/Hong_Kong</td>\n",
       "      <td>http://www.ssd.noaa.gov/PS/TROP/TCFP/data/curr...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>NaN</td>\n",
       "      <td>Mozilla/5.0 (Windows NT 6.1) AppleWebKit/535.1...</td>\n",
       "      <td>zh-TW,zh;q=0.8,en-US;q=0.6,en;q=0.4</td>\n",
       "      <td>HK</td>\n",
       "      <td>Central District</td>\n",
       "      <td>XdUNr</td>\n",
       "      <td>00</td>\n",
       "      <td>qWkgbq</td>\n",
       "      <td>1.317318e+09</td>\n",
       "      <td>j.mp</td>\n",
       "      <td>NaN</td>\n",
       "      <td>walkeryuen</td>\n",
       "      <td>[22.2833, 114.150002]</td>\n",
       "      <td>1.0</td>\n",
       "      <td>http://forum2.hkgolden.com/view.aspx?type=BW&amp;m...</td>\n",
       "      <td>1.331923e+09</td>\n",
       "      <td>Asia/Hong_Kong</td>\n",
       "      <td>http://www.usno.navy.mil/NOOC/nmfc-ph/RSS/jtwc...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>NaN</td>\n",
       "      <td>Mozilla/5.0 (Macintosh; Intel Mac OS X 10.5; r...</td>\n",
       "      <td>en-us,en;q=0.5</td>\n",
       "      <td>US</td>\n",
       "      <td>Buckfield</td>\n",
       "      <td>zH1BFf</td>\n",
       "      <td>ME</td>\n",
       "      <td>x3jOIv</td>\n",
       "      <td>1.331840e+09</td>\n",
       "      <td>1.usa.gov</td>\n",
       "      <td>NaN</td>\n",
       "      <td>andyzieminski</td>\n",
       "      <td>[44.299702, -70.369797]</td>\n",
       "      <td>0.0</td>\n",
       "      <td>http://t.co/6Cx4ROLs</td>\n",
       "      <td>1.331923e+09</td>\n",
       "      <td>America/New_York</td>\n",
       "      <td>http://www.usda.gov/wps/portal/usda/usdahome?c...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>NaN</td>\n",
       "      <td>GoogleMaps/RochesterNY</td>\n",
       "      <td>NaN</td>\n",
       "      <td>US</td>\n",
       "      <td>Provo</td>\n",
       "      <td>mwszkS</td>\n",
       "      <td>UT</td>\n",
       "      <td>mwszkS</td>\n",
       "      <td>1.308262e+09</td>\n",
       "      <td>1.usa.gov</td>\n",
       "      <td>NaN</td>\n",
       "      <td>bitly</td>\n",
       "      <td>[40.218102, -111.613297]</td>\n",
       "      <td>0.0</td>\n",
       "      <td>http://www.AwareMap.com/</td>\n",
       "      <td>1.331923e+09</td>\n",
       "      <td>America/Denver</td>\n",
       "      <td>http://www.monroecounty.gov/etc/911/rss.php</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>NaN</td>\n",
       "      <td>Mozilla/5.0 (Windows NT 6.1; WOW64) AppleWebKi...</td>\n",
       "      <td>it-IT,it;q=0.8,en-US;q=0.6,en;q=0.4</td>\n",
       "      <td>IT</td>\n",
       "      <td>Venice</td>\n",
       "      <td>wcndER</td>\n",
       "      <td>20</td>\n",
       "      <td>zkpJBR</td>\n",
       "      <td>1.331923e+09</td>\n",
       "      <td>1.usa.gov</td>\n",
       "      <td>NaN</td>\n",
       "      <td>bnjacobs</td>\n",
       "      <td>[45.438599, 12.3267]</td>\n",
       "      <td>0.0</td>\n",
       "      <td>http://www.facebook.com/</td>\n",
       "      <td>1.331923e+09</td>\n",
       "      <td>Europe/Rome</td>\n",
       "      <td>http://www.nasa.gov/mission_pages/nustar/main/...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>NaN</td>\n",
       "      <td>Mozilla/5.0 (compatible; MSIE 9.0; Windows NT ...</td>\n",
       "      <td>es-ES</td>\n",
       "      <td>ES</td>\n",
       "      <td>Alcal</td>\n",
       "      <td>zQ95Hi</td>\n",
       "      <td>51</td>\n",
       "      <td>ytZYWR</td>\n",
       "      <td>1.331671e+09</td>\n",
       "      <td>bitly.com</td>\n",
       "      <td>NaN</td>\n",
       "      <td>jplnews</td>\n",
       "      <td>[37.516701, -5.9833]</td>\n",
       "      <td>0.0</td>\n",
       "      <td>http://www.facebook.com/</td>\n",
       "      <td>1.331923e+09</td>\n",
       "      <td>Africa/Ceuta</td>\n",
       "      <td>http://voyager.jpl.nasa.gov/imagesvideo/uranus...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>NaN</td>\n",
       "      <td>Mozilla/5.0 (Macintosh; U; Intel Mac OS X 10.6...</td>\n",
       "      <td>en-us,en;q=0.5</td>\n",
       "      <td>US</td>\n",
       "      <td>Davidsonville</td>\n",
       "      <td>wcndER</td>\n",
       "      <td>MD</td>\n",
       "      <td>zkpJBR</td>\n",
       "      <td>1.331923e+09</td>\n",
       "      <td>1.usa.gov</td>\n",
       "      <td>NaN</td>\n",
       "      <td>bnjacobs</td>\n",
       "      <td>[38.939201, -76.635002]</td>\n",
       "      <td>0.0</td>\n",
       "      <td>http://www.facebook.com/</td>\n",
       "      <td>1.331923e+09</td>\n",
       "      <td>America/New_York</td>\n",
       "      <td>http://www.nasa.gov/mission_pages/nustar/main/...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>NaN</td>\n",
       "      <td>Mozilla/4.0 (compatible; MSIE 8.0; Windows NT ...</td>\n",
       "      <td>en-us</td>\n",
       "      <td>US</td>\n",
       "      <td>Hockessin</td>\n",
       "      <td>y3ZImz</td>\n",
       "      <td>DE</td>\n",
       "      <td>y3ZImz</td>\n",
       "      <td>1.331064e+09</td>\n",
       "      <td>1.usa.gov</td>\n",
       "      <td>NaN</td>\n",
       "      <td>bitly</td>\n",
       "      <td>[39.785, -75.682297]</td>\n",
       "      <td>0.0</td>\n",
       "      <td>direct</td>\n",
       "      <td>1.331923e+09</td>\n",
       "      <td>America/New_York</td>\n",
       "      <td>http://portal.hud.gov/hudportal/documents/hudd...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>NaN</td>\n",
       "      <td>Mozilla/5.0 (Macintosh; Intel Mac OS X 10_7_3)...</td>\n",
       "      <td>en-us</td>\n",
       "      <td>US</td>\n",
       "      <td>Lititz</td>\n",
       "      <td>wWiOiD</td>\n",
       "      <td>PA</td>\n",
       "      <td>wWiOiD</td>\n",
       "      <td>1.330218e+09</td>\n",
       "      <td>1.usa.gov</td>\n",
       "      <td>NaN</td>\n",
       "      <td>bitly</td>\n",
       "      <td>[40.174999, -76.3078]</td>\n",
       "      <td>0.0</td>\n",
       "      <td>http://www.facebook.com/l.php?u=http%3A%2F%2F1...</td>\n",
       "      <td>1.331923e+09</td>\n",
       "      <td>America/New_York</td>\n",
       "      <td>http://www.tricare.mil/mybenefit/ProfileFilter...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>NaN</td>\n",
       "      <td>Mozilla/5.0 (Windows; U; Windows NT 5.1; es-ES...</td>\n",
       "      <td>es-es,es;q=0.8,en-us;q=0.5,en;q=0.3</td>\n",
       "      <td>ES</td>\n",
       "      <td>Bilbao</td>\n",
       "      <td>wcndER</td>\n",
       "      <td>59</td>\n",
       "      <td>zkpJBR</td>\n",
       "      <td>1.331923e+09</td>\n",
       "      <td>1.usa.gov</td>\n",
       "      <td>NaN</td>\n",
       "      <td>bnjacobs</td>\n",
       "      <td>[43.25, -2.9667]</td>\n",
       "      <td>0.0</td>\n",
       "      <td>http://www.facebook.com/</td>\n",
       "      <td>1.331923e+09</td>\n",
       "      <td>Europe/Madrid</td>\n",
       "      <td>http://www.nasa.gov/mission_pages/nustar/main/...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>NaN</td>\n",
       "      <td>Mozilla/5.0 (Windows NT 6.1) AppleWebKit/535.1...</td>\n",
       "      <td>en-GB,en;q=0.8,en-US;q=0.6,en-AU;q=0.4</td>\n",
       "      <td>MY</td>\n",
       "      <td>Kuala Lumpur</td>\n",
       "      <td>wcndER</td>\n",
       "      <td>14</td>\n",
       "      <td>zkpJBR</td>\n",
       "      <td>1.331923e+09</td>\n",
       "      <td>1.usa.gov</td>\n",
       "      <td>NaN</td>\n",
       "      <td>bnjacobs</td>\n",
       "      <td>[3.1667, 101.699997]</td>\n",
       "      <td>0.0</td>\n",
       "      <td>http://www.facebook.com/</td>\n",
       "      <td>1.331923e+09</td>\n",
       "      <td>Asia/Kuala_Lumpur</td>\n",
       "      <td>http://www.nasa.gov/mission_pages/nustar/main/...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>NaN</td>\n",
       "      <td>Mozilla/5.0 (Windows NT 6.1) AppleWebKit/535.1...</td>\n",
       "      <td>ro-RO,ro;q=0.8,en-US;q=0.6,en;q=0.4</td>\n",
       "      <td>CY</td>\n",
       "      <td>Nicosia</td>\n",
       "      <td>wcndER</td>\n",
       "      <td>04</td>\n",
       "      <td>zkpJBR</td>\n",
       "      <td>1.331923e+09</td>\n",
       "      <td>1.usa.gov</td>\n",
       "      <td>NaN</td>\n",
       "      <td>bnjacobs</td>\n",
       "      <td>[35.166698, 33.366699]</td>\n",
       "      <td>0.0</td>\n",
       "      <td>http://www.facebook.com/?ref=tn_tnmn</td>\n",
       "      <td>1.331923e+09</td>\n",
       "      <td>Asia/Nicosia</td>\n",
       "      <td>http://www.nasa.gov/mission_pages/nustar/main/...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>NaN</td>\n",
       "      <td>Mozilla/5.0 (Macintosh; Intel Mac OS X 10_6_8)...</td>\n",
       "      <td>en-US,en;q=0.8</td>\n",
       "      <td>BR</td>\n",
       "      <td>SPaulo</td>\n",
       "      <td>zCaLwp</td>\n",
       "      <td>27</td>\n",
       "      <td>zUtuOu</td>\n",
       "      <td>1.331923e+09</td>\n",
       "      <td>1.usa.gov</td>\n",
       "      <td>NaN</td>\n",
       "      <td>alelex88</td>\n",
       "      <td>[-23.5333, -46.616699]</td>\n",
       "      <td>0.0</td>\n",
       "      <td>direct</td>\n",
       "      <td>1.331923e+09</td>\n",
       "      <td>America/Sao_Paulo</td>\n",
       "      <td>http://apod.nasa.gov/apod/ap120312.html</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>NaN</td>\n",
       "      <td>Mozilla/5.0 (iPad; CPU OS 5_0_1 like Mac OS X)...</td>\n",
       "      <td>en-us</td>\n",
       "      <td>None</td>\n",
       "      <td>NaN</td>\n",
       "      <td>vNJS4H</td>\n",
       "      <td>NaN</td>\n",
       "      <td>u0uD9q</td>\n",
       "      <td>1.319564e+09</td>\n",
       "      <td>1.usa.gov</td>\n",
       "      <td>NaN</td>\n",
       "      <td>o_4us71ccioa</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0</td>\n",
       "      <td>direct</td>\n",
       "      <td>1.331923e+09</td>\n",
       "      <td></td>\n",
       "      <td>https://www.nysdot.gov/rexdesign/design/commun...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>NaN</td>\n",
       "      <td>Mozilla/5.0 (iPad; U; CPU OS 3_2 like Mac OS X...</td>\n",
       "      <td>en-us</td>\n",
       "      <td>None</td>\n",
       "      <td>NaN</td>\n",
       "      <td>FPX0IM</td>\n",
       "      <td>NaN</td>\n",
       "      <td>FPX0IL</td>\n",
       "      <td>1.331923e+09</td>\n",
       "      <td>1.usa.gov</td>\n",
       "      <td>NaN</td>\n",
       "      <td>twittershare</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>http://t.co/5xlp0B34</td>\n",
       "      <td>1.331923e+09</td>\n",
       "      <td></td>\n",
       "      <td>http://www.ed.gov/news/media-advisories/us-dep...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3530</th>\n",
       "      <td>NaN</td>\n",
       "      <td>Mozilla/5.0 (Windows NT 6.0) AppleWebKit/535.1...</td>\n",
       "      <td>en-US,en;q=0.8</td>\n",
       "      <td>US</td>\n",
       "      <td>San Francisco</td>\n",
       "      <td>xVZg4P</td>\n",
       "      <td>CA</td>\n",
       "      <td>wqUkTo</td>\n",
       "      <td>1.331908e+09</td>\n",
       "      <td>go.nasa.gov</td>\n",
       "      <td>NaN</td>\n",
       "      <td>nasatwitter</td>\n",
       "      <td>[37.7645, -122.429398]</td>\n",
       "      <td>0.0</td>\n",
       "      <td>http://www.facebook.com/l.php?u=http%3A%2F%2Fg...</td>\n",
       "      <td>1.331927e+09</td>\n",
       "      <td>America/Los_Angeles</td>\n",
       "      <td>http://www.nasa.gov/multimedia/imagegallery/im...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3531</th>\n",
       "      <td>NaN</td>\n",
       "      <td>Mozilla/5.0 (Macintosh; U; Intel Mac OS X 10_6...</td>\n",
       "      <td>en-US</td>\n",
       "      <td>None</td>\n",
       "      <td>NaN</td>\n",
       "      <td>wcndER</td>\n",
       "      <td>NaN</td>\n",
       "      <td>zkpJBR</td>\n",
       "      <td>1.331923e+09</td>\n",
       "      <td>1.usa.gov</td>\n",
       "      <td>NaN</td>\n",
       "      <td>bnjacobs</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0</td>\n",
       "      <td>direct</td>\n",
       "      <td>1.331927e+09</td>\n",
       "      <td></td>\n",
       "      <td>http://www.nasa.gov/mission_pages/nustar/main/...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3532</th>\n",
       "      <td>NaN</td>\n",
       "      <td>Mozilla/5.0 (Windows NT 6.1; WOW64; rv:10.0.2)...</td>\n",
       "      <td>en-us,en;q=0.5</td>\n",
       "      <td>US</td>\n",
       "      <td>Washington</td>\n",
       "      <td>Au3aUS</td>\n",
       "      <td>DC</td>\n",
       "      <td>A9ct6C</td>\n",
       "      <td>1.331926e+09</td>\n",
       "      <td>1.usa.gov</td>\n",
       "      <td>NaN</td>\n",
       "      <td>ncsha</td>\n",
       "      <td>[38.904202, -77.031998]</td>\n",
       "      <td>1.0</td>\n",
       "      <td>http://www.ncsha.org/</td>\n",
       "      <td>1.331927e+09</td>\n",
       "      <td>America/New_York</td>\n",
       "      <td>http://portal.hud.gov/hudportal/HUD?src=/press...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3533</th>\n",
       "      <td>NaN</td>\n",
       "      <td>Mozilla/5.0 (iPad; CPU OS 5_1 like Mac OS X) A...</td>\n",
       "      <td>en-us</td>\n",
       "      <td>US</td>\n",
       "      <td>Jacksonville</td>\n",
       "      <td>b2UtUJ</td>\n",
       "      <td>FL</td>\n",
       "      <td>ieCdgH</td>\n",
       "      <td>1.301393e+09</td>\n",
       "      <td>go.nasa.gov</td>\n",
       "      <td>NaN</td>\n",
       "      <td>nasatwitter</td>\n",
       "      <td>[30.279301, -81.585098]</td>\n",
       "      <td>1.0</td>\n",
       "      <td>direct</td>\n",
       "      <td>1.331927e+09</td>\n",
       "      <td>America/New_York</td>\n",
       "      <td>http://apod.nasa.gov/apod/</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3534</th>\n",
       "      <td>NaN</td>\n",
       "      <td>Mozilla/5.0 (Macintosh; Intel Mac OS X 10_6_8)...</td>\n",
       "      <td>en-us</td>\n",
       "      <td>US</td>\n",
       "      <td>Frisco</td>\n",
       "      <td>vNJS4H</td>\n",
       "      <td>TX</td>\n",
       "      <td>u0uD9q</td>\n",
       "      <td>1.319564e+09</td>\n",
       "      <td>1.usa.gov</td>\n",
       "      <td>NaN</td>\n",
       "      <td>o_4us71ccioa</td>\n",
       "      <td>[33.149899, -96.855499]</td>\n",
       "      <td>1.0</td>\n",
       "      <td>direct</td>\n",
       "      <td>1.331927e+09</td>\n",
       "      <td>America/Chicago</td>\n",
       "      <td>https://www.nysdot.gov/rexdesign/design/commun...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3535</th>\n",
       "      <td>NaN</td>\n",
       "      <td>Mozilla/5.0 (Windows NT 5.1; rv:10.0.2) Gecko/...</td>\n",
       "      <td>en-us</td>\n",
       "      <td>US</td>\n",
       "      <td>Houston</td>\n",
       "      <td>zIgLx8</td>\n",
       "      <td>TX</td>\n",
       "      <td>yrPaLt</td>\n",
       "      <td>1.331903e+09</td>\n",
       "      <td>aash.to</td>\n",
       "      <td>NaN</td>\n",
       "      <td>aashto</td>\n",
       "      <td>[29.775499, -95.415199]</td>\n",
       "      <td>1.0</td>\n",
       "      <td>direct</td>\n",
       "      <td>1.331927e+09</td>\n",
       "      <td>America/Chicago</td>\n",
       "      <td>http://ntl.bts.gov/lib/44000/44300/44374/FHWA-...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3536</th>\n",
       "      <td>NaN</td>\n",
       "      <td>Mozilla/5.0 (BlackBerry; U; BlackBerry 9800; e...</td>\n",
       "      <td>en-US,en;q=0.5</td>\n",
       "      <td>None</td>\n",
       "      <td>NaN</td>\n",
       "      <td>xIcyim</td>\n",
       "      <td>NaN</td>\n",
       "      <td>yG1TTf</td>\n",
       "      <td>1.331728e+09</td>\n",
       "      <td>go.nasa.gov</td>\n",
       "      <td>NaN</td>\n",
       "      <td>nasatwitter</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0</td>\n",
       "      <td>http://t.co/g1VKE8zS</td>\n",
       "      <td>1.331927e+09</td>\n",
       "      <td></td>\n",
       "      <td>http://www.nasa.gov/mission_pages/hurricanes/a...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3537</th>\n",
       "      <td>NaN</td>\n",
       "      <td>Mozilla/5.0 (Windows NT 6.1; WOW64; rv:10.0.2)...</td>\n",
       "      <td>es-es,es;q=0.8,en-us;q=0.5,en;q=0.3</td>\n",
       "      <td>HN</td>\n",
       "      <td>Tegucigalpa</td>\n",
       "      <td>zCaLwp</td>\n",
       "      <td>08</td>\n",
       "      <td>w63FZW</td>\n",
       "      <td>1.331547e+09</td>\n",
       "      <td>1.usa.gov</td>\n",
       "      <td>NaN</td>\n",
       "      <td>bufferapp</td>\n",
       "      <td>[14.1, -87.216698]</td>\n",
       "      <td>0.0</td>\n",
       "      <td>http://t.co/A8TJyibE</td>\n",
       "      <td>1.331927e+09</td>\n",
       "      <td>America/Tegucigalpa</td>\n",
       "      <td>http://apod.nasa.gov/apod/ap120312.html</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3538</th>\n",
       "      <td>NaN</td>\n",
       "      <td>Mozilla/5.0 (iPhone; CPU iPhone OS 5_1 like Ma...</td>\n",
       "      <td>en-us</td>\n",
       "      <td>US</td>\n",
       "      <td>Los Angeles</td>\n",
       "      <td>qMac9k</td>\n",
       "      <td>CA</td>\n",
       "      <td>qds1Ge</td>\n",
       "      <td>1.310474e+09</td>\n",
       "      <td>1.usa.gov</td>\n",
       "      <td>NaN</td>\n",
       "      <td>healthypeople</td>\n",
       "      <td>[34.041599, -118.298798]</td>\n",
       "      <td>0.0</td>\n",
       "      <td>direct</td>\n",
       "      <td>1.331927e+09</td>\n",
       "      <td>America/Los_Angeles</td>\n",
       "      <td>http://healthypeople.gov/2020/connect/webinars...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3539</th>\n",
       "      <td>NaN</td>\n",
       "      <td>Mozilla/5.0 (compatible; Fedora Core 3) FC3 KDE</td>\n",
       "      <td>NaN</td>\n",
       "      <td>US</td>\n",
       "      <td>Bellevue</td>\n",
       "      <td>zu2M5o</td>\n",
       "      <td>WA</td>\n",
       "      <td>zDhdro</td>\n",
       "      <td>1.331586e+09</td>\n",
       "      <td>bit.ly</td>\n",
       "      <td>NaN</td>\n",
       "      <td>glimtwin</td>\n",
       "      <td>[47.615398, -122.210297]</td>\n",
       "      <td>0.0</td>\n",
       "      <td>direct</td>\n",
       "      <td>1.331927e+09</td>\n",
       "      <td>America/Los_Angeles</td>\n",
       "      <td>http://www.federalreserve.gov/newsevents/press...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3540</th>\n",
       "      <td>NaN</td>\n",
       "      <td>Mozilla/5.0 (Windows NT 6.1; WOW64) AppleWebKi...</td>\n",
       "      <td>en-US,en;q=0.8</td>\n",
       "      <td>US</td>\n",
       "      <td>Payson</td>\n",
       "      <td>wcndER</td>\n",
       "      <td>UT</td>\n",
       "      <td>zkpJBR</td>\n",
       "      <td>1.331923e+09</td>\n",
       "      <td>1.usa.gov</td>\n",
       "      <td>NaN</td>\n",
       "      <td>bnjacobs</td>\n",
       "      <td>[40.014198, -111.738899]</td>\n",
       "      <td>0.0</td>\n",
       "      <td>http://www.facebook.com/l.php?u=http%3A%2F%2F1...</td>\n",
       "      <td>1.331927e+09</td>\n",
       "      <td>America/Denver</td>\n",
       "      <td>http://www.nasa.gov/mission_pages/nustar/main/...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3541</th>\n",
       "      <td>NaN</td>\n",
       "      <td>Mozilla/5.0 (X11; U; OpenVMS AlphaServer_ES40;...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>US</td>\n",
       "      <td>Bellevue</td>\n",
       "      <td>zu2M5o</td>\n",
       "      <td>WA</td>\n",
       "      <td>zDhdro</td>\n",
       "      <td>1.331586e+09</td>\n",
       "      <td>1.usa.gov</td>\n",
       "      <td>NaN</td>\n",
       "      <td>glimtwin</td>\n",
       "      <td>[47.615398, -122.210297]</td>\n",
       "      <td>0.0</td>\n",
       "      <td>direct</td>\n",
       "      <td>1.331927e+09</td>\n",
       "      <td>America/Los_Angeles</td>\n",
       "      <td>http://www.federalreserve.gov/newsevents/press...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3542</th>\n",
       "      <td>NaN</td>\n",
       "      <td>Mozilla/5.0 (compatible; MSIE 9.0; Windows NT ...</td>\n",
       "      <td>en-us</td>\n",
       "      <td>US</td>\n",
       "      <td>Pittsburg</td>\n",
       "      <td>y3reI1</td>\n",
       "      <td>CA</td>\n",
       "      <td>y3reI1</td>\n",
       "      <td>1.331926e+09</td>\n",
       "      <td>1.usa.gov</td>\n",
       "      <td>NaN</td>\n",
       "      <td>bitly</td>\n",
       "      <td>[38.0051, -121.838699]</td>\n",
       "      <td>0.0</td>\n",
       "      <td>http://www.facebook.com/l.php?u=http%3A%2F%2F1...</td>\n",
       "      <td>1.331927e+09</td>\n",
       "      <td>America/Los_Angeles</td>\n",
       "      <td>http://www.sba.gov/community/blogs/community-b...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3543</th>\n",
       "      <td>1.331927e+09</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3544</th>\n",
       "      <td>NaN</td>\n",
       "      <td>Mozilla/5.0 (Windows NT 6.1; WOW64; rv:5.0.1) ...</td>\n",
       "      <td>en-us,en;q=0.5</td>\n",
       "      <td>US</td>\n",
       "      <td>Wentzville</td>\n",
       "      <td>vNJS4H</td>\n",
       "      <td>MO</td>\n",
       "      <td>u0uD9q</td>\n",
       "      <td>1.319564e+09</td>\n",
       "      <td>1.usa.gov</td>\n",
       "      <td>NaN</td>\n",
       "      <td>o_4us71ccioa</td>\n",
       "      <td>[38.790001, -90.854897]</td>\n",
       "      <td>1.0</td>\n",
       "      <td>direct</td>\n",
       "      <td>1.331927e+09</td>\n",
       "      <td>America/Chicago</td>\n",
       "      <td>https://www.nysdot.gov/rexdesign/design/commun...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3545</th>\n",
       "      <td>NaN</td>\n",
       "      <td>Mozilla/5.0 (Windows NT 6.1; WOW64; rv:10.0.2)...</td>\n",
       "      <td>en-us,en;q=0.5</td>\n",
       "      <td>US</td>\n",
       "      <td>Saint Charles</td>\n",
       "      <td>vNJS4H</td>\n",
       "      <td>IL</td>\n",
       "      <td>u0uD9q</td>\n",
       "      <td>1.319564e+09</td>\n",
       "      <td>1.usa.gov</td>\n",
       "      <td>NaN</td>\n",
       "      <td>o_4us71ccioa</td>\n",
       "      <td>[41.9352, -88.290901]</td>\n",
       "      <td>1.0</td>\n",
       "      <td>direct</td>\n",
       "      <td>1.331927e+09</td>\n",
       "      <td>America/Chicago</td>\n",
       "      <td>https://www.nysdot.gov/rexdesign/design/commun...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3546</th>\n",
       "      <td>NaN</td>\n",
       "      <td>Mozilla/5.0 (iPhone; CPU iPhone OS 5_1 like Ma...</td>\n",
       "      <td>en-us</td>\n",
       "      <td>US</td>\n",
       "      <td>Los Angeles</td>\n",
       "      <td>qMac9k</td>\n",
       "      <td>CA</td>\n",
       "      <td>qds1Ge</td>\n",
       "      <td>1.310474e+09</td>\n",
       "      <td>1.usa.gov</td>\n",
       "      <td>NaN</td>\n",
       "      <td>healthypeople</td>\n",
       "      <td>[34.041599, -118.298798]</td>\n",
       "      <td>1.0</td>\n",
       "      <td>direct</td>\n",
       "      <td>1.331927e+09</td>\n",
       "      <td>America/Los_Angeles</td>\n",
       "      <td>http://healthypeople.gov/2020/connect/webinars...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3547</th>\n",
       "      <td>NaN</td>\n",
       "      <td>Mozilla/5.0 (Macintosh; Intel Mac OS X 10_6_8)...</td>\n",
       "      <td>en-us</td>\n",
       "      <td>US</td>\n",
       "      <td>Silver Spring</td>\n",
       "      <td>y0jYkg</td>\n",
       "      <td>MD</td>\n",
       "      <td>y0jYkg</td>\n",
       "      <td>1.331852e+09</td>\n",
       "      <td>1.usa.gov</td>\n",
       "      <td>NaN</td>\n",
       "      <td>bitly</td>\n",
       "      <td>[39.052101, -77.014999]</td>\n",
       "      <td>1.0</td>\n",
       "      <td>direct</td>\n",
       "      <td>1.331927e+09</td>\n",
       "      <td>America/New_York</td>\n",
       "      <td>http://www.epa.gov/otaq/regs/fuels/additive/e1...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3548</th>\n",
       "      <td>NaN</td>\n",
       "      <td>Mozilla/5.0 (iPhone; CPU iPhone OS 5_1 like Ma...</td>\n",
       "      <td>en-us</td>\n",
       "      <td>US</td>\n",
       "      <td>Mcgehee</td>\n",
       "      <td>y5rMac</td>\n",
       "      <td>AR</td>\n",
       "      <td>xANY6O</td>\n",
       "      <td>1.331916e+09</td>\n",
       "      <td>1.usa.gov</td>\n",
       "      <td>NaN</td>\n",
       "      <td>twitterfeed</td>\n",
       "      <td>[33.628399, -91.356903]</td>\n",
       "      <td>1.0</td>\n",
       "      <td>https://twitter.com/fdarecalls/status/18069759...</td>\n",
       "      <td>1.331927e+09</td>\n",
       "      <td>America/Chicago</td>\n",
       "      <td>http://www.fda.gov/Safety/Recalls/ucm296326.htm</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3549</th>\n",
       "      <td>NaN</td>\n",
       "      <td>Mozilla/5.0 (Windows NT 6.1; WOW64) AppleWebKi...</td>\n",
       "      <td>sv-SE,sv;q=0.8,en-US;q=0.6,en;q=0.4</td>\n",
       "      <td>SE</td>\n",
       "      <td>Sollefte</td>\n",
       "      <td>eH8wu</td>\n",
       "      <td>24</td>\n",
       "      <td>7dtjei</td>\n",
       "      <td>1.260316e+09</td>\n",
       "      <td>1.usa.gov</td>\n",
       "      <td>NaN</td>\n",
       "      <td>tweetdeckapi</td>\n",
       "      <td>[63.166698, 17.266701]</td>\n",
       "      <td>1.0</td>\n",
       "      <td>direct</td>\n",
       "      <td>1.331927e+09</td>\n",
       "      <td>Europe/Stockholm</td>\n",
       "      <td>http://www.nasa.gov/mission_pages/WISE/main/in...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3550</th>\n",
       "      <td>NaN</td>\n",
       "      <td>Mozilla/4.0 (compatible; MSIE 8.0; Windows NT ...</td>\n",
       "      <td>en-us</td>\n",
       "      <td>US</td>\n",
       "      <td>Conshohocken</td>\n",
       "      <td>A00b72</td>\n",
       "      <td>PA</td>\n",
       "      <td>yGSwzn</td>\n",
       "      <td>1.331918e+09</td>\n",
       "      <td>1.usa.gov</td>\n",
       "      <td>NaN</td>\n",
       "      <td>addthis</td>\n",
       "      <td>[40.0798, -75.2855]</td>\n",
       "      <td>0.0</td>\n",
       "      <td>http://www.linkedin.com/home?trk=hb_tab_home_top</td>\n",
       "      <td>1.331927e+09</td>\n",
       "      <td>America/New_York</td>\n",
       "      <td>http://www.nlm.nih.gov/medlineplus/news/fullst...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3551</th>\n",
       "      <td>NaN</td>\n",
       "      <td>Mozilla/5.0 (Windows NT 6.1; WOW64) AppleWebKi...</td>\n",
       "      <td>en-US,en;q=0.8</td>\n",
       "      <td>None</td>\n",
       "      <td>NaN</td>\n",
       "      <td>wcndER</td>\n",
       "      <td>NaN</td>\n",
       "      <td>zkpJBR</td>\n",
       "      <td>1.331923e+09</td>\n",
       "      <td>1.usa.gov</td>\n",
       "      <td>NaN</td>\n",
       "      <td>bnjacobs</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0</td>\n",
       "      <td>http://plus.url.google.com/url?sa=z&amp;n=13319268...</td>\n",
       "      <td>1.331927e+09</td>\n",
       "      <td></td>\n",
       "      <td>http://www.nasa.gov/mission_pages/nustar/main/...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3552</th>\n",
       "      <td>NaN</td>\n",
       "      <td>Mozilla/5.0 (Windows; U; Windows NT 6.1; en-US...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>US</td>\n",
       "      <td>Decatur</td>\n",
       "      <td>rqgJuE</td>\n",
       "      <td>AL</td>\n",
       "      <td>xcz8vt</td>\n",
       "      <td>1.331227e+09</td>\n",
       "      <td>1.usa.gov</td>\n",
       "      <td>NaN</td>\n",
       "      <td>bootsnall</td>\n",
       "      <td>[34.572701, -86.940598]</td>\n",
       "      <td>0.0</td>\n",
       "      <td>direct</td>\n",
       "      <td>1.331927e+09</td>\n",
       "      <td>America/Chicago</td>\n",
       "      <td>http://travel.state.gov/passport/passport_5535...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3553</th>\n",
       "      <td>NaN</td>\n",
       "      <td>Mozilla/4.0 (compatible; MSIE 7.0; Windows NT ...</td>\n",
       "      <td>en-us</td>\n",
       "      <td>US</td>\n",
       "      <td>Shrewsbury</td>\n",
       "      <td>9b6kNl</td>\n",
       "      <td>MA</td>\n",
       "      <td>9b6kNl</td>\n",
       "      <td>1.273672e+09</td>\n",
       "      <td>bit.ly</td>\n",
       "      <td>NaN</td>\n",
       "      <td>bitly</td>\n",
       "      <td>[42.286499, -71.714699]</td>\n",
       "      <td>0.0</td>\n",
       "      <td>http://www.shrewsbury-ma.gov/selco/</td>\n",
       "      <td>1.331927e+09</td>\n",
       "      <td>America/New_York</td>\n",
       "      <td>http://www.shrewsbury-ma.gov/egov/gallery/1341...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3554</th>\n",
       "      <td>NaN</td>\n",
       "      <td>Mozilla/4.0 (compatible; MSIE 7.0; Windows NT ...</td>\n",
       "      <td>en-us</td>\n",
       "      <td>US</td>\n",
       "      <td>Shrewsbury</td>\n",
       "      <td>axNK8c</td>\n",
       "      <td>MA</td>\n",
       "      <td>axNK8c</td>\n",
       "      <td>1.273673e+09</td>\n",
       "      <td>bit.ly</td>\n",
       "      <td>NaN</td>\n",
       "      <td>bitly</td>\n",
       "      <td>[42.286499, -71.714699]</td>\n",
       "      <td>0.0</td>\n",
       "      <td>http://www.shrewsbury-ma.gov/selco/</td>\n",
       "      <td>1.331927e+09</td>\n",
       "      <td>America/New_York</td>\n",
       "      <td>http://www.shrewsbury-ma.gov/egov/gallery/1341...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3555</th>\n",
       "      <td>NaN</td>\n",
       "      <td>Mozilla/4.0 (compatible; MSIE 9.0; Windows NT ...</td>\n",
       "      <td>en</td>\n",
       "      <td>US</td>\n",
       "      <td>Paramus</td>\n",
       "      <td>e5SvKE</td>\n",
       "      <td>NJ</td>\n",
       "      <td>fqPSr9</td>\n",
       "      <td>1.301298e+09</td>\n",
       "      <td>1.usa.gov</td>\n",
       "      <td>NaN</td>\n",
       "      <td>tweetdeckapi</td>\n",
       "      <td>[40.9445, -74.07]</td>\n",
       "      <td>1.0</td>\n",
       "      <td>direct</td>\n",
       "      <td>1.331927e+09</td>\n",
       "      <td>America/New_York</td>\n",
       "      <td>http://www.fda.gov/AdvisoryCommittees/Committe...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3556</th>\n",
       "      <td>NaN</td>\n",
       "      <td>Mozilla/5.0 (Windows NT 5.1) AppleWebKit/535.1...</td>\n",
       "      <td>en-US,en;q=0.8</td>\n",
       "      <td>US</td>\n",
       "      <td>Oklahoma City</td>\n",
       "      <td>jQLtP4</td>\n",
       "      <td>OK</td>\n",
       "      <td>jQLtP4</td>\n",
       "      <td>1.307530e+09</td>\n",
       "      <td>1.usa.gov</td>\n",
       "      <td>NaN</td>\n",
       "      <td>bitly</td>\n",
       "      <td>[35.4715, -97.518997]</td>\n",
       "      <td>0.0</td>\n",
       "      <td>http://www.facebook.com/l.php?u=http%3A%2F%2F1...</td>\n",
       "      <td>1.331927e+09</td>\n",
       "      <td>America/Chicago</td>\n",
       "      <td>http://www.okc.gov/PublicNotificationSystem/Fo...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3557</th>\n",
       "      <td>NaN</td>\n",
       "      <td>GoogleMaps/RochesterNY</td>\n",
       "      <td>NaN</td>\n",
       "      <td>US</td>\n",
       "      <td>Provo</td>\n",
       "      <td>mwszkS</td>\n",
       "      <td>UT</td>\n",
       "      <td>mwszkS</td>\n",
       "      <td>1.308262e+09</td>\n",
       "      <td>j.mp</td>\n",
       "      <td>NaN</td>\n",
       "      <td>bitly</td>\n",
       "      <td>[40.218102, -111.613297]</td>\n",
       "      <td>0.0</td>\n",
       "      <td>http://www.AwareMap.com/</td>\n",
       "      <td>1.331927e+09</td>\n",
       "      <td>America/Denver</td>\n",
       "      <td>http://www.monroecounty.gov/etc/911/rss.php</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3558</th>\n",
       "      <td>NaN</td>\n",
       "      <td>GoogleProducer</td>\n",
       "      <td>NaN</td>\n",
       "      <td>US</td>\n",
       "      <td>Mountain View</td>\n",
       "      <td>zjtI4X</td>\n",
       "      <td>CA</td>\n",
       "      <td>zjtI4X</td>\n",
       "      <td>1.327529e+09</td>\n",
       "      <td>1.usa.gov</td>\n",
       "      <td>NaN</td>\n",
       "      <td>bitly</td>\n",
       "      <td>[37.419201, -122.057404]</td>\n",
       "      <td>0.0</td>\n",
       "      <td>direct</td>\n",
       "      <td>1.331927e+09</td>\n",
       "      <td>America/Los_Angeles</td>\n",
       "      <td>http://www.ahrq.gov/qual/qitoolkit/</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3559</th>\n",
       "      <td>NaN</td>\n",
       "      <td>Mozilla/4.0 (compatible; MSIE 8.0; Windows NT ...</td>\n",
       "      <td>en-US</td>\n",
       "      <td>US</td>\n",
       "      <td>Mc Lean</td>\n",
       "      <td>qxKrTK</td>\n",
       "      <td>VA</td>\n",
       "      <td>qxKrTK</td>\n",
       "      <td>1.312898e+09</td>\n",
       "      <td>1.usa.gov</td>\n",
       "      <td>NaN</td>\n",
       "      <td>bitly</td>\n",
       "      <td>[38.935799, -77.162102]</td>\n",
       "      <td>0.0</td>\n",
       "      <td>http://t.co/OEEEvwjU</td>\n",
       "      <td>1.331927e+09</td>\n",
       "      <td>America/New_York</td>\n",
       "      <td>http://herndon-va.gov/Content/public_safety/Pu...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>3560 rows × 18 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "       _heartbeat_                                                  a  \\\n",
       "0              NaN  Mozilla/5.0 (Windows NT 6.1; WOW64) AppleWebKi...   \n",
       "1              NaN                             GoogleMaps/RochesterNY   \n",
       "2              NaN  Mozilla/4.0 (compatible; MSIE 8.0; Windows NT ...   \n",
       "3              NaN  Mozilla/5.0 (Macintosh; Intel Mac OS X 10_6_8)...   \n",
       "4              NaN  Mozilla/5.0 (Windows NT 6.1; WOW64) AppleWebKi...   \n",
       "5              NaN  Mozilla/5.0 (Windows NT 6.1; WOW64) AppleWebKi...   \n",
       "6              NaN  Mozilla/5.0 (Windows NT 5.1) AppleWebKit/535.1...   \n",
       "7              NaN  Mozilla/5.0 (Windows NT 6.1; rv:2.0.1) Gecko/2...   \n",
       "8              NaN  Opera/9.80 (X11; Linux zbov; U; en) Presto/2.1...   \n",
       "9              NaN  Mozilla/5.0 (Windows NT 6.1; WOW64) AppleWebKi...   \n",
       "10             NaN  Mozilla/5.0 (Windows NT 6.1; WOW64; rv:10.0.2)...   \n",
       "11             NaN  Mozilla/5.0 (Macintosh; U; Intel Mac OS X 10.4...   \n",
       "12             NaN  Mozilla/5.0 (Windows NT 6.1; WOW64; rv:10.0.2)...   \n",
       "13    1.331923e+09                                                NaN   \n",
       "14             NaN  Mozilla/5.0 (Windows; U; Windows NT 6.1; en-US...   \n",
       "15             NaN  Mozilla/5.0 (Windows NT 6.1) AppleWebKit/535.1...   \n",
       "16             NaN  Mozilla/5.0 (Windows NT 6.1) AppleWebKit/535.1...   \n",
       "17             NaN  Mozilla/5.0 (Macintosh; Intel Mac OS X 10.5; r...   \n",
       "18             NaN                             GoogleMaps/RochesterNY   \n",
       "19             NaN  Mozilla/5.0 (Windows NT 6.1; WOW64) AppleWebKi...   \n",
       "20             NaN  Mozilla/5.0 (compatible; MSIE 9.0; Windows NT ...   \n",
       "21             NaN  Mozilla/5.0 (Macintosh; U; Intel Mac OS X 10.6...   \n",
       "22             NaN  Mozilla/4.0 (compatible; MSIE 8.0; Windows NT ...   \n",
       "23             NaN  Mozilla/5.0 (Macintosh; Intel Mac OS X 10_7_3)...   \n",
       "24             NaN  Mozilla/5.0 (Windows; U; Windows NT 5.1; es-ES...   \n",
       "25             NaN  Mozilla/5.0 (Windows NT 6.1) AppleWebKit/535.1...   \n",
       "26             NaN  Mozilla/5.0 (Windows NT 6.1) AppleWebKit/535.1...   \n",
       "27             NaN  Mozilla/5.0 (Macintosh; Intel Mac OS X 10_6_8)...   \n",
       "28             NaN  Mozilla/5.0 (iPad; CPU OS 5_0_1 like Mac OS X)...   \n",
       "29             NaN  Mozilla/5.0 (iPad; U; CPU OS 3_2 like Mac OS X...   \n",
       "...            ...                                                ...   \n",
       "3530           NaN  Mozilla/5.0 (Windows NT 6.0) AppleWebKit/535.1...   \n",
       "3531           NaN  Mozilla/5.0 (Macintosh; U; Intel Mac OS X 10_6...   \n",
       "3532           NaN  Mozilla/5.0 (Windows NT 6.1; WOW64; rv:10.0.2)...   \n",
       "3533           NaN  Mozilla/5.0 (iPad; CPU OS 5_1 like Mac OS X) A...   \n",
       "3534           NaN  Mozilla/5.0 (Macintosh; Intel Mac OS X 10_6_8)...   \n",
       "3535           NaN  Mozilla/5.0 (Windows NT 5.1; rv:10.0.2) Gecko/...   \n",
       "3536           NaN  Mozilla/5.0 (BlackBerry; U; BlackBerry 9800; e...   \n",
       "3537           NaN  Mozilla/5.0 (Windows NT 6.1; WOW64; rv:10.0.2)...   \n",
       "3538           NaN  Mozilla/5.0 (iPhone; CPU iPhone OS 5_1 like Ma...   \n",
       "3539           NaN    Mozilla/5.0 (compatible; Fedora Core 3) FC3 KDE   \n",
       "3540           NaN  Mozilla/5.0 (Windows NT 6.1; WOW64) AppleWebKi...   \n",
       "3541           NaN  Mozilla/5.0 (X11; U; OpenVMS AlphaServer_ES40;...   \n",
       "3542           NaN  Mozilla/5.0 (compatible; MSIE 9.0; Windows NT ...   \n",
       "3543  1.331927e+09                                                NaN   \n",
       "3544           NaN  Mozilla/5.0 (Windows NT 6.1; WOW64; rv:5.0.1) ...   \n",
       "3545           NaN  Mozilla/5.0 (Windows NT 6.1; WOW64; rv:10.0.2)...   \n",
       "3546           NaN  Mozilla/5.0 (iPhone; CPU iPhone OS 5_1 like Ma...   \n",
       "3547           NaN  Mozilla/5.0 (Macintosh; Intel Mac OS X 10_6_8)...   \n",
       "3548           NaN  Mozilla/5.0 (iPhone; CPU iPhone OS 5_1 like Ma...   \n",
       "3549           NaN  Mozilla/5.0 (Windows NT 6.1; WOW64) AppleWebKi...   \n",
       "3550           NaN  Mozilla/4.0 (compatible; MSIE 8.0; Windows NT ...   \n",
       "3551           NaN  Mozilla/5.0 (Windows NT 6.1; WOW64) AppleWebKi...   \n",
       "3552           NaN  Mozilla/5.0 (Windows; U; Windows NT 6.1; en-US...   \n",
       "3553           NaN  Mozilla/4.0 (compatible; MSIE 7.0; Windows NT ...   \n",
       "3554           NaN  Mozilla/4.0 (compatible; MSIE 7.0; Windows NT ...   \n",
       "3555           NaN  Mozilla/4.0 (compatible; MSIE 9.0; Windows NT ...   \n",
       "3556           NaN  Mozilla/5.0 (Windows NT 5.1) AppleWebKit/535.1...   \n",
       "3557           NaN                             GoogleMaps/RochesterNY   \n",
       "3558           NaN                                     GoogleProducer   \n",
       "3559           NaN  Mozilla/4.0 (compatible; MSIE 8.0; Windows NT ...   \n",
       "\n",
       "                                          al     c                cy       g  \\\n",
       "0                             en-US,en;q=0.8    US           Danvers  A6qOVH   \n",
       "1                                        NaN    US             Provo  mwszkS   \n",
       "2                                      en-US    US        Washington  xxr3Qb   \n",
       "3                                      pt-br    BR              Braz  zCaLwp   \n",
       "4                             en-US,en;q=0.8    US        Shrewsbury  9b6kNl   \n",
       "5                             en-US,en;q=0.8    US        Shrewsbury  axNK8c   \n",
       "6        pl-PL,pl;q=0.8,en-US;q=0.6,en;q=0.4    PL             Luban  wcndER   \n",
       "7                    bg,en-us;q=0.7,en;q=0.3  None               NaN  wcndER   \n",
       "8                                  en-US, en  None               NaN  wcndER   \n",
       "9        pt-BR,pt;q=0.8,en-US;q=0.6,en;q=0.4  None               NaN  zCaLwp   \n",
       "10                            en-us,en;q=0.5    US           Seattle  vNJS4H   \n",
       "11                            en-us,en;q=0.5    US        Washington  wG7OIH   \n",
       "12                            en-us,en;q=0.5    US        Alexandria  vNJS4H   \n",
       "13                                       NaN   NaN               NaN     NaN   \n",
       "14                            en-us,en;q=0.5    US          Marietta  2rOUYc   \n",
       "15       zh-TW,zh;q=0.8,en-US;q=0.6,en;q=0.4    HK  Central District  nQvgJp   \n",
       "16       zh-TW,zh;q=0.8,en-US;q=0.6,en;q=0.4    HK  Central District   XdUNr   \n",
       "17                            en-us,en;q=0.5    US         Buckfield  zH1BFf   \n",
       "18                                       NaN    US             Provo  mwszkS   \n",
       "19       it-IT,it;q=0.8,en-US;q=0.6,en;q=0.4    IT            Venice  wcndER   \n",
       "20                                     es-ES    ES             Alcal  zQ95Hi   \n",
       "21                            en-us,en;q=0.5    US     Davidsonville  wcndER   \n",
       "22                                     en-us    US         Hockessin  y3ZImz   \n",
       "23                                     en-us    US            Lititz  wWiOiD   \n",
       "24       es-es,es;q=0.8,en-us;q=0.5,en;q=0.3    ES            Bilbao  wcndER   \n",
       "25    en-GB,en;q=0.8,en-US;q=0.6,en-AU;q=0.4    MY      Kuala Lumpur  wcndER   \n",
       "26       ro-RO,ro;q=0.8,en-US;q=0.6,en;q=0.4    CY           Nicosia  wcndER   \n",
       "27                            en-US,en;q=0.8    BR            SPaulo  zCaLwp   \n",
       "28                                     en-us  None               NaN  vNJS4H   \n",
       "29                                     en-us  None               NaN  FPX0IM   \n",
       "...                                      ...   ...               ...     ...   \n",
       "3530                          en-US,en;q=0.8    US     San Francisco  xVZg4P   \n",
       "3531                                   en-US  None               NaN  wcndER   \n",
       "3532                          en-us,en;q=0.5    US        Washington  Au3aUS   \n",
       "3533                                   en-us    US      Jacksonville  b2UtUJ   \n",
       "3534                                   en-us    US            Frisco  vNJS4H   \n",
       "3535                                   en-us    US           Houston  zIgLx8   \n",
       "3536                          en-US,en;q=0.5  None               NaN  xIcyim   \n",
       "3537     es-es,es;q=0.8,en-us;q=0.5,en;q=0.3    HN       Tegucigalpa  zCaLwp   \n",
       "3538                                   en-us    US       Los Angeles  qMac9k   \n",
       "3539                                     NaN    US          Bellevue  zu2M5o   \n",
       "3540                          en-US,en;q=0.8    US            Payson  wcndER   \n",
       "3541                                     NaN    US          Bellevue  zu2M5o   \n",
       "3542                                   en-us    US         Pittsburg  y3reI1   \n",
       "3543                                     NaN   NaN               NaN     NaN   \n",
       "3544                          en-us,en;q=0.5    US        Wentzville  vNJS4H   \n",
       "3545                          en-us,en;q=0.5    US     Saint Charles  vNJS4H   \n",
       "3546                                   en-us    US       Los Angeles  qMac9k   \n",
       "3547                                   en-us    US     Silver Spring  y0jYkg   \n",
       "3548                                   en-us    US           Mcgehee  y5rMac   \n",
       "3549     sv-SE,sv;q=0.8,en-US;q=0.6,en;q=0.4    SE          Sollefte   eH8wu   \n",
       "3550                                   en-us    US      Conshohocken  A00b72   \n",
       "3551                          en-US,en;q=0.8  None               NaN  wcndER   \n",
       "3552                                     NaN    US           Decatur  rqgJuE   \n",
       "3553                                   en-us    US        Shrewsbury  9b6kNl   \n",
       "3554                                   en-us    US        Shrewsbury  axNK8c   \n",
       "3555                                      en    US           Paramus  e5SvKE   \n",
       "3556                          en-US,en;q=0.8    US     Oklahoma City  jQLtP4   \n",
       "3557                                     NaN    US             Provo  mwszkS   \n",
       "3558                                     NaN    US     Mountain View  zjtI4X   \n",
       "3559                                   en-US    US           Mc Lean  qxKrTK   \n",
       "\n",
       "       gr       h            hc           hh   kw              l  \\\n",
       "0      MA  wfLQtf  1.331823e+09    1.usa.gov  NaN        orofrog   \n",
       "1      UT  mwszkS  1.308262e+09         j.mp  NaN          bitly   \n",
       "2      DC  xxr3Qb  1.331920e+09    1.usa.gov  NaN          bitly   \n",
       "3      27  zUtuOu  1.331923e+09    1.usa.gov  NaN       alelex88   \n",
       "4      MA  9b6kNl  1.273672e+09       bit.ly  NaN          bitly   \n",
       "5      MA  axNK8c  1.273673e+09       bit.ly  NaN          bitly   \n",
       "6      77  zkpJBR  1.331923e+09    1.usa.gov  NaN       bnjacobs   \n",
       "7     NaN  zkpJBR  1.331923e+09    1.usa.gov  NaN       bnjacobs   \n",
       "8     NaN  zkpJBR  1.331923e+09    1.usa.gov  NaN       bnjacobs   \n",
       "9     NaN  zUtuOu  1.331923e+09    1.usa.gov  NaN       alelex88   \n",
       "10     WA  u0uD9q  1.319564e+09    1.usa.gov  NaN   o_4us71ccioa   \n",
       "11     DC  A0nRz4  1.331816e+09    1.usa.gov  NaN    darrellissa   \n",
       "12     VA  u0uD9q  1.319564e+09    1.usa.gov  NaN   o_4us71ccioa   \n",
       "13    NaN     NaN           NaN          NaN  NaN            NaN   \n",
       "14     GA  2rOUYc  1.255770e+09    1.usa.gov  NaN          bitly   \n",
       "15     00  rtrrth  1.317318e+09         j.mp  NaN     walkeryuen   \n",
       "16     00  qWkgbq  1.317318e+09         j.mp  NaN     walkeryuen   \n",
       "17     ME  x3jOIv  1.331840e+09    1.usa.gov  NaN  andyzieminski   \n",
       "18     UT  mwszkS  1.308262e+09    1.usa.gov  NaN          bitly   \n",
       "19     20  zkpJBR  1.331923e+09    1.usa.gov  NaN       bnjacobs   \n",
       "20     51  ytZYWR  1.331671e+09    bitly.com  NaN        jplnews   \n",
       "21     MD  zkpJBR  1.331923e+09    1.usa.gov  NaN       bnjacobs   \n",
       "22     DE  y3ZImz  1.331064e+09    1.usa.gov  NaN          bitly   \n",
       "23     PA  wWiOiD  1.330218e+09    1.usa.gov  NaN          bitly   \n",
       "24     59  zkpJBR  1.331923e+09    1.usa.gov  NaN       bnjacobs   \n",
       "25     14  zkpJBR  1.331923e+09    1.usa.gov  NaN       bnjacobs   \n",
       "26     04  zkpJBR  1.331923e+09    1.usa.gov  NaN       bnjacobs   \n",
       "27     27  zUtuOu  1.331923e+09    1.usa.gov  NaN       alelex88   \n",
       "28    NaN  u0uD9q  1.319564e+09    1.usa.gov  NaN   o_4us71ccioa   \n",
       "29    NaN  FPX0IL  1.331923e+09    1.usa.gov  NaN   twittershare   \n",
       "...   ...     ...           ...          ...  ...            ...   \n",
       "3530   CA  wqUkTo  1.331908e+09  go.nasa.gov  NaN    nasatwitter   \n",
       "3531  NaN  zkpJBR  1.331923e+09    1.usa.gov  NaN       bnjacobs   \n",
       "3532   DC  A9ct6C  1.331926e+09    1.usa.gov  NaN          ncsha   \n",
       "3533   FL  ieCdgH  1.301393e+09  go.nasa.gov  NaN    nasatwitter   \n",
       "3534   TX  u0uD9q  1.319564e+09    1.usa.gov  NaN   o_4us71ccioa   \n",
       "3535   TX  yrPaLt  1.331903e+09      aash.to  NaN         aashto   \n",
       "3536  NaN  yG1TTf  1.331728e+09  go.nasa.gov  NaN    nasatwitter   \n",
       "3537   08  w63FZW  1.331547e+09    1.usa.gov  NaN      bufferapp   \n",
       "3538   CA  qds1Ge  1.310474e+09    1.usa.gov  NaN  healthypeople   \n",
       "3539   WA  zDhdro  1.331586e+09       bit.ly  NaN       glimtwin   \n",
       "3540   UT  zkpJBR  1.331923e+09    1.usa.gov  NaN       bnjacobs   \n",
       "3541   WA  zDhdro  1.331586e+09    1.usa.gov  NaN       glimtwin   \n",
       "3542   CA  y3reI1  1.331926e+09    1.usa.gov  NaN          bitly   \n",
       "3543  NaN     NaN           NaN          NaN  NaN            NaN   \n",
       "3544   MO  u0uD9q  1.319564e+09    1.usa.gov  NaN   o_4us71ccioa   \n",
       "3545   IL  u0uD9q  1.319564e+09    1.usa.gov  NaN   o_4us71ccioa   \n",
       "3546   CA  qds1Ge  1.310474e+09    1.usa.gov  NaN  healthypeople   \n",
       "3547   MD  y0jYkg  1.331852e+09    1.usa.gov  NaN          bitly   \n",
       "3548   AR  xANY6O  1.331916e+09    1.usa.gov  NaN    twitterfeed   \n",
       "3549   24  7dtjei  1.260316e+09    1.usa.gov  NaN   tweetdeckapi   \n",
       "3550   PA  yGSwzn  1.331918e+09    1.usa.gov  NaN        addthis   \n",
       "3551  NaN  zkpJBR  1.331923e+09    1.usa.gov  NaN       bnjacobs   \n",
       "3552   AL  xcz8vt  1.331227e+09    1.usa.gov  NaN      bootsnall   \n",
       "3553   MA  9b6kNl  1.273672e+09       bit.ly  NaN          bitly   \n",
       "3554   MA  axNK8c  1.273673e+09       bit.ly  NaN          bitly   \n",
       "3555   NJ  fqPSr9  1.301298e+09    1.usa.gov  NaN   tweetdeckapi   \n",
       "3556   OK  jQLtP4  1.307530e+09    1.usa.gov  NaN          bitly   \n",
       "3557   UT  mwszkS  1.308262e+09         j.mp  NaN          bitly   \n",
       "3558   CA  zjtI4X  1.327529e+09    1.usa.gov  NaN          bitly   \n",
       "3559   VA  qxKrTK  1.312898e+09    1.usa.gov  NaN          bitly   \n",
       "\n",
       "                            ll   nk  \\\n",
       "0      [42.576698, -70.954903]  1.0   \n",
       "1     [40.218102, -111.613297]  0.0   \n",
       "2        [38.9007, -77.043098]  1.0   \n",
       "3     [-23.549999, -46.616699]  0.0   \n",
       "4      [42.286499, -71.714699]  0.0   \n",
       "5      [42.286499, -71.714699]  0.0   \n",
       "6         [51.116699, 15.2833]  0.0   \n",
       "7                          NaN  0.0   \n",
       "8                          NaN  0.0   \n",
       "9                          NaN  0.0   \n",
       "10      [47.5951, -122.332603]  1.0   \n",
       "11     [38.937599, -77.092796]  0.0   \n",
       "12     [38.790901, -77.094704]  1.0   \n",
       "13                         NaN  NaN   \n",
       "14       [33.953201, -84.5177]  1.0   \n",
       "15       [22.2833, 114.150002]  1.0   \n",
       "16       [22.2833, 114.150002]  1.0   \n",
       "17     [44.299702, -70.369797]  0.0   \n",
       "18    [40.218102, -111.613297]  0.0   \n",
       "19        [45.438599, 12.3267]  0.0   \n",
       "20        [37.516701, -5.9833]  0.0   \n",
       "21     [38.939201, -76.635002]  0.0   \n",
       "22        [39.785, -75.682297]  0.0   \n",
       "23       [40.174999, -76.3078]  0.0   \n",
       "24            [43.25, -2.9667]  0.0   \n",
       "25        [3.1667, 101.699997]  0.0   \n",
       "26      [35.166698, 33.366699]  0.0   \n",
       "27      [-23.5333, -46.616699]  0.0   \n",
       "28                         NaN  0.0   \n",
       "29                         NaN  1.0   \n",
       "...                        ...  ...   \n",
       "3530    [37.7645, -122.429398]  0.0   \n",
       "3531                       NaN  0.0   \n",
       "3532   [38.904202, -77.031998]  1.0   \n",
       "3533   [30.279301, -81.585098]  1.0   \n",
       "3534   [33.149899, -96.855499]  1.0   \n",
       "3535   [29.775499, -95.415199]  1.0   \n",
       "3536                       NaN  0.0   \n",
       "3537        [14.1, -87.216698]  0.0   \n",
       "3538  [34.041599, -118.298798]  0.0   \n",
       "3539  [47.615398, -122.210297]  0.0   \n",
       "3540  [40.014198, -111.738899]  0.0   \n",
       "3541  [47.615398, -122.210297]  0.0   \n",
       "3542    [38.0051, -121.838699]  0.0   \n",
       "3543                       NaN  NaN   \n",
       "3544   [38.790001, -90.854897]  1.0   \n",
       "3545     [41.9352, -88.290901]  1.0   \n",
       "3546  [34.041599, -118.298798]  1.0   \n",
       "3547   [39.052101, -77.014999]  1.0   \n",
       "3548   [33.628399, -91.356903]  1.0   \n",
       "3549    [63.166698, 17.266701]  1.0   \n",
       "3550       [40.0798, -75.2855]  0.0   \n",
       "3551                       NaN  0.0   \n",
       "3552   [34.572701, -86.940598]  0.0   \n",
       "3553   [42.286499, -71.714699]  0.0   \n",
       "3554   [42.286499, -71.714699]  0.0   \n",
       "3555         [40.9445, -74.07]  1.0   \n",
       "3556     [35.4715, -97.518997]  0.0   \n",
       "3557  [40.218102, -111.613297]  0.0   \n",
       "3558  [37.419201, -122.057404]  0.0   \n",
       "3559   [38.935799, -77.162102]  0.0   \n",
       "\n",
       "                                                      r             t  \\\n",
       "0     http://www.facebook.com/l/7AQEFzjSi/1.usa.gov/...  1.331923e+09   \n",
       "1                              http://www.AwareMap.com/  1.331923e+09   \n",
       "2                                  http://t.co/03elZC4Q  1.331923e+09   \n",
       "3                                                direct  1.331923e+09   \n",
       "4                   http://www.shrewsbury-ma.gov/selco/  1.331923e+09   \n",
       "5                   http://www.shrewsbury-ma.gov/selco/  1.331923e+09   \n",
       "6     http://plus.url.google.com/url?sa=z&n=13319232...  1.331923e+09   \n",
       "7                              http://www.facebook.com/  1.331923e+09   \n",
       "8     http://www.facebook.com/l.php?u=http%3A%2F%2F1...  1.331923e+09   \n",
       "9                                  http://t.co/o1Pd0WeV  1.331923e+09   \n",
       "10                                               direct  1.331923e+09   \n",
       "11                                 http://t.co/ND7SoPyo  1.331923e+09   \n",
       "12                                               direct  1.331923e+09   \n",
       "13                                                  NaN           NaN   \n",
       "14                                               direct  1.331923e+09   \n",
       "15    http://forum2.hkgolden.com/view.aspx?type=BW&m...  1.331923e+09   \n",
       "16    http://forum2.hkgolden.com/view.aspx?type=BW&m...  1.331923e+09   \n",
       "17                                 http://t.co/6Cx4ROLs  1.331923e+09   \n",
       "18                             http://www.AwareMap.com/  1.331923e+09   \n",
       "19                             http://www.facebook.com/  1.331923e+09   \n",
       "20                             http://www.facebook.com/  1.331923e+09   \n",
       "21                             http://www.facebook.com/  1.331923e+09   \n",
       "22                                               direct  1.331923e+09   \n",
       "23    http://www.facebook.com/l.php?u=http%3A%2F%2F1...  1.331923e+09   \n",
       "24                             http://www.facebook.com/  1.331923e+09   \n",
       "25                             http://www.facebook.com/  1.331923e+09   \n",
       "26                 http://www.facebook.com/?ref=tn_tnmn  1.331923e+09   \n",
       "27                                               direct  1.331923e+09   \n",
       "28                                               direct  1.331923e+09   \n",
       "29                                 http://t.co/5xlp0B34  1.331923e+09   \n",
       "...                                                 ...           ...   \n",
       "3530  http://www.facebook.com/l.php?u=http%3A%2F%2Fg...  1.331927e+09   \n",
       "3531                                             direct  1.331927e+09   \n",
       "3532                              http://www.ncsha.org/  1.331927e+09   \n",
       "3533                                             direct  1.331927e+09   \n",
       "3534                                             direct  1.331927e+09   \n",
       "3535                                             direct  1.331927e+09   \n",
       "3536                               http://t.co/g1VKE8zS  1.331927e+09   \n",
       "3537                               http://t.co/A8TJyibE  1.331927e+09   \n",
       "3538                                             direct  1.331927e+09   \n",
       "3539                                             direct  1.331927e+09   \n",
       "3540  http://www.facebook.com/l.php?u=http%3A%2F%2F1...  1.331927e+09   \n",
       "3541                                             direct  1.331927e+09   \n",
       "3542  http://www.facebook.com/l.php?u=http%3A%2F%2F1...  1.331927e+09   \n",
       "3543                                                NaN           NaN   \n",
       "3544                                             direct  1.331927e+09   \n",
       "3545                                             direct  1.331927e+09   \n",
       "3546                                             direct  1.331927e+09   \n",
       "3547                                             direct  1.331927e+09   \n",
       "3548  https://twitter.com/fdarecalls/status/18069759...  1.331927e+09   \n",
       "3549                                             direct  1.331927e+09   \n",
       "3550   http://www.linkedin.com/home?trk=hb_tab_home_top  1.331927e+09   \n",
       "3551  http://plus.url.google.com/url?sa=z&n=13319268...  1.331927e+09   \n",
       "3552                                             direct  1.331927e+09   \n",
       "3553                http://www.shrewsbury-ma.gov/selco/  1.331927e+09   \n",
       "3554                http://www.shrewsbury-ma.gov/selco/  1.331927e+09   \n",
       "3555                                             direct  1.331927e+09   \n",
       "3556  http://www.facebook.com/l.php?u=http%3A%2F%2F1...  1.331927e+09   \n",
       "3557                           http://www.AwareMap.com/  1.331927e+09   \n",
       "3558                                             direct  1.331927e+09   \n",
       "3559                               http://t.co/OEEEvwjU  1.331927e+09   \n",
       "\n",
       "                       tz                                                  u  \n",
       "0        America/New_York        http://www.ncbi.nlm.nih.gov/pubmed/22415991  \n",
       "1          America/Denver        http://www.monroecounty.gov/etc/911/rss.php  \n",
       "2        America/New_York  http://boxer.senate.gov/en/press/releases/0316...  \n",
       "3       America/Sao_Paulo            http://apod.nasa.gov/apod/ap120312.html  \n",
       "4        America/New_York  http://www.shrewsbury-ma.gov/egov/gallery/1341...  \n",
       "5        America/New_York  http://www.shrewsbury-ma.gov/egov/gallery/1341...  \n",
       "6           Europe/Warsaw  http://www.nasa.gov/mission_pages/nustar/main/...  \n",
       "7                          http://www.nasa.gov/mission_pages/nustar/main/...  \n",
       "8                          http://www.nasa.gov/mission_pages/nustar/main/...  \n",
       "9                                    http://apod.nasa.gov/apod/ap120312.html  \n",
       "10    America/Los_Angeles  https://www.nysdot.gov/rexdesign/design/commun...  \n",
       "11       America/New_York  http://oversight.house.gov/wp-content/uploads/...  \n",
       "12       America/New_York  https://www.nysdot.gov/rexdesign/design/commun...  \n",
       "13                    NaN                                                NaN  \n",
       "14       America/New_York               http://toxtown.nlm.nih.gov/index.php  \n",
       "15         Asia/Hong_Kong  http://www.ssd.noaa.gov/PS/TROP/TCFP/data/curr...  \n",
       "16         Asia/Hong_Kong  http://www.usno.navy.mil/NOOC/nmfc-ph/RSS/jtwc...  \n",
       "17       America/New_York  http://www.usda.gov/wps/portal/usda/usdahome?c...  \n",
       "18         America/Denver        http://www.monroecounty.gov/etc/911/rss.php  \n",
       "19            Europe/Rome  http://www.nasa.gov/mission_pages/nustar/main/...  \n",
       "20           Africa/Ceuta  http://voyager.jpl.nasa.gov/imagesvideo/uranus...  \n",
       "21       America/New_York  http://www.nasa.gov/mission_pages/nustar/main/...  \n",
       "22       America/New_York  http://portal.hud.gov/hudportal/documents/hudd...  \n",
       "23       America/New_York  http://www.tricare.mil/mybenefit/ProfileFilter...  \n",
       "24          Europe/Madrid  http://www.nasa.gov/mission_pages/nustar/main/...  \n",
       "25      Asia/Kuala_Lumpur  http://www.nasa.gov/mission_pages/nustar/main/...  \n",
       "26           Asia/Nicosia  http://www.nasa.gov/mission_pages/nustar/main/...  \n",
       "27      America/Sao_Paulo            http://apod.nasa.gov/apod/ap120312.html  \n",
       "28                         https://www.nysdot.gov/rexdesign/design/commun...  \n",
       "29                         http://www.ed.gov/news/media-advisories/us-dep...  \n",
       "...                   ...                                                ...  \n",
       "3530  America/Los_Angeles  http://www.nasa.gov/multimedia/imagegallery/im...  \n",
       "3531                       http://www.nasa.gov/mission_pages/nustar/main/...  \n",
       "3532     America/New_York  http://portal.hud.gov/hudportal/HUD?src=/press...  \n",
       "3533     America/New_York                         http://apod.nasa.gov/apod/  \n",
       "3534      America/Chicago  https://www.nysdot.gov/rexdesign/design/commun...  \n",
       "3535      America/Chicago  http://ntl.bts.gov/lib/44000/44300/44374/FHWA-...  \n",
       "3536                       http://www.nasa.gov/mission_pages/hurricanes/a...  \n",
       "3537  America/Tegucigalpa            http://apod.nasa.gov/apod/ap120312.html  \n",
       "3538  America/Los_Angeles  http://healthypeople.gov/2020/connect/webinars...  \n",
       "3539  America/Los_Angeles  http://www.federalreserve.gov/newsevents/press...  \n",
       "3540       America/Denver  http://www.nasa.gov/mission_pages/nustar/main/...  \n",
       "3541  America/Los_Angeles  http://www.federalreserve.gov/newsevents/press...  \n",
       "3542  America/Los_Angeles  http://www.sba.gov/community/blogs/community-b...  \n",
       "3543                  NaN                                                NaN  \n",
       "3544      America/Chicago  https://www.nysdot.gov/rexdesign/design/commun...  \n",
       "3545      America/Chicago  https://www.nysdot.gov/rexdesign/design/commun...  \n",
       "3546  America/Los_Angeles  http://healthypeople.gov/2020/connect/webinars...  \n",
       "3547     America/New_York  http://www.epa.gov/otaq/regs/fuels/additive/e1...  \n",
       "3548      America/Chicago    http://www.fda.gov/Safety/Recalls/ucm296326.htm  \n",
       "3549     Europe/Stockholm  http://www.nasa.gov/mission_pages/WISE/main/in...  \n",
       "3550     America/New_York  http://www.nlm.nih.gov/medlineplus/news/fullst...  \n",
       "3551                       http://www.nasa.gov/mission_pages/nustar/main/...  \n",
       "3552      America/Chicago  http://travel.state.gov/passport/passport_5535...  \n",
       "3553     America/New_York  http://www.shrewsbury-ma.gov/egov/gallery/1341...  \n",
       "3554     America/New_York  http://www.shrewsbury-ma.gov/egov/gallery/1341...  \n",
       "3555     America/New_York  http://www.fda.gov/AdvisoryCommittees/Committe...  \n",
       "3556      America/Chicago  http://www.okc.gov/PublicNotificationSystem/Fo...  \n",
       "3557       America/Denver        http://www.monroecounty.gov/etc/911/rss.php  \n",
       "3558  America/Los_Angeles                http://www.ahrq.gov/qual/qitoolkit/  \n",
       "3559     America/New_York  http://herndon-va.gov/Content/public_safety/Pu...  \n",
       "\n",
       "[3560 rows x 18 columns]"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "frame"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0     America/New_York\n",
       "1       America/Denver\n",
       "2     America/New_York\n",
       "3    America/Sao_Paulo\n",
       "4     America/New_York\n",
       "5     America/New_York\n",
       "6        Europe/Warsaw\n",
       "7                     \n",
       "8                     \n",
       "9                     \n",
       "Name: tz, dtype: object"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "frame['tz'][:10]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "tz_counts = frame['tz'].value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "America/New_York       1251\n",
       "                        521\n",
       "America/Chicago         400\n",
       "America/Los_Angeles     382\n",
       "America/Denver          191\n",
       "Europe/London            74\n",
       "Asia/Tokyo               37\n",
       "Pacific/Honolulu         36\n",
       "Europe/Madrid            35\n",
       "America/Sao_Paulo        33\n",
       "Name: tz, dtype: int64"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "tz_counts[:10]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# 利用会图库给这段数据生成一张图片\n",
    "# 首先先给记录中未知缺失的时区填上一个替代值， fillna函数可以替换缺失值（NA），未知值（空字符串）可以通过布尔型数组索引加以替换\n",
    "clean_tz = frame['tz'].fillna(\"Missing\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "clean_tz[clean_tz == ''] = 'Unknown'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "tz_counts = clean_tz.value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "America/New_York       1251\n",
       "Unknown                 521\n",
       "America/Chicago         400\n",
       "America/Los_Angeles     382\n",
       "America/Denver          191\n",
       "Missing                 120\n",
       "Europe/London            74\n",
       "Asia/Tokyo               37\n",
       "Pacific/Honolulu         36\n",
       "Europe/Madrid            35\n",
       "Name: tz, dtype: int64"
      ]
     },
     "execution_count": 43,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "tz_counts[:10]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0xb4780f0>"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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PbujnDuCU0sfOwA7AQ72IIyIi+thAJdJpwPUdyubR/NW7ZwOt5YKcB6jOqfbk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\nIYk0IiKihv8HWlIJd7t89uQAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0xae57828>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 利用counts对象的plot方法可以得到一条水平条形图\n",
    "%matplotlib inline   # 加上此句才能在内部显示图片\n",
    "tz_counts[:10].plot(kind='barh', rot = 0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "u'GoogleMaps/RochesterNY'"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "frame['a'][1]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "u'Mozilla/5.0 (Windows NT 5.1; rv:10.0.2) Gecko/20100101 Firefox/10.0.2'"
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "frame['a'][50]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "u'Mozilla/5.0 (Linux; U; Android 2.2.2; en-us; LG-P925/V10e Build/FRG83G) AppleWebKit/533.1 (KHTML, like Gecko) Version/4.0 Mobile Safari/533.1'"
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "frame['a'][51]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "results = Series([x.split()[0] for x in frame.a.dropna()])"
   ]
  },
  {
   "cell_type": "raw",
   "metadata": {},
   "source": [
    "results[:5]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0               Mozilla/5.0\n",
       "1    GoogleMaps/RochesterNY\n",
       "2               Mozilla/4.0\n",
       "3               Mozilla/5.0\n",
       "4               Mozilla/5.0\n",
       "dtype: object"
      ]
     },
     "execution_count": 37,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "results[:5]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Mozilla/5.0                 2594\n",
       "Mozilla/4.0                  601\n",
       "GoogleMaps/RochesterNY       121\n",
       "Opera/9.80                    34\n",
       "TEST_INTERNET_AGENT           24\n",
       "GoogleProducer                21\n",
       "Mozilla/6.0                    5\n",
       "BlackBerry8520/5.0.0.681       4\n",
       "dtype: int64"
      ]
     },
     "execution_count": 38,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "results.value_counts()[:8]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# 按windows和非windows用户对时区统计信息进行分解\n",
    "# 去除agent缺失的数据\n",
    "cframe = frame[frame.a.notnull()]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "operating_system = np.where(cframe['a'].str.contains('Windows'),\n",
    "                            'Windows', 'Not Windows')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array(['Windows', 'Not Windows', 'Windows', 'Not Windows', 'Windows'], \n",
       "      dtype='|S11')"
      ]
     },
     "execution_count": 41,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "operating_system[:5]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# 对列表进行分组\n",
    "by_tz_os = cframe.groupby(['tz', operating_system])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# 利用unstack对计数结果进行重塑\n",
    "agg_counts = by_tz_os.size().unstack().fillna(0)\n",
    "# agg_counts = by_tz_os.size().fillna(0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Not Windows</th>\n",
       "      <th>Windows</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>tz</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>245.0</td>\n",
       "      <td>276.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Africa/Cairo</th>\n",
       "      <td>0.0</td>\n",
       "      <td>3.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Africa/Casablanca</th>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Africa/Ceuta</th>\n",
       "      <td>0.0</td>\n",
       "      <td>2.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Africa/Johannesburg</th>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Africa/Lusaka</th>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>America/Anchorage</th>\n",
       "      <td>4.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>America/Argentina/Buenos_Aires</th>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>America/Argentina/Cordoba</th>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>America/Argentina/Mendoza</th>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                Not Windows  Windows\n",
       "tz                                                  \n",
       "                                      245.0    276.0\n",
       "Africa/Cairo                            0.0      3.0\n",
       "Africa/Casablanca                       0.0      1.0\n",
       "Africa/Ceuta                            0.0      2.0\n",
       "Africa/Johannesburg                     0.0      1.0\n",
       "Africa/Lusaka                           0.0      1.0\n",
       "America/Anchorage                       4.0      1.0\n",
       "America/Argentina/Buenos_Aires          1.0      0.0\n",
       "America/Argentina/Cordoba               0.0      1.0\n",
       "America/Argentina/Mendoza               0.0      1.0"
      ]
     },
     "execution_count": 48,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "agg_counts[0:10]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# pandas 数据重塑 资料见http://www.jianshu.com/p/4e443a852623\n",
    "# 选取最常出现的时区， 为此，根据agge_counts中的行数构造一个间接索引数组\n",
    "indexer = agg_counts.sum(1).argsort()\n",
    "#平时用的sum应该是默认的axis=0 就是普通的相加，当加入axis=1以后就是将一个矩阵的每一行向量相加。\n",
    "# argsort()返回所在元素按从小打到排序（默认按行）的顺序索引, 0是按列，1是按行，默认是1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "tz\n",
       "                                  24\n",
       "Africa/Cairo                      20\n",
       "Africa/Casablanca                 21\n",
       "Africa/Ceuta                      92\n",
       "Africa/Johannesburg               87\n",
       "Africa/Lusaka                     53\n",
       "America/Anchorage                 54\n",
       "America/Argentina/Buenos_Aires    57\n",
       "America/Argentina/Cordoba         26\n",
       "America/Argentina/Mendoza         55\n",
       "dtype: int64"
      ]
     },
     "execution_count": 50,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "indexer[:10]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[[0 2 1]\n",
      " [0 1 2]\n",
      " [0 1 2]]\n"
     ]
    }
   ],
   "source": [
    "# sum()测试， argsort()测试\n",
    "c = np.array([[0, 2, 1], [3, 5, 6], [0, 1, 1]])\n",
    "# print c.argsort(1)\n",
    "# print c.sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "count_subset = agg_counts.take(indexer)[-10:]\n",
    "# take() 函数介绍https://docs.scipy.org/doc/numpy/reference/generated/numpy.take.html"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Not Windows</th>\n",
       "      <th>Windows</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>tz</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>America/Sao_Paulo</th>\n",
       "      <td>13.0</td>\n",
       "      <td>20.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Europe/Madrid</th>\n",
       "      <td>16.0</td>\n",
       "      <td>19.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Pacific/Honolulu</th>\n",
       "      <td>0.0</td>\n",
       "      <td>36.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Asia/Tokyo</th>\n",
       "      <td>2.0</td>\n",
       "      <td>35.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Europe/London</th>\n",
       "      <td>43.0</td>\n",
       "      <td>31.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>America/Denver</th>\n",
       "      <td>132.0</td>\n",
       "      <td>59.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>America/Los_Angeles</th>\n",
       "      <td>130.0</td>\n",
       "      <td>252.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>America/Chicago</th>\n",
       "      <td>115.0</td>\n",
       "      <td>285.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>245.0</td>\n",
       "      <td>276.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>America/New_York</th>\n",
       "      <td>339.0</td>\n",
       "      <td>912.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                     Not Windows  Windows\n",
       "tz                                       \n",
       "America/Sao_Paulo           13.0     20.0\n",
       "Europe/Madrid               16.0     19.0\n",
       "Pacific/Honolulu             0.0     36.0\n",
       "Asia/Tokyo                   2.0     35.0\n",
       "Europe/London               43.0     31.0\n",
       "America/Denver             132.0     59.0\n",
       "America/Los_Angeles        130.0    252.0\n",
       "America/Chicago            115.0    285.0\n",
       "                           245.0    276.0\n",
       "America/New_York           339.0    912.0"
      ]
     },
     "execution_count": 64,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "count_subset"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x1346ee48>"
      ]
     },
     "execution_count": 65,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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GvhSoSIuplpKN2urzI6BDWmi0ADg6IhaQTT0vA+4hS26QrUx+strxIyWtrHqRjdpHA38G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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x13479e10>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 使用stacked=Treu生成一张堆积条形图\n",
    "count_subset.plot(kind ='barh', stacked=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 66,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# 上述图不太容易看清楚小分组中Windows用户的相对比例，因此可以将各行规范化为“总计为1”\n",
    "normed_subset = count_subset.div(count_subset.sum(1), axis=0)  #每一行除以总数,求出百分比"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 67,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x13708e10>"
      ]
     },
     "execution_count": 67,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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CteWLsMzMzHLjBGxmZpYDJ2AzM7McOAGbmZnlwAnYzMwsB07AZmZm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\nkmJaAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0xb6717b8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "normed_subset.plot(kind='barh', stacked=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 68,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# MovieLends 1M 数据集 测试\n",
    "import pandas as pd"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 71,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "E:\\Anaconda\\lib\\site-packages\\ipykernel\\__main__.py:2: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n",
      "  from ipykernel import kernelapp as app\n"
     ]
    }
   ],
   "source": [
    "unames = ['user_id', 'gender','age', 'occupation', 'zip']\n",
    "users = pd.read_table('ch02/movielens/users.dat', sep='::', header=None, names = unames)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 72,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "E:\\Anaconda\\lib\\site-packages\\ipykernel\\__main__.py:2: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n",
      "  from ipykernel import kernelapp as app\n"
     ]
    }
   ],
   "source": [
    "rnames = ['user_id', 'movie_id', 'rating', 'timestamp']\n",
    "ratings = pd.read_table('ch02/movielens/ratings.dat', sep='::', header=None, names = rnames)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 73,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "E:\\Anaconda\\lib\\site-packages\\ipykernel\\__main__.py:2: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n",
      "  from ipykernel import kernelapp as app\n"
     ]
    }
   ],
   "source": [
    "mnames = ['movie_id', 'title', 'genres']\n",
    "movies = pd.read_table('ch02/movielens/movies.dat', sep='::', header=None, names = mnames)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 74,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>user_id</th>\n",
       "      <th>gender</th>\n",
       "      <th>age</th>\n",
       "      <th>occupation</th>\n",
       "      <th>zip</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>F</td>\n",
       "      <td>1</td>\n",
       "      <td>10</td>\n",
       "      <td>48067</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>M</td>\n",
       "      <td>56</td>\n",
       "      <td>16</td>\n",
       "      <td>70072</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>M</td>\n",
       "      <td>25</td>\n",
       "      <td>15</td>\n",
       "      <td>55117</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>M</td>\n",
       "      <td>45</td>\n",
       "      <td>7</td>\n",
       "      <td>02460</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>M</td>\n",
       "      <td>25</td>\n",
       "      <td>20</td>\n",
       "      <td>55455</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   user_id gender  age  occupation    zip\n",
       "0        1      F    1          10  48067\n",
       "1        2      M   56          16  70072\n",
       "2        3      M   25          15  55117\n",
       "3        4      M   45           7  02460\n",
       "4        5      M   25          20  55455"
      ]
     },
     "execution_count": 74,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 验证数据加载是否正确\n",
    "users[:5]\n",
    "# 注意，年龄和职业是以编码形式给出的，具体含义需要参考文件"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 75,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>user_id</th>\n",
       "      <th>movie_id</th>\n",
       "      <th>rating</th>\n",
       "      <th>timestamp</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>1193</td>\n",
       "      <td>5</td>\n",
       "      <td>978300760</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>661</td>\n",
       "      <td>3</td>\n",
       "      <td>978302109</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1</td>\n",
       "      <td>914</td>\n",
       "      <td>3</td>\n",
       "      <td>978301968</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1</td>\n",
       "      <td>3408</td>\n",
       "      <td>4</td>\n",
       "      <td>978300275</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1</td>\n",
       "      <td>2355</td>\n",
       "      <td>5</td>\n",
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       "  </tbody>\n",
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      ],
      "text/plain": [
       "   user_id  movie_id  rating  timestamp\n",
       "0        1      1193       5  978300760\n",
       "1        1       661       3  978302109\n",
       "2        1       914       3  978301968\n",
       "3        1      3408       4  978300275\n",
       "4        1      2355       5  978824291"
      ]
     },
     "execution_count": 75,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ratings[:5]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 76,
   "metadata": {
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   },
   "outputs": [
    {
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       "    <tr style=\"text-align: right;\">\n",
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       "      <td>Adventure|Children's|Fantasy</td>\n",
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       "      <td>Waiting to Exhale (1995)</td>\n",
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       "      <td>5</td>\n",
       "      <td>Father of the Bride Part II (1995)</td>\n",
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      "text/plain": [
       "   movie_id                               title                        genres\n",
       "0         1                    Toy Story (1995)   Animation|Children's|Comedy\n",
       "1         2                      Jumanji (1995)  Adventure|Children's|Fantasy\n",
       "2         3             Grumpier Old Men (1995)                Comedy|Romance\n",
       "3         4            Waiting to Exhale (1995)                  Comedy|Drama\n",
       "4         5  Father of the Bride Part II (1995)                        Comedy"
      ]
     },
     "execution_count": 76,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "movies[:5]"
   ]
  },
  {
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   "metadata": {
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       "      <td>3408</td>\n",
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       "      <td>1287</td>\n",
       "      <td>5</td>\n",
       "      <td>978302039</td>\n",
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       "      <td>978301368</td>\n",
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       "      <td>938</td>\n",
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       "      <td>978301752</td>\n",
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       "      <th>12</th>\n",
       "      <td>1</td>\n",
       "      <td>2398</td>\n",
       "      <td>4</td>\n",
       "      <td>978302281</td>\n",
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       "      <td>1</td>\n",
       "      <td>2918</td>\n",
       "      <td>4</td>\n",
       "      <td>978302124</td>\n",
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       "      <th>14</th>\n",
       "      <td>1</td>\n",
       "      <td>1035</td>\n",
       "      <td>5</td>\n",
       "      <td>978301753</td>\n",
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       "      <th>15</th>\n",
       "      <td>1</td>\n",
       "      <td>2791</td>\n",
       "      <td>4</td>\n",
       "      <td>978302188</td>\n",
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       "      <th>16</th>\n",
       "      <td>1</td>\n",
       "      <td>2687</td>\n",
       "      <td>3</td>\n",
       "      <td>978824268</td>\n",
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       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>1</td>\n",
       "      <td>2018</td>\n",
       "      <td>4</td>\n",
       "      <td>978301777</td>\n",
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       "      <th>18</th>\n",
       "      <td>1</td>\n",
       "      <td>3105</td>\n",
       "      <td>5</td>\n",
       "      <td>978301713</td>\n",
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       "      <th>19</th>\n",
       "      <td>1</td>\n",
       "      <td>2797</td>\n",
       "      <td>4</td>\n",
       "      <td>978302039</td>\n",
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       "      <td>1</td>\n",
       "      <td>2321</td>\n",
       "      <td>3</td>\n",
       "      <td>978302205</td>\n",
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       "      <td>720</td>\n",
       "      <td>3</td>\n",
       "      <td>978300760</td>\n",
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       "      <td>1270</td>\n",
       "      <td>5</td>\n",
       "      <td>978300055</td>\n",
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       "      <td>1</td>\n",
       "      <td>527</td>\n",
       "      <td>5</td>\n",
       "      <td>978824195</td>\n",
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       "      <td>978300103</td>\n",
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       "      <td>978824351</td>\n",
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       "      <td>4</td>\n",
       "      <td>978824139</td>\n",
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       "      <td>1</td>\n",
       "      <td>745</td>\n",
       "      <td>3</td>\n",
       "      <td>978824268</td>\n",
       "    </tr>\n",
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       "      <td>2762</td>\n",
       "      <td>4</td>\n",
       "      <td>956704584</td>\n",
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       "    <tr>\n",
       "      <th>1000180</th>\n",
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       "      <td>1036</td>\n",
       "      <td>3</td>\n",
       "      <td>956715455</td>\n",
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       "    <tr>\n",
       "      <th>1000181</th>\n",
       "      <td>6040</td>\n",
       "      <td>508</td>\n",
       "      <td>4</td>\n",
       "      <td>956704972</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1000182</th>\n",
       "      <td>6040</td>\n",
       "      <td>1041</td>\n",
       "      <td>4</td>\n",
       "      <td>957717678</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1000183</th>\n",
       "      <td>6040</td>\n",
       "      <td>3735</td>\n",
       "      <td>4</td>\n",
       "      <td>960971654</td>\n",
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       "      <th>1000184</th>\n",
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       "      <td>2791</td>\n",
       "      <td>4</td>\n",
       "      <td>956715569</td>\n",
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       "      <td>6040</td>\n",
       "      <td>2794</td>\n",
       "      <td>1</td>\n",
       "      <td>956716438</td>\n",
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       "      <th>1000186</th>\n",
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       "      <td>527</td>\n",
       "      <td>5</td>\n",
       "      <td>956704219</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1000187</th>\n",
       "      <td>6040</td>\n",
       "      <td>2003</td>\n",
       "      <td>1</td>\n",
       "      <td>956716294</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1000188</th>\n",
       "      <td>6040</td>\n",
       "      <td>535</td>\n",
       "      <td>4</td>\n",
       "      <td>964828734</td>\n",
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       "      <th>1000189</th>\n",
       "      <td>6040</td>\n",
       "      <td>2010</td>\n",
       "      <td>5</td>\n",
       "      <td>957716795</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1000190</th>\n",
       "      <td>6040</td>\n",
       "      <td>2011</td>\n",
       "      <td>4</td>\n",
       "      <td>956716113</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1000191</th>\n",
       "      <td>6040</td>\n",
       "      <td>3751</td>\n",
       "      <td>4</td>\n",
       "      <td>964828782</td>\n",
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       "    <tr>\n",
       "      <th>1000192</th>\n",
       "      <td>6040</td>\n",
       "      <td>2019</td>\n",
       "      <td>5</td>\n",
       "      <td>956703977</td>\n",
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       "    <tr>\n",
       "      <th>1000193</th>\n",
       "      <td>6040</td>\n",
       "      <td>541</td>\n",
       "      <td>4</td>\n",
       "      <td>956715288</td>\n",
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       "    <tr>\n",
       "      <th>1000194</th>\n",
       "      <td>6040</td>\n",
       "      <td>1077</td>\n",
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       "      <td>964828799</td>\n",
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       "    <tr>\n",
       "      <th>1000195</th>\n",
       "      <td>6040</td>\n",
       "      <td>1079</td>\n",
       "      <td>2</td>\n",
       "      <td>956715648</td>\n",
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       "    <tr>\n",
       "      <th>1000196</th>\n",
       "      <td>6040</td>\n",
       "      <td>549</td>\n",
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       "      <td>956704746</td>\n",
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       "      <th>1000197</th>\n",
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       "      <th>1000198</th>\n",
       "      <td>6040</td>\n",
       "      <td>2021</td>\n",
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       "      <td>956716374</td>\n",
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       "    <tr>\n",
       "      <th>1000199</th>\n",
       "      <td>6040</td>\n",
       "      <td>2022</td>\n",
       "      <td>5</td>\n",
       "      <td>956716207</td>\n",
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       "    <tr>\n",
       "      <th>1000200</th>\n",
       "      <td>6040</td>\n",
       "      <td>2028</td>\n",
       "      <td>5</td>\n",
       "      <td>956704519</td>\n",
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       "    <tr>\n",
       "      <th>1000201</th>\n",
       "      <td>6040</td>\n",
       "      <td>1080</td>\n",
       "      <td>4</td>\n",
       "      <td>957717322</td>\n",
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       "      <th>1000202</th>\n",
       "      <td>6040</td>\n",
       "      <td>1089</td>\n",
       "      <td>4</td>\n",
       "      <td>956704996</td>\n",
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       "    <tr>\n",
       "      <th>1000203</th>\n",
       "      <td>6040</td>\n",
       "      <td>1090</td>\n",
       "      <td>3</td>\n",
       "      <td>956715518</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1000204</th>\n",
       "      <td>6040</td>\n",
       "      <td>1091</td>\n",
       "      <td>1</td>\n",
       "      <td>956716541</td>\n",
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       "    <tr>\n",
       "      <th>1000205</th>\n",
       "      <td>6040</td>\n",
       "      <td>1094</td>\n",
       "      <td>5</td>\n",
       "      <td>956704887</td>\n",
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       "    <tr>\n",
       "      <th>1000206</th>\n",
       "      <td>6040</td>\n",
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       "      <td>5</td>\n",
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       "      <td>6040</td>\n",
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       "  </tbody>\n",
       "</table>\n",
       "<p>1000209 rows × 4 columns</p>\n",
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      ],
      "text/plain": [
       "         user_id  movie_id  rating  timestamp\n",
       "0              1      1193       5  978300760\n",
       "1              1       661       3  978302109\n",
       "2              1       914       3  978301968\n",
       "3              1      3408       4  978300275\n",
       "4              1      2355       5  978824291\n",
       "5              1      1197       3  978302268\n",
       "6              1      1287       5  978302039\n",
       "7              1      2804       5  978300719\n",
       "8              1       594       4  978302268\n",
       "9              1       919       4  978301368\n",
       "10             1       595       5  978824268\n",
       "11             1       938       4  978301752\n",
       "12             1      2398       4  978302281\n",
       "13             1      2918       4  978302124\n",
       "14             1      1035       5  978301753\n",
       "15             1      2791       4  978302188\n",
       "16             1      2687       3  978824268\n",
       "17             1      2018       4  978301777\n",
       "18             1      3105       5  978301713\n",
       "19             1      2797       4  978302039\n",
       "20             1      2321       3  978302205\n",
       "21             1       720       3  978300760\n",
       "22             1      1270       5  978300055\n",
       "23             1       527       5  978824195\n",
       "24             1      2340       3  978300103\n",
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       "26             1      1097       4  978301953\n",
       "27             1      1721       4  978300055\n",
       "28             1      1545       4  978824139\n",
       "29             1       745       3  978824268\n",
       "...          ...       ...     ...        ...\n",
       "1000179     6040      2762       4  956704584\n",
       "1000180     6040      1036       3  956715455\n",
       "1000181     6040       508       4  956704972\n",
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       "1000185     6040      2794       1  956716438\n",
       "1000186     6040       527       5  956704219\n",
       "1000187     6040      2003       1  956716294\n",
       "1000188     6040       535       4  964828734\n",
       "1000189     6040      2010       5  957716795\n",
       "1000190     6040      2011       4  956716113\n",
       "1000191     6040      3751       4  964828782\n",
       "1000192     6040      2019       5  956703977\n",
       "1000193     6040       541       4  956715288\n",
       "1000194     6040      1077       5  964828799\n",
       "1000195     6040      1079       2  956715648\n",
       "1000196     6040       549       4  956704746\n",
       "1000197     6040      2020       3  956715288\n",
       "1000198     6040      2021       3  956716374\n",
       "1000199     6040      2022       5  956716207\n",
       "1000200     6040      2028       5  956704519\n",
       "1000201     6040      1080       4  957717322\n",
       "1000202     6040      1089       4  956704996\n",
       "1000203     6040      1090       3  956715518\n",
       "1000204     6040      1091       1  956716541\n",
       "1000205     6040      1094       5  956704887\n",
       "1000206     6040       562       5  956704746\n",
       "1000207     6040      1096       4  956715648\n",
       "1000208     6040      1097       4  956715569\n",
       "\n",
       "[1000209 rows x 4 columns]"
      ]
     },
     "execution_count": 77,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ratings"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 78,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# 假设我们想要根据性别和年龄计算某部电影的平均得分先用pandas的merge函数将ratings跟users合并到一起，\n",
    "# 然后再将movies也合并进去，pandas会根据列明的重叠情况判断出哪些列是合并键\n",
    "data = pd.merge(pd.merge(ratings, users), movies)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 79,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
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       "      <td>35</td>\n",
       "      <td>3</td>\n",
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       "      <th>21</th>\n",
       "      <td>80</td>\n",
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       "      <td>56</td>\n",
       "      <td>1</td>\n",
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       "    <tr>\n",
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       "    </tr>\n",
       "    <tr>\n",
       "      <th>1000183</th>\n",
       "      <td>5059</td>\n",
       "      <td>1434</td>\n",
       "      <td>4</td>\n",
       "      <td>962484364</td>\n",
       "      <td>M</td>\n",
       "      <td>45</td>\n",
       "      <td>16</td>\n",
       "      <td>22652</td>\n",
       "      <td>Stranger, The (1994)</td>\n",
       "      <td>Action</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1000184</th>\n",
       "      <td>5947</td>\n",
       "      <td>1434</td>\n",
       "      <td>4</td>\n",
       "      <td>957190428</td>\n",
       "      <td>F</td>\n",
       "      <td>45</td>\n",
       "      <td>16</td>\n",
       "      <td>97215</td>\n",
       "      <td>Stranger, The (1994)</td>\n",
       "      <td>Action</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1000185</th>\n",
       "      <td>5077</td>\n",
       "      <td>1868</td>\n",
       "      <td>3</td>\n",
       "      <td>962417299</td>\n",
       "      <td>M</td>\n",
       "      <td>25</td>\n",
       "      <td>2</td>\n",
       "      <td>20037</td>\n",
       "      <td>Truce, The (1996)</td>\n",
       "      <td>Drama|War</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1000186</th>\n",
       "      <td>5944</td>\n",
       "      <td>1868</td>\n",
       "      <td>1</td>\n",
       "      <td>957197520</td>\n",
       "      <td>F</td>\n",
       "      <td>18</td>\n",
       "      <td>10</td>\n",
       "      <td>27606</td>\n",
       "      <td>Truce, The (1996)</td>\n",
       "      <td>Drama|War</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1000187</th>\n",
       "      <td>5105</td>\n",
       "      <td>404</td>\n",
       "      <td>3</td>\n",
       "      <td>962337582</td>\n",
       "      <td>M</td>\n",
       "      <td>50</td>\n",
       "      <td>7</td>\n",
       "      <td>18977</td>\n",
       "      <td>Brother Minister: The Assassination of Malcolm...</td>\n",
       "      <td>Documentary</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1000188</th>\n",
       "      <td>5185</td>\n",
       "      <td>404</td>\n",
       "      <td>4</td>\n",
       "      <td>963402617</td>\n",
       "      <td>F</td>\n",
       "      <td>35</td>\n",
       "      <td>4</td>\n",
       "      <td>44485</td>\n",
       "      <td>Brother Minister: The Assassination of Malcolm...</td>\n",
       "      <td>Documentary</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1000189</th>\n",
       "      <td>5532</td>\n",
       "      <td>404</td>\n",
       "      <td>5</td>\n",
       "      <td>959619841</td>\n",
       "      <td>M</td>\n",
       "      <td>25</td>\n",
       "      <td>17</td>\n",
       "      <td>27408</td>\n",
       "      <td>Brother Minister: The Assassination of Malcolm...</td>\n",
       "      <td>Documentary</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1000190</th>\n",
       "      <td>5543</td>\n",
       "      <td>404</td>\n",
       "      <td>3</td>\n",
       "      <td>960127592</td>\n",
       "      <td>M</td>\n",
       "      <td>25</td>\n",
       "      <td>17</td>\n",
       "      <td>97401</td>\n",
       "      <td>Brother Minister: The Assassination of Malcolm...</td>\n",
       "      <td>Documentary</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1000191</th>\n",
       "      <td>5220</td>\n",
       "      <td>2543</td>\n",
       "      <td>3</td>\n",
       "      <td>961546137</td>\n",
       "      <td>M</td>\n",
       "      <td>25</td>\n",
       "      <td>7</td>\n",
       "      <td>91436</td>\n",
       "      <td>Six Ways to Sunday (1997)</td>\n",
       "      <td>Comedy</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1000192</th>\n",
       "      <td>5754</td>\n",
       "      <td>2543</td>\n",
       "      <td>4</td>\n",
       "      <td>958272316</td>\n",
       "      <td>F</td>\n",
       "      <td>18</td>\n",
       "      <td>1</td>\n",
       "      <td>60640</td>\n",
       "      <td>Six Ways to Sunday (1997)</td>\n",
       "      <td>Comedy</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1000193</th>\n",
       "      <td>5227</td>\n",
       "      <td>591</td>\n",
       "      <td>3</td>\n",
       "      <td>961475931</td>\n",
       "      <td>M</td>\n",
       "      <td>18</td>\n",
       "      <td>10</td>\n",
       "      <td>64050</td>\n",
       "      <td>Tough and Deadly (1995)</td>\n",
       "      <td>Action|Drama|Thriller</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1000194</th>\n",
       "      <td>5795</td>\n",
       "      <td>591</td>\n",
       "      <td>1</td>\n",
       "      <td>958145253</td>\n",
       "      <td>M</td>\n",
       "      <td>25</td>\n",
       "      <td>1</td>\n",
       "      <td>92688</td>\n",
       "      <td>Tough and Deadly (1995)</td>\n",
       "      <td>Action|Drama|Thriller</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1000195</th>\n",
       "      <td>5313</td>\n",
       "      <td>3656</td>\n",
       "      <td>5</td>\n",
       "      <td>960920392</td>\n",
       "      <td>M</td>\n",
       "      <td>56</td>\n",
       "      <td>0</td>\n",
       "      <td>55406</td>\n",
       "      <td>Lured (1947)</td>\n",
       "      <td>Crime</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1000196</th>\n",
       "      <td>5328</td>\n",
       "      <td>2438</td>\n",
       "      <td>4</td>\n",
       "      <td>960838075</td>\n",
       "      <td>F</td>\n",
       "      <td>25</td>\n",
       "      <td>4</td>\n",
       "      <td>91740</td>\n",
       "      <td>Outside Ozona (1998)</td>\n",
       "      <td>Drama|Thriller</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1000197</th>\n",
       "      <td>5334</td>\n",
       "      <td>3323</td>\n",
       "      <td>3</td>\n",
       "      <td>960796159</td>\n",
       "      <td>F</td>\n",
       "      <td>56</td>\n",
       "      <td>13</td>\n",
       "      <td>46140</td>\n",
       "      <td>Chain of Fools (2000)</td>\n",
       "      <td>Comedy|Crime</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1000198</th>\n",
       "      <td>5334</td>\n",
       "      <td>127</td>\n",
       "      <td>1</td>\n",
       "      <td>960795494</td>\n",
       "      <td>F</td>\n",
       "      <td>56</td>\n",
       "      <td>13</td>\n",
       "      <td>46140</td>\n",
       "      <td>Silence of the Palace, The (Saimt el Qusur) (1...</td>\n",
       "      <td>Drama</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1000199</th>\n",
       "      <td>5334</td>\n",
       "      <td>3382</td>\n",
       "      <td>5</td>\n",
       "      <td>960796159</td>\n",
       "      <td>F</td>\n",
       "      <td>56</td>\n",
       "      <td>13</td>\n",
       "      <td>46140</td>\n",
       "      <td>Song of Freedom (1936)</td>\n",
       "      <td>Drama</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1000200</th>\n",
       "      <td>5420</td>\n",
       "      <td>1843</td>\n",
       "      <td>3</td>\n",
       "      <td>960156505</td>\n",
       "      <td>F</td>\n",
       "      <td>1</td>\n",
       "      <td>19</td>\n",
       "      <td>14850</td>\n",
       "      <td>Slappy and the Stinkers (1998)</td>\n",
       "      <td>Children's|Comedy</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1000201</th>\n",
       "      <td>5433</td>\n",
       "      <td>286</td>\n",
       "      <td>3</td>\n",
       "      <td>960240881</td>\n",
       "      <td>F</td>\n",
       "      <td>35</td>\n",
       "      <td>17</td>\n",
       "      <td>45014</td>\n",
       "      <td>Nemesis 2: Nebula (1995)</td>\n",
       "      <td>Action|Sci-Fi|Thriller</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1000202</th>\n",
       "      <td>5494</td>\n",
       "      <td>3530</td>\n",
       "      <td>4</td>\n",
       "      <td>959816296</td>\n",
       "      <td>F</td>\n",
       "      <td>35</td>\n",
       "      <td>17</td>\n",
       "      <td>94306</td>\n",
       "      <td>Smoking/No Smoking (1993)</td>\n",
       "      <td>Comedy</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1000203</th>\n",
       "      <td>5556</td>\n",
       "      <td>2198</td>\n",
       "      <td>3</td>\n",
       "      <td>959445515</td>\n",
       "      <td>M</td>\n",
       "      <td>45</td>\n",
       "      <td>6</td>\n",
       "      <td>92103</td>\n",
       "      <td>Modulations (1998)</td>\n",
       "      <td>Documentary</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1000204</th>\n",
       "      <td>5949</td>\n",
       "      <td>2198</td>\n",
       "      <td>5</td>\n",
       "      <td>958846401</td>\n",
       "      <td>M</td>\n",
       "      <td>18</td>\n",
       "      <td>17</td>\n",
       "      <td>47901</td>\n",
       "      <td>Modulations (1998)</td>\n",
       "      <td>Documentary</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1000205</th>\n",
       "      <td>5675</td>\n",
       "      <td>2703</td>\n",
       "      <td>3</td>\n",
       "      <td>976029116</td>\n",
       "      <td>M</td>\n",
       "      <td>35</td>\n",
       "      <td>14</td>\n",
       "      <td>30030</td>\n",
       "      <td>Broken Vessels (1998)</td>\n",
       "      <td>Drama</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1000206</th>\n",
       "      <td>5780</td>\n",
       "      <td>2845</td>\n",
       "      <td>1</td>\n",
       "      <td>958153068</td>\n",
       "      <td>M</td>\n",
       "      <td>18</td>\n",
       "      <td>17</td>\n",
       "      <td>92886</td>\n",
       "      <td>White Boys (1999)</td>\n",
       "      <td>Drama</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1000207</th>\n",
       "      <td>5851</td>\n",
       "      <td>3607</td>\n",
       "      <td>5</td>\n",
       "      <td>957756608</td>\n",
       "      <td>F</td>\n",
       "      <td>18</td>\n",
       "      <td>20</td>\n",
       "      <td>55410</td>\n",
       "      <td>One Little Indian (1973)</td>\n",
       "      <td>Comedy|Drama|Western</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1000208</th>\n",
       "      <td>5938</td>\n",
       "      <td>2909</td>\n",
       "      <td>4</td>\n",
       "      <td>957273353</td>\n",
       "      <td>M</td>\n",
       "      <td>25</td>\n",
       "      <td>1</td>\n",
       "      <td>35401</td>\n",
       "      <td>Five Wives, Three Secretaries and Me (1998)</td>\n",
       "      <td>Documentary</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>1000209 rows × 10 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "         user_id  movie_id  rating   timestamp gender  age  occupation    zip  \\\n",
       "0              1      1193       5   978300760      F    1          10  48067   \n",
       "1              2      1193       5   978298413      M   56          16  70072   \n",
       "2             12      1193       4   978220179      M   25          12  32793   \n",
       "3             15      1193       4   978199279      M   25           7  22903   \n",
       "4             17      1193       5   978158471      M   50           1  95350   \n",
       "5             18      1193       4   978156168      F   18           3  95825   \n",
       "6             19      1193       5   982730936      M    1          10  48073   \n",
       "7             24      1193       5   978136709      F   25           7  10023   \n",
       "8             28      1193       3   978125194      F   25           1  14607   \n",
       "9             33      1193       5   978557765      M   45           3  55421   \n",
       "10            39      1193       5   978043535      M   18           4  61820   \n",
       "11            42      1193       3   978038981      M   25           8  24502   \n",
       "12            44      1193       4   978018995      M   45          17  98052   \n",
       "13            47      1193       4   977978345      M   18           4  94305   \n",
       "14            48      1193       4   977975061      M   25           4  92107   \n",
       "15            49      1193       4   978813972      M   18          12  77084   \n",
       "16            53      1193       5   977946400      M   25           0  96931   \n",
       "17            54      1193       5   977944039      M   50           1  56723   \n",
       "18            58      1193       5   977933866      M   25           2  30303   \n",
       "19            59      1193       4   977934292      F   50           1  55413   \n",
       "20            62      1193       4   977968584      F   35           3  98105   \n",
       "21            80      1193       4   977786172      M   56           1  49327   \n",
       "22            81      1193       5   977785864      F   25           0  60640   \n",
       "23            88      1193       5   977694161      F   45           1  02476   \n",
       "24            89      1193       5   977683596      F   56           9  85749   \n",
       "25            95      1193       5   977626632      M   45           0  98201   \n",
       "26            96      1193       3   977621789      F   25          16  78028   \n",
       "27            99      1193       2   982791053      F    1          10  19390   \n",
       "28           102      1193       5  1040737607      M   35          19  20871   \n",
       "29           104      1193       2   977546620      M   25          12  00926   \n",
       "...          ...       ...     ...         ...    ...  ...         ...    ...   \n",
       "1000179     4933      3084       3   962757020      M   25          15  94040   \n",
       "1000180     4802      2218       2  1014866656      M   56           1  40601   \n",
       "1000181     4812      2308       2   962932391      M   18          14  25301   \n",
       "1000182     4874       624       4   962781918      F   25           4  70808   \n",
       "1000183     5059      1434       4   962484364      M   45          16  22652   \n",
       "1000184     5947      1434       4   957190428      F   45          16  97215   \n",
       "1000185     5077      1868       3   962417299      M   25           2  20037   \n",
       "1000186     5944      1868       1   957197520      F   18          10  27606   \n",
       "1000187     5105       404       3   962337582      M   50           7  18977   \n",
       "1000188     5185       404       4   963402617      F   35           4  44485   \n",
       "1000189     5532       404       5   959619841      M   25          17  27408   \n",
       "1000190     5543       404       3   960127592      M   25          17  97401   \n",
       "1000191     5220      2543       3   961546137      M   25           7  91436   \n",
       "1000192     5754      2543       4   958272316      F   18           1  60640   \n",
       "1000193     5227       591       3   961475931      M   18          10  64050   \n",
       "1000194     5795       591       1   958145253      M   25           1  92688   \n",
       "1000195     5313      3656       5   960920392      M   56           0  55406   \n",
       "1000196     5328      2438       4   960838075      F   25           4  91740   \n",
       "1000197     5334      3323       3   960796159      F   56          13  46140   \n",
       "1000198     5334       127       1   960795494      F   56          13  46140   \n",
       "1000199     5334      3382       5   960796159      F   56          13  46140   \n",
       "1000200     5420      1843       3   960156505      F    1          19  14850   \n",
       "1000201     5433       286       3   960240881      F   35          17  45014   \n",
       "1000202     5494      3530       4   959816296      F   35          17  94306   \n",
       "1000203     5556      2198       3   959445515      M   45           6  92103   \n",
       "1000204     5949      2198       5   958846401      M   18          17  47901   \n",
       "1000205     5675      2703       3   976029116      M   35          14  30030   \n",
       "1000206     5780      2845       1   958153068      M   18          17  92886   \n",
       "1000207     5851      3607       5   957756608      F   18          20  55410   \n",
       "1000208     5938      2909       4   957273353      M   25           1  35401   \n",
       "\n",
       "                                                     title  \\\n",
       "0                   One Flew Over the Cuckoo's Nest (1975)   \n",
       "1                   One Flew Over the Cuckoo's Nest (1975)   \n",
       "2                   One Flew Over the Cuckoo's Nest (1975)   \n",
       "3                   One Flew Over the Cuckoo's Nest (1975)   \n",
       "4                   One Flew Over the Cuckoo's Nest (1975)   \n",
       "5                   One Flew Over the Cuckoo's Nest (1975)   \n",
       "6                   One Flew Over the Cuckoo's Nest (1975)   \n",
       "7                   One Flew Over the Cuckoo's Nest (1975)   \n",
       "8                   One Flew Over the Cuckoo's Nest (1975)   \n",
       "9                   One Flew Over the Cuckoo's Nest (1975)   \n",
       "10                  One Flew Over the Cuckoo's Nest (1975)   \n",
       "11                  One Flew Over the Cuckoo's Nest (1975)   \n",
       "12                  One Flew Over the Cuckoo's Nest (1975)   \n",
       "13                  One Flew Over the Cuckoo's Nest (1975)   \n",
       "14                  One Flew Over the Cuckoo's Nest (1975)   \n",
       "15                  One Flew Over the Cuckoo's Nest (1975)   \n",
       "16                  One Flew Over the Cuckoo's Nest (1975)   \n",
       "17                  One Flew Over the Cuckoo's Nest (1975)   \n",
       "18                  One Flew Over the Cuckoo's Nest (1975)   \n",
       "19                  One Flew Over the Cuckoo's Nest (1975)   \n",
       "20                  One Flew Over the Cuckoo's Nest (1975)   \n",
       "21                  One Flew Over the Cuckoo's Nest (1975)   \n",
       "22                  One Flew Over the Cuckoo's Nest (1975)   \n",
       "23                  One Flew Over the Cuckoo's Nest (1975)   \n",
       "24                  One Flew Over the Cuckoo's Nest (1975)   \n",
       "25                  One Flew Over the Cuckoo's Nest (1975)   \n",
       "26                  One Flew Over the Cuckoo's Nest (1975)   \n",
       "27                  One Flew Over the Cuckoo's Nest (1975)   \n",
       "28                  One Flew Over the Cuckoo's Nest (1975)   \n",
       "29                  One Flew Over the Cuckoo's Nest (1975)   \n",
       "...                                                    ...   \n",
       "1000179                                   Home Page (1999)   \n",
       "1000180                            Juno and Paycock (1930)   \n",
       "1000181                                Detroit 9000 (1973)   \n",
       "1000182                               Condition Red (1995)   \n",
       "1000183                               Stranger, The (1994)   \n",
       "1000184                               Stranger, The (1994)   \n",
       "1000185                                  Truce, The (1996)   \n",
       "1000186                                  Truce, The (1996)   \n",
       "1000187  Brother Minister: The Assassination of Malcolm...   \n",
       "1000188  Brother Minister: The Assassination of Malcolm...   \n",
       "1000189  Brother Minister: The Assassination of Malcolm...   \n",
       "1000190  Brother Minister: The Assassination of Malcolm...   \n",
       "1000191                          Six Ways to Sunday (1997)   \n",
       "1000192                          Six Ways to Sunday (1997)   \n",
       "1000193                            Tough and Deadly (1995)   \n",
       "1000194                            Tough and Deadly (1995)   \n",
       "1000195                                       Lured (1947)   \n",
       "1000196                               Outside Ozona (1998)   \n",
       "1000197                              Chain of Fools (2000)   \n",
       "1000198  Silence of the Palace, The (Saimt el Qusur) (1...   \n",
       "1000199                             Song of Freedom (1936)   \n",
       "1000200                     Slappy and the Stinkers (1998)   \n",
       "1000201                           Nemesis 2: Nebula (1995)   \n",
       "1000202                          Smoking/No Smoking (1993)   \n",
       "1000203                                 Modulations (1998)   \n",
       "1000204                                 Modulations (1998)   \n",
       "1000205                              Broken Vessels (1998)   \n",
       "1000206                                  White Boys (1999)   \n",
       "1000207                           One Little Indian (1973)   \n",
       "1000208        Five Wives, Three Secretaries and Me (1998)   \n",
       "\n",
       "                         genres  \n",
       "0                         Drama  \n",
       "1                         Drama  \n",
       "2                         Drama  \n",
       "3                         Drama  \n",
       "4                         Drama  \n",
       "5                         Drama  \n",
       "6                         Drama  \n",
       "7                         Drama  \n",
       "8                         Drama  \n",
       "9                         Drama  \n",
       "10                        Drama  \n",
       "11                        Drama  \n",
       "12                        Drama  \n",
       "13                        Drama  \n",
       "14                        Drama  \n",
       "15                        Drama  \n",
       "16                        Drama  \n",
       "17                        Drama  \n",
       "18                        Drama  \n",
       "19                        Drama  \n",
       "20                        Drama  \n",
       "21                        Drama  \n",
       "22                        Drama  \n",
       "23                        Drama  \n",
       "24                        Drama  \n",
       "25                        Drama  \n",
       "26                        Drama  \n",
       "27                        Drama  \n",
       "28                        Drama  \n",
       "29                        Drama  \n",
       "...                         ...  \n",
       "1000179             Documentary  \n",
       "1000180                   Drama  \n",
       "1000181            Action|Crime  \n",
       "1000182   Action|Drama|Thriller  \n",
       "1000183                  Action  \n",
       "1000184                  Action  \n",
       "1000185               Drama|War  \n",
       "1000186               Drama|War  \n",
       "1000187             Documentary  \n",
       "1000188             Documentary  \n",
       "1000189             Documentary  \n",
       "1000190             Documentary  \n",
       "1000191                  Comedy  \n",
       "1000192                  Comedy  \n",
       "1000193   Action|Drama|Thriller  \n",
       "1000194   Action|Drama|Thriller  \n",
       "1000195                   Crime  \n",
       "1000196          Drama|Thriller  \n",
       "1000197            Comedy|Crime  \n",
       "1000198                   Drama  \n",
       "1000199                   Drama  \n",
       "1000200       Children's|Comedy  \n",
       "1000201  Action|Sci-Fi|Thriller  \n",
       "1000202                  Comedy  \n",
       "1000203             Documentary  \n",
       "1000204             Documentary  \n",
       "1000205                   Drama  \n",
       "1000206                   Drama  \n",
       "1000207    Comedy|Drama|Western  \n",
       "1000208             Documentary  \n",
       "\n",
       "[1000209 rows x 10 columns]"
      ]
     },
     "execution_count": 79,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 82,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "user_id                                            1\n",
       "movie_id                                        1193\n",
       "rating                                             5\n",
       "timestamp                                  978300760\n",
       "gender                                             F\n",
       "age                                                1\n",
       "occupation                                        10\n",
       "zip                                            48067\n",
       "title         One Flew Over the Cuckoo's Nest (1975)\n",
       "genres                                         Drama\n",
       "Name: 0, dtype: object"
      ]
     },
     "execution_count": 82,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# pandas 按x轴取（行），ix[0]代表取第一行\n",
    "data.ix[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 86,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "mean_ratings = data.pivot_table('rating', index='title', columns='gender', aggfunc='mean')\n",
    "# 此处书中有参数错误， 版本原因。\n",
    "# rows改为index，cols改为columns"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 87,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th>gender</th>\n",
       "      <th>F</th>\n",
       "      <th>M</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>title</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>$1,000,000 Duck (1971)</th>\n",
       "      <td>3.375000</td>\n",
       "      <td>2.761905</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>'Night Mother (1986)</th>\n",
       "      <td>3.388889</td>\n",
       "      <td>3.352941</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>'Til There Was You (1997)</th>\n",
       "      <td>2.675676</td>\n",
       "      <td>2.733333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>'burbs, The (1989)</th>\n",
       "      <td>2.793478</td>\n",
       "      <td>2.962085</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...And Justice for All (1979)</th>\n",
       "      <td>3.828571</td>\n",
       "      <td>3.689024</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1-900 (1994)</th>\n",
       "      <td>2.000000</td>\n",
       "      <td>3.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10 Things I Hate About You (1999)</th>\n",
       "      <td>3.646552</td>\n",
       "      <td>3.311966</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>101 Dalmatians (1961)</th>\n",
       "      <td>3.791444</td>\n",
       "      <td>3.500000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>101 Dalmatians (1996)</th>\n",
       "      <td>3.240000</td>\n",
       "      <td>2.911215</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12 Angry Men (1957)</th>\n",
       "      <td>4.184397</td>\n",
       "      <td>4.328421</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13th Warrior, The (1999)</th>\n",
       "      <td>3.112000</td>\n",
       "      <td>3.168000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>187 (1997)</th>\n",
       "      <td>2.428571</td>\n",
       "      <td>2.791667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2 Days in the Valley (1996)</th>\n",
       "      <td>3.488889</td>\n",
       "      <td>3.244813</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20 Dates (1998)</th>\n",
       "      <td>2.620690</td>\n",
       "      <td>2.918182</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20,000 Leagues Under the Sea (1954)</th>\n",
       "      <td>3.670103</td>\n",
       "      <td>3.709205</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>200 Cigarettes (1999)</th>\n",
       "      <td>3.169014</td>\n",
       "      <td>2.700000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2001: A Space Odyssey (1968)</th>\n",
       "      <td>3.825581</td>\n",
       "      <td>4.129738</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2010 (1984)</th>\n",
       "      <td>3.446809</td>\n",
       "      <td>3.413712</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24 7: Twenty Four Seven (1997)</th>\n",
       "      <td>5.000000</td>\n",
       "      <td>3.750000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24-hour Woman (1998)</th>\n",
       "      <td>2.000000</td>\n",
       "      <td>1.600000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28 Days (2000)</th>\n",
       "      <td>3.209424</td>\n",
       "      <td>2.977707</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3 Ninjas: High Noon On Mega Mountain (1998)</th>\n",
       "      <td>1.400000</td>\n",
       "      <td>1.351351</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3 Strikes (2000)</th>\n",
       "      <td>NaN</td>\n",
       "      <td>2.750000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>301, 302 (1995)</th>\n",
       "      <td>3.000000</td>\n",
       "      <td>2.857143</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>39 Steps, The (1935)</th>\n",
       "      <td>3.965517</td>\n",
       "      <td>4.107692</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>400 Blows, The (Les Quatre cents coups) (1959)</th>\n",
       "      <td>4.489362</td>\n",
       "      <td>4.264286</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>42 Up (1998)</th>\n",
       "      <td>3.966667</td>\n",
       "      <td>4.362069</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>52 Pick-Up (1986)</th>\n",
       "      <td>3.304348</td>\n",
       "      <td>3.299145</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>54 (1998)</th>\n",
       "      <td>2.701754</td>\n",
       "      <td>2.782178</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7th Voyage of Sinbad, The (1958)</th>\n",
       "      <td>3.409091</td>\n",
       "      <td>3.658879</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Wrongfully Accused (1998)</th>\n",
       "      <td>2.666667</td>\n",
       "      <td>2.540541</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Wyatt Earp (1994)</th>\n",
       "      <td>3.147059</td>\n",
       "      <td>3.283898</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>X-Files: Fight the Future, The (1998)</th>\n",
       "      <td>3.489474</td>\n",
       "      <td>3.493797</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>X-Men (2000)</th>\n",
       "      <td>3.682310</td>\n",
       "      <td>3.851702</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>X: The Unknown (1956)</th>\n",
       "      <td>2.250000</td>\n",
       "      <td>3.125000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Xiu Xiu: The Sent-Down Girl (Tian yu) (1998)</th>\n",
       "      <td>3.821429</td>\n",
       "      <td>3.536585</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Yankee Zulu (1994)</th>\n",
       "      <td>3.000000</td>\n",
       "      <td>3.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Yards, The (1999)</th>\n",
       "      <td>2.687500</td>\n",
       "      <td>3.360656</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Year My Voice Broke, The (1987)</th>\n",
       "      <td>4.000000</td>\n",
       "      <td>3.705882</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Year of Living Dangerously (1982)</th>\n",
       "      <td>3.951220</td>\n",
       "      <td>3.869403</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Year of the Horse (1997)</th>\n",
       "      <td>NaN</td>\n",
       "      <td>3.250000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Yellow Submarine (1968)</th>\n",
       "      <td>3.714286</td>\n",
       "      <td>3.689286</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Yojimbo (1961)</th>\n",
       "      <td>4.423077</td>\n",
       "      <td>4.402116</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>You Can't Take It With You (1938)</th>\n",
       "      <td>4.192308</td>\n",
       "      <td>3.921569</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>You So Crazy (1994)</th>\n",
       "      <td>3.666667</td>\n",
       "      <td>2.300000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>You've Got Mail (1998)</th>\n",
       "      <td>3.542424</td>\n",
       "      <td>3.275591</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Young Doctors in Love (1982)</th>\n",
       "      <td>1.923077</td>\n",
       "      <td>2.742424</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Young Frankenstein (1974)</th>\n",
       "      <td>4.289963</td>\n",
       "      <td>4.239177</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Young Guns (1988)</th>\n",
       "      <td>3.371795</td>\n",
       "      <td>3.425620</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Young Guns II (1990)</th>\n",
       "      <td>2.934783</td>\n",
       "      <td>2.904025</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Young Poisoner's Handbook, The (1995)</th>\n",
       "      <td>4.000000</td>\n",
       "      <td>3.532258</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Young Sherlock Holmes (1985)</th>\n",
       "      <td>3.514706</td>\n",
       "      <td>3.363344</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Young and Innocent (1937)</th>\n",
       "      <td>2.500000</td>\n",
       "      <td>3.500000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Your Friends and Neighbors (1998)</th>\n",
       "      <td>2.888889</td>\n",
       "      <td>3.536585</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Zachariah (1971)</th>\n",
       "      <td>NaN</td>\n",
       "      <td>3.500000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Zed &amp; Two Noughts, A (1985)</th>\n",
       "      <td>3.500000</td>\n",
       "      <td>3.380952</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Zero Effect (1998)</th>\n",
       "      <td>3.864407</td>\n",
       "      <td>3.723140</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Zero Kelvin (Kj�rlighetens kj�tere) (1995)</th>\n",
       "      <td>NaN</td>\n",
       "      <td>3.500000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Zeus and Roxanne (1997)</th>\n",
       "      <td>2.777778</td>\n",
       "      <td>2.357143</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>eXistenZ (1999)</th>\n",
       "      <td>3.098592</td>\n",
       "      <td>3.289086</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>3706 rows × 2 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "gender                                                 F         M\n",
       "title                                                             \n",
       "$1,000,000 Duck (1971)                          3.375000  2.761905\n",
       "'Night Mother (1986)                            3.388889  3.352941\n",
       "'Til There Was You (1997)                       2.675676  2.733333\n",
       "'burbs, The (1989)                              2.793478  2.962085\n",
       "...And Justice for All (1979)                   3.828571  3.689024\n",
       "1-900 (1994)                                    2.000000  3.000000\n",
       "10 Things I Hate About You (1999)               3.646552  3.311966\n",
       "101 Dalmatians (1961)                           3.791444  3.500000\n",
       "101 Dalmatians (1996)                           3.240000  2.911215\n",
       "12 Angry Men (1957)                             4.184397  4.328421\n",
       "13th Warrior, The (1999)                        3.112000  3.168000\n",
       "187 (1997)                                      2.428571  2.791667\n",
       "2 Days in the Valley (1996)                     3.488889  3.244813\n",
       "20 Dates (1998)                                 2.620690  2.918182\n",
       "20,000 Leagues Under the Sea (1954)             3.670103  3.709205\n",
       "200 Cigarettes (1999)                           3.169014  2.700000\n",
       "2001: A Space Odyssey (1968)                    3.825581  4.129738\n",
       "2010 (1984)                                     3.446809  3.413712\n",
       "24 7: Twenty Four Seven (1997)                  5.000000  3.750000\n",
       "24-hour Woman (1998)                            2.000000  1.600000\n",
       "28 Days (2000)                                  3.209424  2.977707\n",
       "3 Ninjas: High Noon On Mega Mountain (1998)     1.400000  1.351351\n",
       "3 Strikes (2000)                                     NaN  2.750000\n",
       "301, 302 (1995)                                 3.000000  2.857143\n",
       "39 Steps, The (1935)                            3.965517  4.107692\n",
       "400 Blows, The (Les Quatre cents coups) (1959)  4.489362  4.264286\n",
       "42 Up (1998)                                    3.966667  4.362069\n",
       "52 Pick-Up (1986)                               3.304348  3.299145\n",
       "54 (1998)                                       2.701754  2.782178\n",
       "7th Voyage of Sinbad, The (1958)                3.409091  3.658879\n",
       "...                                                  ...       ...\n",
       "Wrongfully Accused (1998)                       2.666667  2.540541\n",
       "Wyatt Earp (1994)                               3.147059  3.283898\n",
       "X-Files: Fight the Future, The (1998)           3.489474  3.493797\n",
       "X-Men (2000)                                    3.682310  3.851702\n",
       "X: The Unknown (1956)                           2.250000  3.125000\n",
       "Xiu Xiu: The Sent-Down Girl (Tian yu) (1998)    3.821429  3.536585\n",
       "Yankee Zulu (1994)                              3.000000  3.000000\n",
       "Yards, The (1999)                               2.687500  3.360656\n",
       "Year My Voice Broke, The (1987)                 4.000000  3.705882\n",
       "Year of Living Dangerously (1982)               3.951220  3.869403\n",
       "Year of the Horse (1997)                             NaN  3.250000\n",
       "Yellow Submarine (1968)                         3.714286  3.689286\n",
       "Yojimbo (1961)                                  4.423077  4.402116\n",
       "You Can't Take It With You (1938)               4.192308  3.921569\n",
       "You So Crazy (1994)                             3.666667  2.300000\n",
       "You've Got Mail (1998)                          3.542424  3.275591\n",
       "Young Doctors in Love (1982)                    1.923077  2.742424\n",
       "Young Frankenstein (1974)                       4.289963  4.239177\n",
       "Young Guns (1988)                               3.371795  3.425620\n",
       "Young Guns II (1990)                            2.934783  2.904025\n",
       "Young Poisoner's Handbook, The (1995)           4.000000  3.532258\n",
       "Young Sherlock Holmes (1985)                    3.514706  3.363344\n",
       "Young and Innocent (1937)                       2.500000  3.500000\n",
       "Your Friends and Neighbors (1998)               2.888889  3.536585\n",
       "Zachariah (1971)                                     NaN  3.500000\n",
       "Zed & Two Noughts, A (1985)                     3.500000  3.380952\n",
       "Zero Effect (1998)                              3.864407  3.723140\n",
       "Zero Kelvin (Kj�rlighetens kj�tere) (1995)           NaN  3.500000\n",
       "Zeus and Roxanne (1997)                         2.777778  2.357143\n",
       "eXistenZ (1999)                                 3.098592  3.289086\n",
       "\n",
       "[3706 rows x 2 columns]"
      ]
     },
     "execution_count": 87,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "mean_ratings"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 88,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# 过滤掉评分数据不足250条的电影\n",
    "# 先对title进行分组，然后利用size()得到一个含有各电影分组大小的Series对象\n",
    "ratings_by_title = data.groupby('title').size()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 89,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "title\n",
       "$1,000,000 Duck (1971)                37\n",
       "'Night Mother (1986)                  70\n",
       "'Til There Was You (1997)             52\n",
       "'burbs, The (1989)                   303\n",
       "...And Justice for All (1979)        199\n",
       "1-900 (1994)                           2\n",
       "10 Things I Hate About You (1999)    700\n",
       "101 Dalmatians (1961)                565\n",
       "101 Dalmatians (1996)                364\n",
       "12 Angry Men (1957)                  616\n",
       "dtype: int64"
      ]
     },
     "execution_count": 89,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ratings_by_title[:10]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 90,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "active_titles = ratings_by_title.index[ratings_by_title >= 250]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 91,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index([u''burbs, The (1989)', u'10 Things I Hate About You (1999)',\n",
       "       u'101 Dalmatians (1961)', u'101 Dalmatians (1996)',\n",
       "       u'12 Angry Men (1957)', u'13th Warrior, The (1999)',\n",
       "       u'2 Days in the Valley (1996)', u'20,000 Leagues Under the Sea (1954)',\n",
       "       u'2001: A Space Odyssey (1968)', u'2010 (1984)',\n",
       "       ...\n",
       "       u'X-Men (2000)', u'Year of Living Dangerously (1982)',\n",
       "       u'Yellow Submarine (1968)', u'You've Got Mail (1998)',\n",
       "       u'Young Frankenstein (1974)', u'Young Guns (1988)',\n",
       "       u'Young Guns II (1990)', u'Young Sherlock Holmes (1985)',\n",
       "       u'Zero Effect (1998)', u'eXistenZ (1999)'],\n",
       "      dtype='object', name=u'title', length=1216)"
      ]
     },
     "execution_count": 91,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "active_titles"
   ]
  },
  {
   "cell_type": "raw",
   "metadata": {},
   "source": [
    "# 从前面mean_ratings中选取所需行"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 93,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "mean_ratings = mean_ratings.ix[active_titles]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 94,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th>gender</th>\n",
       "      <th>F</th>\n",
       "      <th>M</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>title</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>'burbs, The (1989)</th>\n",
       "      <td>2.793478</td>\n",
       "      <td>2.962085</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10 Things I Hate About You (1999)</th>\n",
       "      <td>3.646552</td>\n",
       "      <td>3.311966</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>101 Dalmatians (1961)</th>\n",
       "      <td>3.791444</td>\n",
       "      <td>3.500000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>101 Dalmatians (1996)</th>\n",
       "      <td>3.240000</td>\n",
       "      <td>2.911215</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12 Angry Men (1957)</th>\n",
       "      <td>4.184397</td>\n",
       "      <td>4.328421</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13th Warrior, The (1999)</th>\n",
       "      <td>3.112000</td>\n",
       "      <td>3.168000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2 Days in the Valley (1996)</th>\n",
       "      <td>3.488889</td>\n",
       "      <td>3.244813</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20,000 Leagues Under the Sea (1954)</th>\n",
       "      <td>3.670103</td>\n",
       "      <td>3.709205</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2001: A Space Odyssey (1968)</th>\n",
       "      <td>3.825581</td>\n",
       "      <td>4.129738</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2010 (1984)</th>\n",
       "      <td>3.446809</td>\n",
       "      <td>3.413712</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28 Days (2000)</th>\n",
       "      <td>3.209424</td>\n",
       "      <td>2.977707</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>39 Steps, The (1935)</th>\n",
       "      <td>3.965517</td>\n",
       "      <td>4.107692</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>54 (1998)</th>\n",
       "      <td>2.701754</td>\n",
       "      <td>2.782178</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7th Voyage of Sinbad, The (1958)</th>\n",
       "      <td>3.409091</td>\n",
       "      <td>3.658879</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8MM (1999)</th>\n",
       "      <td>2.906250</td>\n",
       "      <td>2.850962</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>About Last Night... (1986)</th>\n",
       "      <td>3.188679</td>\n",
       "      <td>3.140909</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Absent Minded Professor, The (1961)</th>\n",
       "      <td>3.469388</td>\n",
       "      <td>3.446809</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Absolute Power (1997)</th>\n",
       "      <td>3.469136</td>\n",
       "      <td>3.327759</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Abyss, The (1989)</th>\n",
       "      <td>3.659236</td>\n",
       "      <td>3.689507</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Ace Ventura: Pet Detective (1994)</th>\n",
       "      <td>3.000000</td>\n",
       "      <td>3.197917</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Ace Ventura: When Nature Calls (1995)</th>\n",
       "      <td>2.269663</td>\n",
       "      <td>2.543333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Addams Family Values (1993)</th>\n",
       "      <td>3.000000</td>\n",
       "      <td>2.878531</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Addams Family, The (1991)</th>\n",
       "      <td>3.186170</td>\n",
       "      <td>3.163498</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Adventures in Babysitting (1987)</th>\n",
       "      <td>3.455782</td>\n",
       "      <td>3.208122</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Adventures of Buckaroo Bonzai Across the 8th Dimension, The (1984)</th>\n",
       "      <td>3.308511</td>\n",
       "      <td>3.402321</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Adventures of Priscilla, Queen of the Desert, The (1994)</th>\n",
       "      <td>3.989071</td>\n",
       "      <td>3.688811</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Adventures of Robin Hood, The (1938)</th>\n",
       "      <td>4.166667</td>\n",
       "      <td>3.918367</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>African Queen, The (1951)</th>\n",
       "      <td>4.324232</td>\n",
       "      <td>4.223822</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Age of Innocence, The (1993)</th>\n",
       "      <td>3.827068</td>\n",
       "      <td>3.339506</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Agnes of God (1985)</th>\n",
       "      <td>3.534884</td>\n",
       "      <td>3.244898</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>White Men Can't Jump (1992)</th>\n",
       "      <td>3.028777</td>\n",
       "      <td>3.231061</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Who Framed Roger Rabbit? (1988)</th>\n",
       "      <td>3.569378</td>\n",
       "      <td>3.713251</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Who's Afraid of Virginia Woolf? (1966)</th>\n",
       "      <td>4.029703</td>\n",
       "      <td>4.096939</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Whole Nine Yards, The (2000)</th>\n",
       "      <td>3.296552</td>\n",
       "      <td>3.404814</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Wild Bunch, The (1969)</th>\n",
       "      <td>3.636364</td>\n",
       "      <td>4.128099</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Wild Things (1998)</th>\n",
       "      <td>3.392000</td>\n",
       "      <td>3.459082</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Wild Wild West (1999)</th>\n",
       "      <td>2.275449</td>\n",
       "      <td>2.131973</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>William Shakespeare's Romeo and Juliet (1996)</th>\n",
       "      <td>3.532609</td>\n",
       "      <td>3.318644</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Willow (1988)</th>\n",
       "      <td>3.658683</td>\n",
       "      <td>3.453543</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Willy Wonka and the Chocolate Factory (1971)</th>\n",
       "      <td>4.063953</td>\n",
       "      <td>3.789474</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Witness (1985)</th>\n",
       "      <td>4.115854</td>\n",
       "      <td>3.941504</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Wizard of Oz, The (1939)</th>\n",
       "      <td>4.355030</td>\n",
       "      <td>4.203138</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Wolf (1994)</th>\n",
       "      <td>3.074074</td>\n",
       "      <td>2.899083</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Women on the Verge of a Nervous Breakdown (1988)</th>\n",
       "      <td>3.934307</td>\n",
       "      <td>3.865741</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Wonder Boys (2000)</th>\n",
       "      <td>4.043796</td>\n",
       "      <td>3.913649</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Working Girl (1988)</th>\n",
       "      <td>3.606742</td>\n",
       "      <td>3.312500</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>World Is Not Enough, The (1999)</th>\n",
       "      <td>3.337500</td>\n",
       "      <td>3.388889</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Wrong Trousers, The (1993)</th>\n",
       "      <td>4.588235</td>\n",
       "      <td>4.478261</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Wyatt Earp (1994)</th>\n",
       "      <td>3.147059</td>\n",
       "      <td>3.283898</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>X-Files: Fight the Future, The (1998)</th>\n",
       "      <td>3.489474</td>\n",
       "      <td>3.493797</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>X-Men (2000)</th>\n",
       "      <td>3.682310</td>\n",
       "      <td>3.851702</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Year of Living Dangerously (1982)</th>\n",
       "      <td>3.951220</td>\n",
       "      <td>3.869403</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Yellow Submarine (1968)</th>\n",
       "      <td>3.714286</td>\n",
       "      <td>3.689286</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>You've Got Mail (1998)</th>\n",
       "      <td>3.542424</td>\n",
       "      <td>3.275591</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Young Frankenstein (1974)</th>\n",
       "      <td>4.289963</td>\n",
       "      <td>4.239177</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Young Guns (1988)</th>\n",
       "      <td>3.371795</td>\n",
       "      <td>3.425620</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Young Guns II (1990)</th>\n",
       "      <td>2.934783</td>\n",
       "      <td>2.904025</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Young Sherlock Holmes (1985)</th>\n",
       "      <td>3.514706</td>\n",
       "      <td>3.363344</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Zero Effect (1998)</th>\n",
       "      <td>3.864407</td>\n",
       "      <td>3.723140</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>eXistenZ (1999)</th>\n",
       "      <td>3.098592</td>\n",
       "      <td>3.289086</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>1216 rows × 2 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "gender                                                     F         M\n",
       "title                                                                 \n",
       "'burbs, The (1989)                                  2.793478  2.962085\n",
       "10 Things I Hate About You (1999)                   3.646552  3.311966\n",
       "101 Dalmatians (1961)                               3.791444  3.500000\n",
       "101 Dalmatians (1996)                               3.240000  2.911215\n",
       "12 Angry Men (1957)                                 4.184397  4.328421\n",
       "13th Warrior, The (1999)                            3.112000  3.168000\n",
       "2 Days in the Valley (1996)                         3.488889  3.244813\n",
       "20,000 Leagues Under the Sea (1954)                 3.670103  3.709205\n",
       "2001: A Space Odyssey (1968)                        3.825581  4.129738\n",
       "2010 (1984)                                         3.446809  3.413712\n",
       "28 Days (2000)                                      3.209424  2.977707\n",
       "39 Steps, The (1935)                                3.965517  4.107692\n",
       "54 (1998)                                           2.701754  2.782178\n",
       "7th Voyage of Sinbad, The (1958)                    3.409091  3.658879\n",
       "8MM (1999)                                          2.906250  2.850962\n",
       "About Last Night... (1986)                          3.188679  3.140909\n",
       "Absent Minded Professor, The (1961)                 3.469388  3.446809\n",
       "Absolute Power (1997)                               3.469136  3.327759\n",
       "Abyss, The (1989)                                   3.659236  3.689507\n",
       "Ace Ventura: Pet Detective (1994)                   3.000000  3.197917\n",
       "Ace Ventura: When Nature Calls (1995)               2.269663  2.543333\n",
       "Addams Family Values (1993)                         3.000000  2.878531\n",
       "Addams Family, The (1991)                           3.186170  3.163498\n",
       "Adventures in Babysitting (1987)                    3.455782  3.208122\n",
       "Adventures of Buckaroo Bonzai Across the 8th Di...  3.308511  3.402321\n",
       "Adventures of Priscilla, Queen of the Desert, T...  3.989071  3.688811\n",
       "Adventures of Robin Hood, The (1938)                4.166667  3.918367\n",
       "African Queen, The (1951)                           4.324232  4.223822\n",
       "Age of Innocence, The (1993)                        3.827068  3.339506\n",
       "Agnes of God (1985)                                 3.534884  3.244898\n",
       "...                                                      ...       ...\n",
       "White Men Can't Jump (1992)                         3.028777  3.231061\n",
       "Who Framed Roger Rabbit? (1988)                     3.569378  3.713251\n",
       "Who's Afraid of Virginia Woolf? (1966)              4.029703  4.096939\n",
       "Whole Nine Yards, The (2000)                        3.296552  3.404814\n",
       "Wild Bunch, The (1969)                              3.636364  4.128099\n",
       "Wild Things (1998)                                  3.392000  3.459082\n",
       "Wild Wild West (1999)                               2.275449  2.131973\n",
       "William Shakespeare's Romeo and Juliet (1996)       3.532609  3.318644\n",
       "Willow (1988)                                       3.658683  3.453543\n",
       "Willy Wonka and the Chocolate Factory (1971)        4.063953  3.789474\n",
       "Witness (1985)                                      4.115854  3.941504\n",
       "Wizard of Oz, The (1939)                            4.355030  4.203138\n",
       "Wolf (1994)                                         3.074074  2.899083\n",
       "Women on the Verge of a Nervous Breakdown (1988)    3.934307  3.865741\n",
       "Wonder Boys (2000)                                  4.043796  3.913649\n",
       "Working Girl (1988)                                 3.606742  3.312500\n",
       "World Is Not Enough, The (1999)                     3.337500  3.388889\n",
       "Wrong Trousers, The (1993)                          4.588235  4.478261\n",
       "Wyatt Earp (1994)                                   3.147059  3.283898\n",
       "X-Files: Fight the Future, The (1998)               3.489474  3.493797\n",
       "X-Men (2000)                                        3.682310  3.851702\n",
       "Year of Living Dangerously (1982)                   3.951220  3.869403\n",
       "Yellow Submarine (1968)                             3.714286  3.689286\n",
       "You've Got Mail (1998)                              3.542424  3.275591\n",
       "Young Frankenstein (1974)                           4.289963  4.239177\n",
       "Young Guns (1988)                                   3.371795  3.425620\n",
       "Young Guns II (1990)                                2.934783  2.904025\n",
       "Young Sherlock Holmes (1985)                        3.514706  3.363344\n",
       "Zero Effect (1998)                                  3.864407  3.723140\n",
       "eXistenZ (1999)                                     3.098592  3.289086\n",
       "\n",
       "[1216 rows x 2 columns]"
      ]
     },
     "execution_count": 94,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "mean_ratings"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 95,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "E:\\Anaconda\\lib\\site-packages\\ipykernel\\__main__.py:2: FutureWarning: by argument to sort_index is deprecated, pls use .sort_values(by=...)\n",
      "  from ipykernel import kernelapp as app\n"
     ]
    }
   ],
   "source": [
    "# 了解女性观众最喜欢的电影，对F进行降序排列\n",
    "top_female_ratings = mean_ratings.sort_index(by='F', ascending=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 96,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th>gender</th>\n",
       "      <th>F</th>\n",
       "      <th>M</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>title</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Close Shave, A (1995)</th>\n",
       "      <td>4.644444</td>\n",
       "      <td>4.473795</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Wrong Trousers, The (1993)</th>\n",
       "      <td>4.588235</td>\n",
       "      <td>4.478261</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Sunset Blvd. (a.k.a. Sunset Boulevard) (1950)</th>\n",
       "      <td>4.572650</td>\n",
       "      <td>4.464589</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Wallace &amp; Gromit: The Best of Aardman Animation (1996)</th>\n",
       "      <td>4.563107</td>\n",
       "      <td>4.385075</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Schindler's List (1993)</th>\n",
       "      <td>4.562602</td>\n",
       "      <td>4.491415</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Shawshank Redemption, The (1994)</th>\n",
       "      <td>4.539075</td>\n",
       "      <td>4.560625</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Grand Day Out, A (1992)</th>\n",
       "      <td>4.537879</td>\n",
       "      <td>4.293255</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>To Kill a Mockingbird (1962)</th>\n",
       "      <td>4.536667</td>\n",
       "      <td>4.372611</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Creature Comforts (1990)</th>\n",
       "      <td>4.513889</td>\n",
       "      <td>4.272277</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Usual Suspects, The (1995)</th>\n",
       "      <td>4.513317</td>\n",
       "      <td>4.518248</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "gender                                                     F         M\n",
       "title                                                                 \n",
       "Close Shave, A (1995)                               4.644444  4.473795\n",
       "Wrong Trousers, The (1993)                          4.588235  4.478261\n",
       "Sunset Blvd. (a.k.a. Sunset Boulevard) (1950)       4.572650  4.464589\n",
       "Wallace & Gromit: The Best of Aardman Animation...  4.563107  4.385075\n",
       "Schindler's List (1993)                             4.562602  4.491415\n",
       "Shawshank Redemption, The (1994)                    4.539075  4.560625\n",
       "Grand Day Out, A (1992)                             4.537879  4.293255\n",
       "To Kill a Mockingbird (1962)                        4.536667  4.372611\n",
       "Creature Comforts (1990)                            4.513889  4.272277\n",
       "Usual Suspects, The (1995)                          4.513317  4.518248"
      ]
     },
     "execution_count": 96,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "top_female_ratings[0:10]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 97,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "top_female_ratings = mean_ratings.sort_values(by='F', ascending=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 99,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th>gender</th>\n",
       "      <th>F</th>\n",
       "      <th>M</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>title</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Close Shave, A (1995)</th>\n",
       "      <td>4.644444</td>\n",
       "      <td>4.473795</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Wrong Trousers, The (1993)</th>\n",
       "      <td>4.588235</td>\n",
       "      <td>4.478261</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Sunset Blvd. (a.k.a. Sunset Boulevard) (1950)</th>\n",
       "      <td>4.572650</td>\n",
       "      <td>4.464589</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Wallace &amp; Gromit: The Best of Aardman Animation (1996)</th>\n",
       "      <td>4.563107</td>\n",
       "      <td>4.385075</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Schindler's List (1993)</th>\n",
       "      <td>4.562602</td>\n",
       "      <td>4.491415</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Shawshank Redemption, The (1994)</th>\n",
       "      <td>4.539075</td>\n",
       "      <td>4.560625</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Grand Day Out, A (1992)</th>\n",
       "      <td>4.537879</td>\n",
       "      <td>4.293255</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>To Kill a Mockingbird (1962)</th>\n",
       "      <td>4.536667</td>\n",
       "      <td>4.372611</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Creature Comforts (1990)</th>\n",
       "      <td>4.513889</td>\n",
       "      <td>4.272277</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Usual Suspects, The (1995)</th>\n",
       "      <td>4.513317</td>\n",
       "      <td>4.518248</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>It Happened One Night (1934)</th>\n",
       "      <td>4.500000</td>\n",
       "      <td>4.163934</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Rear Window (1954)</th>\n",
       "      <td>4.484536</td>\n",
       "      <td>4.472991</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Seven Samurai (The Magnificent Seven) (Shichinin no samurai) (1954)</th>\n",
       "      <td>4.481132</td>\n",
       "      <td>4.576628</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Sixth Sense, The (1999)</th>\n",
       "      <td>4.477410</td>\n",
       "      <td>4.379944</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Third Man, The (1949)</th>\n",
       "      <td>4.466019</td>\n",
       "      <td>4.448276</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Some Like It Hot (1959)</th>\n",
       "      <td>4.462745</td>\n",
       "      <td>4.228769</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>City Lights (1931)</th>\n",
       "      <td>4.452055</td>\n",
       "      <td>4.363636</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Notorious (1946)</th>\n",
       "      <td>4.448718</td>\n",
       "      <td>4.211073</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Philadelphia Story, The (1940)</th>\n",
       "      <td>4.446809</td>\n",
       "      <td>4.201729</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Life Is Beautiful (La Vita � bella) (1997)</th>\n",
       "      <td>4.422343</td>\n",
       "      <td>4.286624</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Strangers on a Train (1951)</th>\n",
       "      <td>4.414815</td>\n",
       "      <td>4.262248</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Bicycle Thief, The (Ladri di biciclette) (1948)</th>\n",
       "      <td>4.407407</td>\n",
       "      <td>4.343434</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Mr. Smith Goes to Washington (1939)</th>\n",
       "      <td>4.400000</td>\n",
       "      <td>4.183746</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Thin Blue Line, The (1988)</th>\n",
       "      <td>4.396552</td>\n",
       "      <td>4.213270</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Killing Fields, The (1984)</th>\n",
       "      <td>4.378049</td>\n",
       "      <td>4.211268</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Dr. Strangelove or: How I Learned to Stop Worrying and Love the Bomb (1963)</th>\n",
       "      <td>4.376623</td>\n",
       "      <td>4.464789</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Ran (1985)</th>\n",
       "      <td>4.365079</td>\n",
       "      <td>4.248299</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>North by Northwest (1959)</th>\n",
       "      <td>4.364458</td>\n",
       "      <td>4.390641</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>All About Eve (1950)</th>\n",
       "      <td>4.363057</td>\n",
       "      <td>4.186992</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Manchurian Candidate, The (1962)</th>\n",
       "      <td>4.358824</td>\n",
       "      <td>4.326050</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Rocky III (1982)</th>\n",
       "      <td>2.361702</td>\n",
       "      <td>2.943503</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Congo (1995)</th>\n",
       "      <td>2.347368</td>\n",
       "      <td>2.217021</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>House on Haunted Hill, The (1999)</th>\n",
       "      <td>2.333333</td>\n",
       "      <td>2.299213</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Spawn (1997)</th>\n",
       "      <td>2.333333</td>\n",
       "      <td>2.660287</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Blue Lagoon, The (1980)</th>\n",
       "      <td>2.321739</td>\n",
       "      <td>2.337662</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Nightmare on Elm Street Part 2: Freddy's Revenge, A (1985)</th>\n",
       "      <td>2.319149</td>\n",
       "      <td>2.321586</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Inspector Gadget (1999)</th>\n",
       "      <td>2.316327</td>\n",
       "      <td>2.112727</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Porky's (1981)</th>\n",
       "      <td>2.296875</td>\n",
       "      <td>2.836364</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Honey, I Blew Up the Kid (1992)</th>\n",
       "      <td>2.295918</td>\n",
       "      <td>2.243816</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Wild Wild West (1999)</th>\n",
       "      <td>2.275449</td>\n",
       "      <td>2.131973</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Ace Ventura: When Nature Calls (1995)</th>\n",
       "      <td>2.269663</td>\n",
       "      <td>2.543333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Fly II, The (1989)</th>\n",
       "      <td>2.257143</td>\n",
       "      <td>2.321285</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Cable Guy, The (1996)</th>\n",
       "      <td>2.250000</td>\n",
       "      <td>2.863787</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Island of Dr. Moreau, The (1996)</th>\n",
       "      <td>2.245283</td>\n",
       "      <td>2.191882</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Grease 2 (1982)</th>\n",
       "      <td>2.243478</td>\n",
       "      <td>1.792553</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Superman IV: The Quest for Peace (1987)</th>\n",
       "      <td>2.216216</td>\n",
       "      <td>1.847458</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>I Still Know What You Did Last Summer (1998)</th>\n",
       "      <td>2.200000</td>\n",
       "      <td>2.204444</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Eye of the Beholder (1999)</th>\n",
       "      <td>2.181818</td>\n",
       "      <td>2.115789</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Godzilla (1998)</th>\n",
       "      <td>2.175439</td>\n",
       "      <td>2.343891</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Super Mario Bros. (1993)</th>\n",
       "      <td>2.163636</td>\n",
       "      <td>1.820339</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Karate Kid III, The (1989)</th>\n",
       "      <td>2.155556</td>\n",
       "      <td>2.116183</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Teenage Mutant Ninja Turtles II: The Secret of the Ooze (1991)</th>\n",
       "      <td>2.152174</td>\n",
       "      <td>2.121951</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Striptease (1996)</th>\n",
       "      <td>2.150000</td>\n",
       "      <td>2.193277</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Howard the Duck (1986)</th>\n",
       "      <td>2.074627</td>\n",
       "      <td>2.103542</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Anaconda (1997)</th>\n",
       "      <td>2.000000</td>\n",
       "      <td>2.248447</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Avengers, The (1998)</th>\n",
       "      <td>1.915254</td>\n",
       "      <td>2.017467</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Speed 2: Cruise Control (1997)</th>\n",
       "      <td>1.906667</td>\n",
       "      <td>1.863014</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Rocky V (1990)</th>\n",
       "      <td>1.878788</td>\n",
       "      <td>2.132780</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Barb Wire (1996)</th>\n",
       "      <td>1.585366</td>\n",
       "      <td>2.100386</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Battlefield Earth (2000)</th>\n",
       "      <td>1.574468</td>\n",
       "      <td>1.616949</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>1216 rows × 2 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "gender                                                     F         M\n",
       "title                                                                 \n",
       "Close Shave, A (1995)                               4.644444  4.473795\n",
       "Wrong Trousers, The (1993)                          4.588235  4.478261\n",
       "Sunset Blvd. (a.k.a. Sunset Boulevard) (1950)       4.572650  4.464589\n",
       "Wallace & Gromit: The Best of Aardman Animation...  4.563107  4.385075\n",
       "Schindler's List (1993)                             4.562602  4.491415\n",
       "Shawshank Redemption, The (1994)                    4.539075  4.560625\n",
       "Grand Day Out, A (1992)                             4.537879  4.293255\n",
       "To Kill a Mockingbird (1962)                        4.536667  4.372611\n",
       "Creature Comforts (1990)                            4.513889  4.272277\n",
       "Usual Suspects, The (1995)                          4.513317  4.518248\n",
       "It Happened One Night (1934)                        4.500000  4.163934\n",
       "Rear Window (1954)                                  4.484536  4.472991\n",
       "Seven Samurai (The Magnificent Seven) (Shichini...  4.481132  4.576628\n",
       "Sixth Sense, The (1999)                             4.477410  4.379944\n",
       "Third Man, The (1949)                               4.466019  4.448276\n",
       "Some Like It Hot (1959)                             4.462745  4.228769\n",
       "City Lights (1931)                                  4.452055  4.363636\n",
       "Notorious (1946)                                    4.448718  4.211073\n",
       "Philadelphia Story, The (1940)                      4.446809  4.201729\n",
       "Life Is Beautiful (La Vita � bella) (1997)          4.422343  4.286624\n",
       "Strangers on a Train (1951)                         4.414815  4.262248\n",
       "Bicycle Thief, The (Ladri di biciclette) (1948)     4.407407  4.343434\n",
       "Mr. Smith Goes to Washington (1939)                 4.400000  4.183746\n",
       "Thin Blue Line, The (1988)                          4.396552  4.213270\n",
       "Killing Fields, The (1984)                          4.378049  4.211268\n",
       "Dr. Strangelove or: How I Learned to Stop Worry...  4.376623  4.464789\n",
       "Ran (1985)                                          4.365079  4.248299\n",
       "North by Northwest (1959)                           4.364458  4.390641\n",
       "All About Eve (1950)                                4.363057  4.186992\n",
       "Manchurian Candidate, The (1962)                    4.358824  4.326050\n",
       "...                                                      ...       ...\n",
       "Rocky III (1982)                                    2.361702  2.943503\n",
       "Congo (1995)                                        2.347368  2.217021\n",
       "House on Haunted Hill, The (1999)                   2.333333  2.299213\n",
       "Spawn (1997)                                        2.333333  2.660287\n",
       "Blue Lagoon, The (1980)                             2.321739  2.337662\n",
       "Nightmare on Elm Street Part 2: Freddy's Reveng...  2.319149  2.321586\n",
       "Inspector Gadget (1999)                             2.316327  2.112727\n",
       "Porky's (1981)                                      2.296875  2.836364\n",
       "Honey, I Blew Up the Kid (1992)                     2.295918  2.243816\n",
       "Wild Wild West (1999)                               2.275449  2.131973\n",
       "Ace Ventura: When Nature Calls (1995)               2.269663  2.543333\n",
       "Fly II, The (1989)                                  2.257143  2.321285\n",
       "Cable Guy, The (1996)                               2.250000  2.863787\n",
       "Island of Dr. Moreau, The (1996)                    2.245283  2.191882\n",
       "Grease 2 (1982)                                     2.243478  1.792553\n",
       "Superman IV: The Quest for Peace (1987)             2.216216  1.847458\n",
       "I Still Know What You Did Last Summer (1998)        2.200000  2.204444\n",
       "Eye of the Beholder (1999)                          2.181818  2.115789\n",
       "Godzilla (1998)                                     2.175439  2.343891\n",
       "Super Mario Bros. (1993)                            2.163636  1.820339\n",
       "Karate Kid III, The (1989)                          2.155556  2.116183\n",
       "Teenage Mutant Ninja Turtles II: The Secret of ...  2.152174  2.121951\n",
       "Striptease (1996)                                   2.150000  2.193277\n",
       "Howard the Duck (1986)                              2.074627  2.103542\n",
       "Anaconda (1997)                                     2.000000  2.248447\n",
       "Avengers, The (1998)                                1.915254  2.017467\n",
       "Speed 2: Cruise Control (1997)                      1.906667  1.863014\n",
       "Rocky V (1990)                                      1.878788  2.132780\n",
       "Barb Wire (1996)                                    1.585366  2.100386\n",
       "Battlefield Earth (2000)                            1.574468  1.616949\n",
       "\n",
       "[1216 rows x 2 columns]"
      ]
     },
     "execution_count": 99,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "top_female_ratings"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 计算评分分歧"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 找出男性和女性观众分歧最大的电影，一个办法是给mean-ratings加上一个用于存放平均得分之差的列，并排序"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 100,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "mean_ratings['diff'] = mean_ratings['M'] - mean_ratings['F']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 104,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "# 按diff排序\n",
    "sorted_by_diff = mean_ratings.sort_values(by='diff')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 105,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th>gender</th>\n",
       "      <th>F</th>\n",
       "      <th>M</th>\n",
       "      <th>diff</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>title</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Dirty Dancing (1987)</th>\n",
       "      <td>3.790378</td>\n",
       "      <td>2.959596</td>\n",
       "      <td>-0.830782</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Jumpin' Jack Flash (1986)</th>\n",
       "      <td>3.254717</td>\n",
       "      <td>2.578358</td>\n",
       "      <td>-0.676359</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Grease (1978)</th>\n",
       "      <td>3.975265</td>\n",
       "      <td>3.367041</td>\n",
       "      <td>-0.608224</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Little Women (1994)</th>\n",
       "      <td>3.870588</td>\n",
       "      <td>3.321739</td>\n",
       "      <td>-0.548849</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Steel Magnolias (1989)</th>\n",
       "      <td>3.901734</td>\n",
       "      <td>3.365957</td>\n",
       "      <td>-0.535777</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Anastasia (1997)</th>\n",
       "      <td>3.800000</td>\n",
       "      <td>3.281609</td>\n",
       "      <td>-0.518391</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Rocky Horror Picture Show, The (1975)</th>\n",
       "      <td>3.673016</td>\n",
       "      <td>3.160131</td>\n",
       "      <td>-0.512885</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Color Purple, The (1985)</th>\n",
       "      <td>4.158192</td>\n",
       "      <td>3.659341</td>\n",
       "      <td>-0.498851</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Age of Innocence, The (1993)</th>\n",
       "      <td>3.827068</td>\n",
       "      <td>3.339506</td>\n",
       "      <td>-0.487561</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Free Willy (1993)</th>\n",
       "      <td>2.921348</td>\n",
       "      <td>2.438776</td>\n",
       "      <td>-0.482573</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>French Kiss (1995)</th>\n",
       "      <td>3.535714</td>\n",
       "      <td>3.056962</td>\n",
       "      <td>-0.478752</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Little Shop of Horrors, The (1960)</th>\n",
       "      <td>3.650000</td>\n",
       "      <td>3.179688</td>\n",
       "      <td>-0.470312</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Guys and Dolls (1955)</th>\n",
       "      <td>4.051724</td>\n",
       "      <td>3.583333</td>\n",
       "      <td>-0.468391</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Mary Poppins (1964)</th>\n",
       "      <td>4.197740</td>\n",
       "      <td>3.730594</td>\n",
       "      <td>-0.467147</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Patch Adams (1998)</th>\n",
       "      <td>3.473282</td>\n",
       "      <td>3.008746</td>\n",
       "      <td>-0.464536</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Grease 2 (1982)</th>\n",
       "      <td>2.243478</td>\n",
       "      <td>1.792553</td>\n",
       "      <td>-0.450925</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Sound of Music, The (1965)</th>\n",
       "      <td>4.233677</td>\n",
       "      <td>3.783418</td>\n",
       "      <td>-0.450259</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Never Been Kissed (1999)</th>\n",
       "      <td>3.452174</td>\n",
       "      <td>3.002538</td>\n",
       "      <td>-0.449636</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Casper (1995)</th>\n",
       "      <td>3.291139</td>\n",
       "      <td>2.844444</td>\n",
       "      <td>-0.446695</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Jewel of the Nile, The (1985)</th>\n",
       "      <td>3.494253</td>\n",
       "      <td>3.048096</td>\n",
       "      <td>-0.446157</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>South Pacific (1958)</th>\n",
       "      <td>3.887850</td>\n",
       "      <td>3.445087</td>\n",
       "      <td>-0.442764</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Gone with the Wind (1939)</th>\n",
       "      <td>4.269841</td>\n",
       "      <td>3.829371</td>\n",
       "      <td>-0.440471</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Sommersby (1993)</th>\n",
       "      <td>3.482270</td>\n",
       "      <td>3.046667</td>\n",
       "      <td>-0.435603</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Skulls, The (2000)</th>\n",
       "      <td>3.053333</td>\n",
       "      <td>2.621145</td>\n",
       "      <td>-0.432188</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Corrina, Corrina (1994)</th>\n",
       "      <td>3.523490</td>\n",
       "      <td>3.092593</td>\n",
       "      <td>-0.430897</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Iron Eagle (1986)</th>\n",
       "      <td>2.968750</td>\n",
       "      <td>2.543933</td>\n",
       "      <td>-0.424817</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Hope Floats (1998)</th>\n",
       "      <td>3.206186</td>\n",
       "      <td>2.782383</td>\n",
       "      <td>-0.423802</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Beverly Hills Cop III (1994)</th>\n",
       "      <td>2.865385</td>\n",
       "      <td>2.443333</td>\n",
       "      <td>-0.422051</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Sense and Sensibility (1995)</th>\n",
       "      <td>4.233333</td>\n",
       "      <td>3.819277</td>\n",
       "      <td>-0.414056</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Parent Trap, The (1961)</th>\n",
       "      <td>3.805556</td>\n",
       "      <td>3.393333</td>\n",
       "      <td>-0.412222</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Tommy Boy (1995)</th>\n",
       "      <td>3.170732</td>\n",
       "      <td>3.585366</td>\n",
       "      <td>0.414634</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Eyes Wide Shut (1999)</th>\n",
       "      <td>2.891213</td>\n",
       "      <td>3.305949</td>\n",
       "      <td>0.414736</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>South Park: Bigger, Longer and Uncut (1999)</th>\n",
       "      <td>3.422481</td>\n",
       "      <td>3.846686</td>\n",
       "      <td>0.424206</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Godzilla (Gojira) (1954)</th>\n",
       "      <td>2.948718</td>\n",
       "      <td>3.374046</td>\n",
       "      <td>0.425328</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Raging Bull (1980)</th>\n",
       "      <td>3.831933</td>\n",
       "      <td>4.263441</td>\n",
       "      <td>0.431508</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Reservoir Dogs (1992)</th>\n",
       "      <td>3.769231</td>\n",
       "      <td>4.213873</td>\n",
       "      <td>0.444642</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Where Eagles Dare (1969)</th>\n",
       "      <td>3.384615</td>\n",
       "      <td>3.833333</td>\n",
       "      <td>0.448718</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Kingpin (1996)</th>\n",
       "      <td>3.092308</td>\n",
       "      <td>3.557480</td>\n",
       "      <td>0.465173</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Me, Myself and Irene (2000)</th>\n",
       "      <td>2.629310</td>\n",
       "      <td>3.096847</td>\n",
       "      <td>0.467537</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Akira (1988)</th>\n",
       "      <td>3.511111</td>\n",
       "      <td>3.980344</td>\n",
       "      <td>0.469233</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Wild Bunch, The (1969)</th>\n",
       "      <td>3.636364</td>\n",
       "      <td>4.128099</td>\n",
       "      <td>0.491736</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>From Dusk Till Dawn (1996)</th>\n",
       "      <td>2.735714</td>\n",
       "      <td>3.232558</td>\n",
       "      <td>0.496844</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Big Trouble in Little China (1986)</th>\n",
       "      <td>2.987952</td>\n",
       "      <td>3.485030</td>\n",
       "      <td>0.497078</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Beavis and Butt-head Do America (1996)</th>\n",
       "      <td>2.637363</td>\n",
       "      <td>3.135417</td>\n",
       "      <td>0.498054</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Rocky II (1979)</th>\n",
       "      <td>2.741379</td>\n",
       "      <td>3.242894</td>\n",
       "      <td>0.501515</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Barb Wire (1996)</th>\n",
       "      <td>1.585366</td>\n",
       "      <td>2.100386</td>\n",
       "      <td>0.515020</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Fright Night (1985)</th>\n",
       "      <td>2.973684</td>\n",
       "      <td>3.500000</td>\n",
       "      <td>0.526316</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Exorcist, The (1973)</th>\n",
       "      <td>3.537634</td>\n",
       "      <td>4.067239</td>\n",
       "      <td>0.529605</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Animal House (1978)</th>\n",
       "      <td>3.628906</td>\n",
       "      <td>4.167192</td>\n",
       "      <td>0.538286</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Porky's (1981)</th>\n",
       "      <td>2.296875</td>\n",
       "      <td>2.836364</td>\n",
       "      <td>0.539489</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>For a Few Dollars More (1965)</th>\n",
       "      <td>3.409091</td>\n",
       "      <td>3.953795</td>\n",
       "      <td>0.544704</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Caddyshack (1980)</th>\n",
       "      <td>3.396135</td>\n",
       "      <td>3.969737</td>\n",
       "      <td>0.573602</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Rocky III (1982)</th>\n",
       "      <td>2.361702</td>\n",
       "      <td>2.943503</td>\n",
       "      <td>0.581801</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Hidden, The (1987)</th>\n",
       "      <td>3.137931</td>\n",
       "      <td>3.745098</td>\n",
       "      <td>0.607167</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Evil Dead II (Dead By Dawn) (1987)</th>\n",
       "      <td>3.297297</td>\n",
       "      <td>3.909283</td>\n",
       "      <td>0.611985</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Cable Guy, The (1996)</th>\n",
       "      <td>2.250000</td>\n",
       "      <td>2.863787</td>\n",
       "      <td>0.613787</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Longest Day, The (1962)</th>\n",
       "      <td>3.411765</td>\n",
       "      <td>4.031447</td>\n",
       "      <td>0.619682</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Dumb &amp; Dumber (1994)</th>\n",
       "      <td>2.697987</td>\n",
       "      <td>3.336595</td>\n",
       "      <td>0.638608</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Kentucky Fried Movie, The (1977)</th>\n",
       "      <td>2.878788</td>\n",
       "      <td>3.555147</td>\n",
       "      <td>0.676359</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Good, The Bad and The Ugly, The (1966)</th>\n",
       "      <td>3.494949</td>\n",
       "      <td>4.221300</td>\n",
       "      <td>0.726351</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>1216 rows × 3 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "gender                                              F         M      diff\n",
       "title                                                                    \n",
       "Dirty Dancing (1987)                         3.790378  2.959596 -0.830782\n",
       "Jumpin' Jack Flash (1986)                    3.254717  2.578358 -0.676359\n",
       "Grease (1978)                                3.975265  3.367041 -0.608224\n",
       "Little Women (1994)                          3.870588  3.321739 -0.548849\n",
       "Steel Magnolias (1989)                       3.901734  3.365957 -0.535777\n",
       "Anastasia (1997)                             3.800000  3.281609 -0.518391\n",
       "Rocky Horror Picture Show, The (1975)        3.673016  3.160131 -0.512885\n",
       "Color Purple, The (1985)                     4.158192  3.659341 -0.498851\n",
       "Age of Innocence, The (1993)                 3.827068  3.339506 -0.487561\n",
       "Free Willy (1993)                            2.921348  2.438776 -0.482573\n",
       "French Kiss (1995)                           3.535714  3.056962 -0.478752\n",
       "Little Shop of Horrors, The (1960)           3.650000  3.179688 -0.470312\n",
       "Guys and Dolls (1955)                        4.051724  3.583333 -0.468391\n",
       "Mary Poppins (1964)                          4.197740  3.730594 -0.467147\n",
       "Patch Adams (1998)                           3.473282  3.008746 -0.464536\n",
       "Grease 2 (1982)                              2.243478  1.792553 -0.450925\n",
       "Sound of Music, The (1965)                   4.233677  3.783418 -0.450259\n",
       "Never Been Kissed (1999)                     3.452174  3.002538 -0.449636\n",
       "Casper (1995)                                3.291139  2.844444 -0.446695\n",
       "Jewel of the Nile, The (1985)                3.494253  3.048096 -0.446157\n",
       "South Pacific (1958)                         3.887850  3.445087 -0.442764\n",
       "Gone with the Wind (1939)                    4.269841  3.829371 -0.440471\n",
       "Sommersby (1993)                             3.482270  3.046667 -0.435603\n",
       "Skulls, The (2000)                           3.053333  2.621145 -0.432188\n",
       "Corrina, Corrina (1994)                      3.523490  3.092593 -0.430897\n",
       "Iron Eagle (1986)                            2.968750  2.543933 -0.424817\n",
       "Hope Floats (1998)                           3.206186  2.782383 -0.423802\n",
       "Beverly Hills Cop III (1994)                 2.865385  2.443333 -0.422051\n",
       "Sense and Sensibility (1995)                 4.233333  3.819277 -0.414056\n",
       "Parent Trap, The (1961)                      3.805556  3.393333 -0.412222\n",
       "...                                               ...       ...       ...\n",
       "Tommy Boy (1995)                             3.170732  3.585366  0.414634\n",
       "Eyes Wide Shut (1999)                        2.891213  3.305949  0.414736\n",
       "South Park: Bigger, Longer and Uncut (1999)  3.422481  3.846686  0.424206\n",
       "Godzilla (Gojira) (1954)                     2.948718  3.374046  0.425328\n",
       "Raging Bull (1980)                           3.831933  4.263441  0.431508\n",
       "Reservoir Dogs (1992)                        3.769231  4.213873  0.444642\n",
       "Where Eagles Dare (1969)                     3.384615  3.833333  0.448718\n",
       "Kingpin (1996)                               3.092308  3.557480  0.465173\n",
       "Me, Myself and Irene (2000)                  2.629310  3.096847  0.467537\n",
       "Akira (1988)                                 3.511111  3.980344  0.469233\n",
       "Wild Bunch, The (1969)                       3.636364  4.128099  0.491736\n",
       "From Dusk Till Dawn (1996)                   2.735714  3.232558  0.496844\n",
       "Big Trouble in Little China (1986)           2.987952  3.485030  0.497078\n",
       "Beavis and Butt-head Do America (1996)       2.637363  3.135417  0.498054\n",
       "Rocky II (1979)                              2.741379  3.242894  0.501515\n",
       "Barb Wire (1996)                             1.585366  2.100386  0.515020\n",
       "Fright Night (1985)                          2.973684  3.500000  0.526316\n",
       "Exorcist, The (1973)                         3.537634  4.067239  0.529605\n",
       "Animal House (1978)                          3.628906  4.167192  0.538286\n",
       "Porky's (1981)                               2.296875  2.836364  0.539489\n",
       "For a Few Dollars More (1965)                3.409091  3.953795  0.544704\n",
       "Caddyshack (1980)                            3.396135  3.969737  0.573602\n",
       "Rocky III (1982)                             2.361702  2.943503  0.581801\n",
       "Hidden, The (1987)                           3.137931  3.745098  0.607167\n",
       "Evil Dead II (Dead By Dawn) (1987)           3.297297  3.909283  0.611985\n",
       "Cable Guy, The (1996)                        2.250000  2.863787  0.613787\n",
       "Longest Day, The (1962)                      3.411765  4.031447  0.619682\n",
       "Dumb & Dumber (1994)                         2.697987  3.336595  0.638608\n",
       "Kentucky Fried Movie, The (1977)             2.878788  3.555147  0.676359\n",
       "Good, The Bad and The Ugly, The (1966)       3.494949  4.221300  0.726351\n",
       "\n",
       "[1216 rows x 3 columns]"
      ]
     },
     "execution_count": 105,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sorted_by_diff"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 106,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# 对结果反序并取出前15行，得到的是男性观众更喜欢的电影"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 108,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th>gender</th>\n",
       "      <th>F</th>\n",
       "      <th>M</th>\n",
       "      <th>diff</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>title</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Good, The Bad and The Ugly, The (1966)</th>\n",
       "      <td>3.494949</td>\n",
       "      <td>4.221300</td>\n",
       "      <td>0.726351</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Kentucky Fried Movie, The (1977)</th>\n",
       "      <td>2.878788</td>\n",
       "      <td>3.555147</td>\n",
       "      <td>0.676359</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Dumb &amp; Dumber (1994)</th>\n",
       "      <td>2.697987</td>\n",
       "      <td>3.336595</td>\n",
       "      <td>0.638608</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Longest Day, The (1962)</th>\n",
       "      <td>3.411765</td>\n",
       "      <td>4.031447</td>\n",
       "      <td>0.619682</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Cable Guy, The (1996)</th>\n",
       "      <td>2.250000</td>\n",
       "      <td>2.863787</td>\n",
       "      <td>0.613787</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Evil Dead II (Dead By Dawn) (1987)</th>\n",
       "      <td>3.297297</td>\n",
       "      <td>3.909283</td>\n",
       "      <td>0.611985</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Hidden, The (1987)</th>\n",
       "      <td>3.137931</td>\n",
       "      <td>3.745098</td>\n",
       "      <td>0.607167</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Rocky III (1982)</th>\n",
       "      <td>2.361702</td>\n",
       "      <td>2.943503</td>\n",
       "      <td>0.581801</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Caddyshack (1980)</th>\n",
       "      <td>3.396135</td>\n",
       "      <td>3.969737</td>\n",
       "      <td>0.573602</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>For a Few Dollars More (1965)</th>\n",
       "      <td>3.409091</td>\n",
       "      <td>3.953795</td>\n",
       "      <td>0.544704</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Porky's (1981)</th>\n",
       "      <td>2.296875</td>\n",
       "      <td>2.836364</td>\n",
       "      <td>0.539489</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Animal House (1978)</th>\n",
       "      <td>3.628906</td>\n",
       "      <td>4.167192</td>\n",
       "      <td>0.538286</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Exorcist, The (1973)</th>\n",
       "      <td>3.537634</td>\n",
       "      <td>4.067239</td>\n",
       "      <td>0.529605</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Fright Night (1985)</th>\n",
       "      <td>2.973684</td>\n",
       "      <td>3.500000</td>\n",
       "      <td>0.526316</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Barb Wire (1996)</th>\n",
       "      <td>1.585366</td>\n",
       "      <td>2.100386</td>\n",
       "      <td>0.515020</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "gender                                         F         M      diff\n",
       "title                                                               \n",
       "Good, The Bad and The Ugly, The (1966)  3.494949  4.221300  0.726351\n",
       "Kentucky Fried Movie, The (1977)        2.878788  3.555147  0.676359\n",
       "Dumb & Dumber (1994)                    2.697987  3.336595  0.638608\n",
       "Longest Day, The (1962)                 3.411765  4.031447  0.619682\n",
       "Cable Guy, The (1996)                   2.250000  2.863787  0.613787\n",
       "Evil Dead II (Dead By Dawn) (1987)      3.297297  3.909283  0.611985\n",
       "Hidden, The (1987)                      3.137931  3.745098  0.607167\n",
       "Rocky III (1982)                        2.361702  2.943503  0.581801\n",
       "Caddyshack (1980)                       3.396135  3.969737  0.573602\n",
       "For a Few Dollars More (1965)           3.409091  3.953795  0.544704\n",
       "Porky's (1981)                          2.296875  2.836364  0.539489\n",
       "Animal House (1978)                     3.628906  4.167192  0.538286\n",
       "Exorcist, The (1973)                    3.537634  4.067239  0.529605\n",
       "Fright Night (1985)                     2.973684  3.500000  0.526316\n",
       "Barb Wire (1996)                        1.585366  2.100386  0.515020"
      ]
     },
     "execution_count": 108,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sorted_by_diff[::-1][:15]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 只是想要找出分歧最大的电影，不考虑性别因素，则可以计算得分数据的方差或标准差"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 109,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# 根据电影名称分组的得分数据的标准差\n",
    "rating_std_by_title = data.groupby('title')['rating'].std()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 110,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# 根据active_titles进行过滤\n",
    "rating_std_by_title = rating_std_by_title.ix[active_titles]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 112,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "title\n",
       "Dumb & Dumber (1994)                     1.321333\n",
       "Blair Witch Project, The (1999)          1.316368\n",
       "Natural Born Killers (1994)              1.307198\n",
       "Tank Girl (1995)                         1.277695\n",
       "Rocky Horror Picture Show, The (1975)    1.260177\n",
       "Eyes Wide Shut (1999)                    1.259624\n",
       "Evita (1996)                             1.253631\n",
       "Billy Madison (1995)                     1.249970\n",
       "Fear and Loathing in Las Vegas (1998)    1.246408\n",
       "Bicentennial Man (1999)                  1.245533\n",
       "Name: rating, dtype: float64"
      ]
     },
     "execution_count": 112,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 根据值对Series进行降序排列\n",
    "rating_std_by_title.sort_values(ascending=False)[:10]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 1880-2010年间全美婴儿姓名"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 114,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "# 由于是一个非常标准的以逗号隔开的格式，所以可以用pandas.read_csv讲其加载到DataFrame中\n",
    "import pandas as pd"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 115,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "names1880 = pd.read_csv('ch02/names/yob1880.txt', names=['name', 'sex', 'births'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 116,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>name</th>\n",
       "      <th>sex</th>\n",
       "      <th>births</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Mary</td>\n",
       "      <td>F</td>\n",
       "      <td>7065</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Anna</td>\n",
       "      <td>F</td>\n",
       "      <td>2604</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Emma</td>\n",
       "      <td>F</td>\n",
       "      <td>2003</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Elizabeth</td>\n",
       "      <td>F</td>\n",
       "      <td>1939</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Minnie</td>\n",
       "      <td>F</td>\n",
       "      <td>1746</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>Margaret</td>\n",
       "      <td>F</td>\n",
       "      <td>1578</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>Ida</td>\n",
       "      <td>F</td>\n",
       "      <td>1472</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>Alice</td>\n",
       "      <td>F</td>\n",
       "      <td>1414</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>Bertha</td>\n",
       "      <td>F</td>\n",
       "      <td>1320</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>Sarah</td>\n",
       "      <td>F</td>\n",
       "      <td>1288</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>Annie</td>\n",
       "      <td>F</td>\n",
       "      <td>1258</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>Clara</td>\n",
       "      <td>F</td>\n",
       "      <td>1226</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>Ella</td>\n",
       "      <td>F</td>\n",
       "      <td>1156</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>Florence</td>\n",
       "      <td>F</td>\n",
       "      <td>1063</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>Cora</td>\n",
       "      <td>F</td>\n",
       "      <td>1045</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>Martha</td>\n",
       "      <td>F</td>\n",
       "      <td>1040</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>Laura</td>\n",
       "      <td>F</td>\n",
       "      <td>1012</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>Nellie</td>\n",
       "      <td>F</td>\n",
       "      <td>995</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>Grace</td>\n",
       "      <td>F</td>\n",
       "      <td>982</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>Carrie</td>\n",
       "      <td>F</td>\n",
       "      <td>949</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>Maude</td>\n",
       "      <td>F</td>\n",
       "      <td>858</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>Mabel</td>\n",
       "      <td>F</td>\n",
       "      <td>808</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>Bessie</td>\n",
       "      <td>F</td>\n",
       "      <td>794</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>Jennie</td>\n",
       "      <td>F</td>\n",
       "      <td>793</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>Gertrude</td>\n",
       "      <td>F</td>\n",
       "      <td>787</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>Julia</td>\n",
       "      <td>F</td>\n",
       "      <td>783</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>Hattie</td>\n",
       "      <td>F</td>\n",
       "      <td>769</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>Edith</td>\n",
       "      <td>F</td>\n",
       "      <td>768</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>Mattie</td>\n",
       "      <td>F</td>\n",
       "      <td>704</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>Rose</td>\n",
       "      <td>F</td>\n",
       "      <td>700</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1970</th>\n",
       "      <td>Philo</td>\n",
       "      <td>M</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1971</th>\n",
       "      <td>Phineas</td>\n",
       "      <td>M</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1972</th>\n",
       "      <td>Presley</td>\n",
       "      <td>M</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1973</th>\n",
       "      <td>Ransom</td>\n",
       "      <td>M</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1974</th>\n",
       "      <td>Reece</td>\n",
       "      <td>M</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1975</th>\n",
       "      <td>Rene</td>\n",
       "      <td>M</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1976</th>\n",
       "      <td>Roswell</td>\n",
       "      <td>M</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1977</th>\n",
       "      <td>Rowland</td>\n",
       "      <td>M</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1978</th>\n",
       "      <td>Sampson</td>\n",
       "      <td>M</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1979</th>\n",
       "      <td>Samual</td>\n",
       "      <td>M</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1980</th>\n",
       "      <td>Santos</td>\n",
       "      <td>M</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1981</th>\n",
       "      <td>Schuyler</td>\n",
       "      <td>M</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1982</th>\n",
       "      <td>Sheppard</td>\n",
       "      <td>M</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1983</th>\n",
       "      <td>Spurgeon</td>\n",
       "      <td>M</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1984</th>\n",
       "      <td>Starling</td>\n",
       "      <td>M</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1985</th>\n",
       "      <td>Sylvanus</td>\n",
       "      <td>M</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1986</th>\n",
       "      <td>Theadore</td>\n",
       "      <td>M</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1987</th>\n",
       "      <td>Theophile</td>\n",
       "      <td>M</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1988</th>\n",
       "      <td>Tilmon</td>\n",
       "      <td>M</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1989</th>\n",
       "      <td>Tommy</td>\n",
       "      <td>M</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1990</th>\n",
       "      <td>Unknown</td>\n",
       "      <td>M</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1991</th>\n",
       "      <td>Vann</td>\n",
       "      <td>M</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1992</th>\n",
       "      <td>Wes</td>\n",
       "      <td>M</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1993</th>\n",
       "      <td>Winston</td>\n",
       "      <td>M</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1994</th>\n",
       "      <td>Wood</td>\n",
       "      <td>M</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1995</th>\n",
       "      <td>Woodie</td>\n",
       "      <td>M</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1996</th>\n",
       "      <td>Worthy</td>\n",
       "      <td>M</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1997</th>\n",
       "      <td>Wright</td>\n",
       "      <td>M</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1998</th>\n",
       "      <td>York</td>\n",
       "      <td>M</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1999</th>\n",
       "      <td>Zachariah</td>\n",
       "      <td>M</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>2000 rows × 3 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "           name sex  births\n",
       "0          Mary   F    7065\n",
       "1          Anna   F    2604\n",
       "2          Emma   F    2003\n",
       "3     Elizabeth   F    1939\n",
       "4        Minnie   F    1746\n",
       "5      Margaret   F    1578\n",
       "6           Ida   F    1472\n",
       "7         Alice   F    1414\n",
       "8        Bertha   F    1320\n",
       "9         Sarah   F    1288\n",
       "10        Annie   F    1258\n",
       "11        Clara   F    1226\n",
       "12         Ella   F    1156\n",
       "13     Florence   F    1063\n",
       "14         Cora   F    1045\n",
       "15       Martha   F    1040\n",
       "16        Laura   F    1012\n",
       "17       Nellie   F     995\n",
       "18        Grace   F     982\n",
       "19       Carrie   F     949\n",
       "20        Maude   F     858\n",
       "21        Mabel   F     808\n",
       "22       Bessie   F     794\n",
       "23       Jennie   F     793\n",
       "24     Gertrude   F     787\n",
       "25        Julia   F     783\n",
       "26       Hattie   F     769\n",
       "27        Edith   F     768\n",
       "28       Mattie   F     704\n",
       "29         Rose   F     700\n",
       "...         ...  ..     ...\n",
       "1970      Philo   M       5\n",
       "1971    Phineas   M       5\n",
       "1972    Presley   M       5\n",
       "1973     Ransom   M       5\n",
       "1974      Reece   M       5\n",
       "1975       Rene   M       5\n",
       "1976    Roswell   M       5\n",
       "1977    Rowland   M       5\n",
       "1978    Sampson   M       5\n",
       "1979     Samual   M       5\n",
       "1980     Santos   M       5\n",
       "1981   Schuyler   M       5\n",
       "1982   Sheppard   M       5\n",
       "1983   Spurgeon   M       5\n",
       "1984   Starling   M       5\n",
       "1985   Sylvanus   M       5\n",
       "1986   Theadore   M       5\n",
       "1987  Theophile   M       5\n",
       "1988     Tilmon   M       5\n",
       "1989      Tommy   M       5\n",
       "1990    Unknown   M       5\n",
       "1991       Vann   M       5\n",
       "1992        Wes   M       5\n",
       "1993    Winston   M       5\n",
       "1994       Wood   M       5\n",
       "1995     Woodie   M       5\n",
       "1996     Worthy   M       5\n",
       "1997     Wright   M       5\n",
       "1998       York   M       5\n",
       "1999  Zachariah   M       5\n",
       "\n",
       "[2000 rows x 3 columns]"
      ]
     },
     "execution_count": 116,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "names1880"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 121,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "sex\n",
       "F     90993\n",
       "M    110493\n",
       "Name: births, dtype: int64"
      ]
     },
     "execution_count": 121,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 文件中仅含有当前出现超过5次的名字。可以用births列的sex分组小计表示该年度的births总计：\n",
    "names1880.groupby('sex').births.sum()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 由于该数据集按年度被分割成了多个文件，所以先要将所有数据都组装到一个DataFrame里面，并加上一个year字段，使用pandas.concat即可做到"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 122,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# 2010是目前最后一个有效统计年度\n",
    "years = range(1880, 2011)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 125,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "pieces = []\n",
    "columns = ['name', 'sex', 'births']\n",
    "\n",
    "for year in years:\n",
    "    path = 'ch02/names/yob%d.txt' % year\n",
    "    frame = pd.read_csv(path, names=columns)\n",
    "    \n",
    "    frame['year'] = year\n",
    "    pieces.append(frame)\n",
    "    \n",
    "# 将所有数据整合到单个DataFrame中\n",
    "# 必须指定ignore_index=True, 忽略数据里的原始行号\n",
    "# concat默认按行将多个DataFrame组合到一起\n",
    "names = pd.concat(pieces, ignore_index=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 126,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>name</th>\n",
       "      <th>sex</th>\n",
       "      <th>births</th>\n",
       "      <th>year</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Mary</td>\n",
       "      <td>F</td>\n",
       "      <td>7065</td>\n",
       "      <td>1880</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Anna</td>\n",
       "      <td>F</td>\n",
       "      <td>2604</td>\n",
       "      <td>1880</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Emma</td>\n",
       "      <td>F</td>\n",
       "      <td>2003</td>\n",
       "      <td>1880</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Elizabeth</td>\n",
       "      <td>F</td>\n",
       "      <td>1939</td>\n",
       "      <td>1880</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Minnie</td>\n",
       "      <td>F</td>\n",
       "      <td>1746</td>\n",
       "      <td>1880</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>Margaret</td>\n",
       "      <td>F</td>\n",
       "      <td>1578</td>\n",
       "      <td>1880</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>Ida</td>\n",
       "      <td>F</td>\n",
       "      <td>1472</td>\n",
       "      <td>1880</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>Alice</td>\n",
       "      <td>F</td>\n",
       "      <td>1414</td>\n",
       "      <td>1880</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>Bertha</td>\n",
       "      <td>F</td>\n",
       "      <td>1320</td>\n",
       "      <td>1880</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>Sarah</td>\n",
       "      <td>F</td>\n",
       "      <td>1288</td>\n",
       "      <td>1880</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>Annie</td>\n",
       "      <td>F</td>\n",
       "      <td>1258</td>\n",
       "      <td>1880</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>Clara</td>\n",
       "      <td>F</td>\n",
       "      <td>1226</td>\n",
       "      <td>1880</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>Ella</td>\n",
       "      <td>F</td>\n",
       "      <td>1156</td>\n",
       "      <td>1880</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>Florence</td>\n",
       "      <td>F</td>\n",
       "      <td>1063</td>\n",
       "      <td>1880</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>Cora</td>\n",
       "      <td>F</td>\n",
       "      <td>1045</td>\n",
       "      <td>1880</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>Martha</td>\n",
       "      <td>F</td>\n",
       "      <td>1040</td>\n",
       "      <td>1880</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>Laura</td>\n",
       "      <td>F</td>\n",
       "      <td>1012</td>\n",
       "      <td>1880</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>Nellie</td>\n",
       "      <td>F</td>\n",
       "      <td>995</td>\n",
       "      <td>1880</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>Grace</td>\n",
       "      <td>F</td>\n",
       "      <td>982</td>\n",
       "      <td>1880</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>Carrie</td>\n",
       "      <td>F</td>\n",
       "      <td>949</td>\n",
       "      <td>1880</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>Maude</td>\n",
       "      <td>F</td>\n",
       "      <td>858</td>\n",
       "      <td>1880</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>Mabel</td>\n",
       "      <td>F</td>\n",
       "      <td>808</td>\n",
       "      <td>1880</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>Bessie</td>\n",
       "      <td>F</td>\n",
       "      <td>794</td>\n",
       "      <td>1880</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>Jennie</td>\n",
       "      <td>F</td>\n",
       "      <td>793</td>\n",
       "      <td>1880</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>Gertrude</td>\n",
       "      <td>F</td>\n",
       "      <td>787</td>\n",
       "      <td>1880</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>Julia</td>\n",
       "      <td>F</td>\n",
       "      <td>783</td>\n",
       "      <td>1880</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>Hattie</td>\n",
       "      <td>F</td>\n",
       "      <td>769</td>\n",
       "      <td>1880</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>Edith</td>\n",
       "      <td>F</td>\n",
       "      <td>768</td>\n",
       "      <td>1880</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>Mattie</td>\n",
       "      <td>F</td>\n",
       "      <td>704</td>\n",
       "      <td>1880</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>Rose</td>\n",
       "      <td>F</td>\n",
       "      <td>700</td>\n",
       "      <td>1880</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1690754</th>\n",
       "      <td>Zaviyon</td>\n",
       "      <td>M</td>\n",
       "      <td>5</td>\n",
       "      <td>2010</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1690755</th>\n",
       "      <td>Zaybrien</td>\n",
       "      <td>M</td>\n",
       "      <td>5</td>\n",
       "      <td>2010</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1690756</th>\n",
       "      <td>Zayshawn</td>\n",
       "      <td>M</td>\n",
       "      <td>5</td>\n",
       "      <td>2010</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1690757</th>\n",
       "      <td>Zayyan</td>\n",
       "      <td>M</td>\n",
       "      <td>5</td>\n",
       "      <td>2010</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1690758</th>\n",
       "      <td>Zeal</td>\n",
       "      <td>M</td>\n",
       "      <td>5</td>\n",
       "      <td>2010</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1690759</th>\n",
       "      <td>Zealan</td>\n",
       "      <td>M</td>\n",
       "      <td>5</td>\n",
       "      <td>2010</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1690760</th>\n",
       "      <td>Zecharia</td>\n",
       "      <td>M</td>\n",
       "      <td>5</td>\n",
       "      <td>2010</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1690761</th>\n",
       "      <td>Zeferino</td>\n",
       "      <td>M</td>\n",
       "      <td>5</td>\n",
       "      <td>2010</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1690762</th>\n",
       "      <td>Zekariah</td>\n",
       "      <td>M</td>\n",
       "      <td>5</td>\n",
       "      <td>2010</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1690763</th>\n",
       "      <td>Zeki</td>\n",
       "      <td>M</td>\n",
       "      <td>5</td>\n",
       "      <td>2010</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1690764</th>\n",
       "      <td>Zeriah</td>\n",
       "      <td>M</td>\n",
       "      <td>5</td>\n",
       "      <td>2010</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1690765</th>\n",
       "      <td>Zeshan</td>\n",
       "      <td>M</td>\n",
       "      <td>5</td>\n",
       "      <td>2010</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1690766</th>\n",
       "      <td>Zhyier</td>\n",
       "      <td>M</td>\n",
       "      <td>5</td>\n",
       "      <td>2010</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1690767</th>\n",
       "      <td>Zildjian</td>\n",
       "      <td>M</td>\n",
       "      <td>5</td>\n",
       "      <td>2010</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1690768</th>\n",
       "      <td>Zinn</td>\n",
       "      <td>M</td>\n",
       "      <td>5</td>\n",
       "      <td>2010</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1690769</th>\n",
       "      <td>Zishan</td>\n",
       "      <td>M</td>\n",
       "      <td>5</td>\n",
       "      <td>2010</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1690770</th>\n",
       "      <td>Ziven</td>\n",
       "      <td>M</td>\n",
       "      <td>5</td>\n",
       "      <td>2010</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1690771</th>\n",
       "      <td>Zmari</td>\n",
       "      <td>M</td>\n",
       "      <td>5</td>\n",
       "      <td>2010</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1690772</th>\n",
       "      <td>Zoren</td>\n",
       "      <td>M</td>\n",
       "      <td>5</td>\n",
       "      <td>2010</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1690773</th>\n",
       "      <td>Zuhaib</td>\n",
       "      <td>M</td>\n",
       "      <td>5</td>\n",
       "      <td>2010</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1690774</th>\n",
       "      <td>Zyeire</td>\n",
       "      <td>M</td>\n",
       "      <td>5</td>\n",
       "      <td>2010</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1690775</th>\n",
       "      <td>Zygmunt</td>\n",
       "      <td>M</td>\n",
       "      <td>5</td>\n",
       "      <td>2010</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1690776</th>\n",
       "      <td>Zykerion</td>\n",
       "      <td>M</td>\n",
       "      <td>5</td>\n",
       "      <td>2010</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1690777</th>\n",
       "      <td>Zylar</td>\n",
       "      <td>M</td>\n",
       "      <td>5</td>\n",
       "      <td>2010</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1690778</th>\n",
       "      <td>Zylin</td>\n",
       "      <td>M</td>\n",
       "      <td>5</td>\n",
       "      <td>2010</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1690779</th>\n",
       "      <td>Zymaire</td>\n",
       "      <td>M</td>\n",
       "      <td>5</td>\n",
       "      <td>2010</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1690780</th>\n",
       "      <td>Zyonne</td>\n",
       "      <td>M</td>\n",
       "      <td>5</td>\n",
       "      <td>2010</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1690781</th>\n",
       "      <td>Zyquarius</td>\n",
       "      <td>M</td>\n",
       "      <td>5</td>\n",
       "      <td>2010</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1690782</th>\n",
       "      <td>Zyran</td>\n",
       "      <td>M</td>\n",
       "      <td>5</td>\n",
       "      <td>2010</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1690783</th>\n",
       "      <td>Zzyzx</td>\n",
       "      <td>M</td>\n",
       "      <td>5</td>\n",
       "      <td>2010</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>1690784 rows × 4 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "              name sex  births  year\n",
       "0             Mary   F    7065  1880\n",
       "1             Anna   F    2604  1880\n",
       "2             Emma   F    2003  1880\n",
       "3        Elizabeth   F    1939  1880\n",
       "4           Minnie   F    1746  1880\n",
       "5         Margaret   F    1578  1880\n",
       "6              Ida   F    1472  1880\n",
       "7            Alice   F    1414  1880\n",
       "8           Bertha   F    1320  1880\n",
       "9            Sarah   F    1288  1880\n",
       "10           Annie   F    1258  1880\n",
       "11           Clara   F    1226  1880\n",
       "12            Ella   F    1156  1880\n",
       "13        Florence   F    1063  1880\n",
       "14            Cora   F    1045  1880\n",
       "15          Martha   F    1040  1880\n",
       "16           Laura   F    1012  1880\n",
       "17          Nellie   F     995  1880\n",
       "18           Grace   F     982  1880\n",
       "19          Carrie   F     949  1880\n",
       "20           Maude   F     858  1880\n",
       "21           Mabel   F     808  1880\n",
       "22          Bessie   F     794  1880\n",
       "23          Jennie   F     793  1880\n",
       "24        Gertrude   F     787  1880\n",
       "25           Julia   F     783  1880\n",
       "26          Hattie   F     769  1880\n",
       "27           Edith   F     768  1880\n",
       "28          Mattie   F     704  1880\n",
       "29            Rose   F     700  1880\n",
       "...            ...  ..     ...   ...\n",
       "1690754    Zaviyon   M       5  2010\n",
       "1690755   Zaybrien   M       5  2010\n",
       "1690756   Zayshawn   M       5  2010\n",
       "1690757     Zayyan   M       5  2010\n",
       "1690758       Zeal   M       5  2010\n",
       "1690759     Zealan   M       5  2010\n",
       "1690760   Zecharia   M       5  2010\n",
       "1690761   Zeferino   M       5  2010\n",
       "1690762   Zekariah   M       5  2010\n",
       "1690763       Zeki   M       5  2010\n",
       "1690764     Zeriah   M       5  2010\n",
       "1690765     Zeshan   M       5  2010\n",
       "1690766     Zhyier   M       5  2010\n",
       "1690767   Zildjian   M       5  2010\n",
       "1690768       Zinn   M       5  2010\n",
       "1690769     Zishan   M       5  2010\n",
       "1690770      Ziven   M       5  2010\n",
       "1690771      Zmari   M       5  2010\n",
       "1690772      Zoren   M       5  2010\n",
       "1690773     Zuhaib   M       5  2010\n",
       "1690774     Zyeire   M       5  2010\n",
       "1690775    Zygmunt   M       5  2010\n",
       "1690776   Zykerion   M       5  2010\n",
       "1690777      Zylar   M       5  2010\n",
       "1690778      Zylin   M       5  2010\n",
       "1690779    Zymaire   M       5  2010\n",
       "1690780     Zyonne   M       5  2010\n",
       "1690781  Zyquarius   M       5  2010\n",
       "1690782      Zyran   M       5  2010\n",
       "1690783      Zzyzx   M       5  2010\n",
       "\n",
       "[1690784 rows x 4 columns]"
      ]
     },
     "execution_count": 126,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "names"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 131,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th>sex</th>\n",
       "      <th>F</th>\n",
       "      <th>M</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>year</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1880</th>\n",
       "      <td>90993</td>\n",
       "      <td>110493</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1881</th>\n",
       "      <td>91955</td>\n",
       "      <td>100748</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1882</th>\n",
       "      <td>107851</td>\n",
       "      <td>113687</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1883</th>\n",
       "      <td>112322</td>\n",
       "      <td>104632</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1884</th>\n",
       "      <td>129021</td>\n",
       "      <td>114445</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1885</th>\n",
       "      <td>133056</td>\n",
       "      <td>107802</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1886</th>\n",
       "      <td>144538</td>\n",
       "      <td>110785</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1887</th>\n",
       "      <td>145983</td>\n",
       "      <td>101412</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1888</th>\n",
       "      <td>178631</td>\n",
       "      <td>120857</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1889</th>\n",
       "      <td>178369</td>\n",
       "      <td>110590</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1890</th>\n",
       "      <td>190377</td>\n",
       "      <td>111026</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1891</th>\n",
       "      <td>185486</td>\n",
       "      <td>101198</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1892</th>\n",
       "      <td>212350</td>\n",
       "      <td>122038</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1893</th>\n",
       "      <td>212908</td>\n",
       "      <td>112319</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1894</th>\n",
       "      <td>222923</td>\n",
       "      <td>115775</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1895</th>\n",
       "      <td>233632</td>\n",
       "      <td>117398</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1896</th>\n",
       "      <td>237924</td>\n",
       "      <td>119575</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1897</th>\n",
       "      <td>234199</td>\n",
       "      <td>112760</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1898</th>\n",
       "      <td>258771</td>\n",
       "      <td>122703</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1899</th>\n",
       "      <td>233022</td>\n",
       "      <td>106218</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1900</th>\n",
       "      <td>299873</td>\n",
       "      <td>150554</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1901</th>\n",
       "      <td>239351</td>\n",
       "      <td>106478</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1902</th>\n",
       "      <td>264079</td>\n",
       "      <td>122660</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1903</th>\n",
       "      <td>261976</td>\n",
       "      <td>119240</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1904</th>\n",
       "      <td>275375</td>\n",
       "      <td>128129</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1905</th>\n",
       "      <td>291641</td>\n",
       "      <td>132319</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1906</th>\n",
       "      <td>295301</td>\n",
       "      <td>133159</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1907</th>\n",
       "      <td>318558</td>\n",
       "      <td>146838</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1908</th>\n",
       "      <td>334277</td>\n",
       "      <td>154339</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1909</th>\n",
       "      <td>347191</td>\n",
       "      <td>163983</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1981</th>\n",
       "      <td>1666833</td>\n",
       "      <td>1789568</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1982</th>\n",
       "      <td>1692036</td>\n",
       "      <td>1812642</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1983</th>\n",
       "      <td>1669486</td>\n",
       "      <td>1790670</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1984</th>\n",
       "      <td>1682396</td>\n",
       "      <td>1802735</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1985</th>\n",
       "      <td>1719450</td>\n",
       "      <td>1846162</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1986</th>\n",
       "      <td>1714053</td>\n",
       "      <td>1839442</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1987</th>\n",
       "      <td>1737508</td>\n",
       "      <td>1865113</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1988</th>\n",
       "      <td>1779112</td>\n",
       "      <td>1911858</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1989</th>\n",
       "      <td>1843057</td>\n",
       "      <td>1999840</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1990</th>\n",
       "      <td>1897256</td>\n",
       "      <td>2052070</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1991</th>\n",
       "      <td>1874110</td>\n",
       "      <td>2019018</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1992</th>\n",
       "      <td>1842818</td>\n",
       "      <td>1995760</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1993</th>\n",
       "      <td>1807795</td>\n",
       "      <td>1959712</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1994</th>\n",
       "      <td>1784407</td>\n",
       "      <td>1930363</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1995</th>\n",
       "      <td>1757240</td>\n",
       "      <td>1902100</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1996</th>\n",
       "      <td>1751681</td>\n",
       "      <td>1892700</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1997</th>\n",
       "      <td>1739331</td>\n",
       "      <td>1883571</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1998</th>\n",
       "      <td>1765390</td>\n",
       "      <td>1909676</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1999</th>\n",
       "      <td>1772139</td>\n",
       "      <td>1918267</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2000</th>\n",
       "      <td>1813960</td>\n",
       "      <td>1961702</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2001</th>\n",
       "      <td>1798284</td>\n",
       "      <td>1940498</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2002</th>\n",
       "      <td>1794358</td>\n",
       "      <td>1938941</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2003</th>\n",
       "      <td>1824406</td>\n",
       "      <td>1972439</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2004</th>\n",
       "      <td>1833005</td>\n",
       "      <td>1981557</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2005</th>\n",
       "      <td>1843890</td>\n",
       "      <td>1993285</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2006</th>\n",
       "      <td>1896468</td>\n",
       "      <td>2050234</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2007</th>\n",
       "      <td>1916888</td>\n",
       "      <td>2069242</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2008</th>\n",
       "      <td>1883645</td>\n",
       "      <td>2032310</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2009</th>\n",
       "      <td>1827643</td>\n",
       "      <td>1973359</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2010</th>\n",
       "      <td>1759010</td>\n",
       "      <td>1898382</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>131 rows × 2 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "sex         F        M\n",
       "year                  \n",
       "1880    90993   110493\n",
       "1881    91955   100748\n",
       "1882   107851   113687\n",
       "1883   112322   104632\n",
       "1884   129021   114445\n",
       "1885   133056   107802\n",
       "1886   144538   110785\n",
       "1887   145983   101412\n",
       "1888   178631   120857\n",
       "1889   178369   110590\n",
       "1890   190377   111026\n",
       "1891   185486   101198\n",
       "1892   212350   122038\n",
       "1893   212908   112319\n",
       "1894   222923   115775\n",
       "1895   233632   117398\n",
       "1896   237924   119575\n",
       "1897   234199   112760\n",
       "1898   258771   122703\n",
       "1899   233022   106218\n",
       "1900   299873   150554\n",
       "1901   239351   106478\n",
       "1902   264079   122660\n",
       "1903   261976   119240\n",
       "1904   275375   128129\n",
       "1905   291641   132319\n",
       "1906   295301   133159\n",
       "1907   318558   146838\n",
       "1908   334277   154339\n",
       "1909   347191   163983\n",
       "...       ...      ...\n",
       "1981  1666833  1789568\n",
       "1982  1692036  1812642\n",
       "1983  1669486  1790670\n",
       "1984  1682396  1802735\n",
       "1985  1719450  1846162\n",
       "1986  1714053  1839442\n",
       "1987  1737508  1865113\n",
       "1988  1779112  1911858\n",
       "1989  1843057  1999840\n",
       "1990  1897256  2052070\n",
       "1991  1874110  2019018\n",
       "1992  1842818  1995760\n",
       "1993  1807795  1959712\n",
       "1994  1784407  1930363\n",
       "1995  1757240  1902100\n",
       "1996  1751681  1892700\n",
       "1997  1739331  1883571\n",
       "1998  1765390  1909676\n",
       "1999  1772139  1918267\n",
       "2000  1813960  1961702\n",
       "2001  1798284  1940498\n",
       "2002  1794358  1938941\n",
       "2003  1824406  1972439\n",
       "2004  1833005  1981557\n",
       "2005  1843890  1993285\n",
       "2006  1896468  2050234\n",
       "2007  1916888  2069242\n",
       "2008  1883645  2032310\n",
       "2009  1827643  1973359\n",
       "2010  1759010  1898382\n",
       "\n",
       "[131 rows x 2 columns]"
      ]
     },
     "execution_count": 131,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 可以用groupby或pivot_table进行聚合\n",
    "total_births = names.pivot_table('births', index='year', columns='sex',aggfunc=sum)\n",
    "total_births"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 129,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th>sex</th>\n",
       "      <th>F</th>\n",
       "      <th>M</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>year</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2006</th>\n",
       "      <td>1896468</td>\n",
       "      <td>2050234</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2007</th>\n",
       "      <td>1916888</td>\n",
       "      <td>2069242</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2008</th>\n",
       "      <td>1883645</td>\n",
       "      <td>2032310</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2009</th>\n",
       "      <td>1827643</td>\n",
       "      <td>1973359</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2010</th>\n",
       "      <td>1759010</td>\n",
       "      <td>1898382</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "sex         F        M\n",
       "year                  \n",
       "2006  1896468  2050234\n",
       "2007  1916888  2069242\n",
       "2008  1883645  2032310\n",
       "2009  1827643  1973359\n",
       "2010  1759010  1898382"
      ]
     },
     "execution_count": 129,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "total_births.tail()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 130,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x17193c18>"
      ]
     },
     "execution_count": 130,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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JfWsdTAD8PF25ulcb5m1JrN6Mf4u0UMqqRkuiIY0bN46//OUv/Pzzz6SlVX+5\nA3EeyjxiNmw6sNy0UiIvNOm2ErN0+ep/Q/TFLD5m/oXH1fBad0PpE+nHsl3JZBU74df9GhP48tKg\nVbk+g+J8WPcBtLvILNcCZsb50mdg/48w6L76r1zSTrNXSNp+8zj6Yhg/07SOpiyFhY/BiX0w/BmI\nud5M6qvCF2uPAHDbOS53lTe0Y2vm/nEod3y6gQkfrGXaHQMY0rH6fSrPz4+loMTOqzf0okOwN7Pv\nG0xsYjYHU3M5fCKP3pF+XN6t9nvelJowIIq5WxJYtKOChSMrIS2UJmTKlCk8//zz9OpV/SamOA8V\nF6CzE5mX0prizqPNt3xbsdk9b/rVsPpf0O82uHU2P8YmExPuS1Rg3ZfkqA+lExx3JmSZBQxLCmHR\n42dnXP+RGQl22bOn04I6mstMDdWPsvJlMypu9KvwwFrTMikd+uvmBde/D/f8BH0mVCuYxGecZPrv\ncYzuGVbjOT+dQ3347sGhRAZ4MmX6BtYdOvcXyONZ+Xy98RgPz9rC4p1J/GlE51Oz3JVS9Izw49q+\nETw6sku9BBOAge0D6dC6FbM3HK32ORJQmpDIyEgeeaTqa7biPJd1DIXm52Qv1vlcYa7xf3sXvDcE\nUnbBDR/Dte+SWujCpqMZXNkjzNE1PqW3NQdjQ1w6hMaYyX+x35kRX6XyM00Lq9NIiB52ZgGdRkLc\nb/U/fDjtoBnEMOAeGPxHCOlep0mDWmue/W4nCnh2TPdalRHi48GX9wwmIsCTO6dvYP62RE7knj2j\nfsXuZC5942eenLOd3w+c4JaBUdx7SYda1726lFJMGBDFhriMap8jAaUJqGj5+uHDh/PDDz84oDbC\n4TLMZZSjOoQPEtqb5c13zYPuY+GhDdDbbG66fHcyWsOonvXzjbQ++Hu5MbB9IPO3JprtgYc9CpED\nYOHjkGXNvv79HSjINPurA3a75rst8eQVlkCbPmArPH1Zqr6s/9CMIhtwV70UN3dzAqv2pfLk6G61\n7lgHCPZx58t7BhHu78kjs7bQ/6XlDHv1J95avo/0vCIW7zjOfZ9toluYD0sfvYSNz43klRt6VzqP\npL7dcEEkXjXom5M+FCGamgzTKX1Mh5B6OIsTk6bT2tPprDkdS2OTaBvoRddQH0fUslI3XhDBU9/u\nYOuxTPq1DYDr3of3L4K3ekFIDzPQoOeNJngAy3Yn8+fZ23hydAEPdLPWH0vaaVoR9aEgC7Z8bhbQ\n9Kl7ay79y3FsAAAgAElEQVQ5u4B/LtxF/3YB/KEGfSeVCfHx4IeHL2LbsUy2x2fx28ETvLV8P+//\ncpBim6ZPpB/Tpwxs0G0IKhPs486Gv47E+5/Vyy8tFCGamswjFOJGm4i2aA3fpkScFUxyCor5/UAa\no2JC67xHfH27qlcb3F2cmLvZapG07gRTlpjVdL2DzWKHlz93Kv8nv5oAujQ22fShOLlCcj0O39/y\nuZntPviPdS7qQEoON079ncJiO6/e2Asnp/p57z1cnRnUIYh7LunA9DsHsuzPl3BtnwhG9wxj5l2D\nHBJMSrVyr367Q1oomOuhTe2fsiJaO2YdING47OlxHNOtGdY5BGdnZ77bksB9l55evlxrzfLdyRTZ\n7FwZ03T6T0r5erhyZUwYC7Yn8tzY7mayZXhfcytnZ0IW6w+n0zbQi23HMknKsxMW3M20UOqD3W5G\nk7UdYva8r6EVu5P5Yt1RuoX50MbfkzeW7MHNxZnZ9w2mU0jDtQw7h/rw2k29G6z8htLiA4qHhwdp\naWkEBQU16aCitSYtLQ0Pj8Zd9E80vpIThzlqD6FtoBdt/Dz427xYNsalsy0+i7mb44k7kUdekY3W\n3u6VLvXhaDdcEMGCbYms3JPK6J6VB71pv5ptiv87sS/Xv/c7P+5KYlJYLzO5sD4kbDRDsMuOJqum\nY+knefSrrTg5KVbtS6XErukU4s2ndwxoMqPqmpoWH1AiIyOJj48nNTXV0VWpkoeHB5GRFa8SKs4T\nWuOUFcdRPZQugV50a+PLCwt2cdP7awDo19af8QOiiAzwYnCHQJzr6ZJLfbu4U2uCfdyZuzm+0oBS\nuk3xbYPa0a9tAB2DW7E0NolJMT1h25eQm1q7vdrL2jnX7GbZtfLJwrmFJXiXu6xTbLPzyFdmT5cf\nHr6IYB93DqXm0b51qyYxgbSpavEBxdXVlfbt2zu6GkIY+Rm4FOdyTAczItCLwFZuPDC8I8cy8rlj\naDR9ovwdXcNqcXF24rq+4Xz6WxyHT5gP4vJmrjlCiV1z57BowKzK+8GqQ+QM7YYPmH4U78trXwm7\n3azH1WkkePhWmOW9nw/w+pK93HtJB54a3e1UgH5r+T62HM3kvxP7nmqN9AivuAxxmnTKC9GUWGt4\nJRBKuDVZ7rEru/LmhL7NJpiUuvviDni6OfPUnO1n7QOSnF3AtN8Oc1XPMNoFmWAzumcYNrtmZZY1\nDLqu6+odW2smT/a84axDWmteXbyH15fspVOINx+uOsR9n21i5d4UbvlwLe+uPMhNF0ZybV9Z9bsm\nJKAI0ZRkmjkoxT5RTfZyVnWF+nrwt7E9WB+Xzhfrjpxx7PUleymxaZ4afXoL3V4RfoT7ebBgfwH4\nhNe9Yz72O3DxMEu6WNLzipi3NYF7Zm7i/V8Octugtix99BJevDaGlXtTuPPTDRxMzeWvY7rz8vWN\nt4Xy+aLFX/ISokmxWihOQdEOrUZ9ufnCSBZsS+SVxXsY3jWEqEAvth7L5NvN8dx/acdTrRMwM7NH\ndA9lzqZ4dNeeqOQ6BBS7zUwG7XwluJvRWMt3JXPf55uw2TUBXq48dkUXHr68E0opJg2JpmuoD0fS\nTzKuT3i1FnoUZ5OAIkRTknGEDHwIaV3HzugmQinFKzf0YtSbqxjz39WM6xvOjoQsWnu7V7i7YZ8o\nfz5be4QM364EHvrJrAVWxYq/p2htgkjxScg7AbnJZpFHzGz8V5fsITrIi3+P70uvCL+zWoCDOgQx\nqIE3vjrfSUARogkpTjvMEXswbc+jYamRAV7Mvm8I0349zJxN8RSW2Hn9xt5njawCiLE6vg86RxNo\nLzHL2Vsz6qsUvwG+mXz6sbvvqctdi3Ye50BKLu/c0o++zawvqjmRgCJEE2JPP8wx3ea8CigAPSP8\n+M+Evjx/TQw7E7MYWsly7Z1CvHFzdmJzYSQDwPSjVDegbJsFLp5w70rTsvEMALdW2O2ad1YcoGNw\nK8b0OvcmWKJupFNeiKZCa1xzEknQweftxDk/L1eGdWpd6SRiV2cnuoR581u6r9n86sCy6hVcUmjm\nnHQfa9YAC+9rlngBftyVxN7kHB6+vHOzH+jQ1ElAEaKpOJmOky4mWfvTNuj8DCjV0aONL7HH89B9\nb4PdCyD7eNUn7VtqVjDuM/GMZK017/x0gPatWzG2ii16Rd1JQBGiqcg1O+OddAty6GKAjhYT7kda\nXhEnuk8yo7U2fVr1Sdtng3cotB9+RvKOhCxiE7O566L2uDTSku8tmbzDQjQVOSagOPm27G/SpTPS\nd+QHmGG/Gz+FkqLKT8hLMy2UXjeD85ndwnM3J+Dm4sQ1vZvGFsnnOwkoQjQVuSkAeAS07A+/7m1M\nQIlNyIaB90JeCuyeDznJsPwF+PnV05t12Upg4zSwF591uavYZmf+tkSu6B6Kn1fLbfE1JhnlJUQT\nYc9Jwgnwbt2yFwD1dnchOsiLXcez4bLLIbAD/Pic2TrYVgTaDr+8DlEDzZbIBVkQORDCep1Rzi97\nU0nPK+KGC2T5lMYiAUWIJqIwIxGb9iAooGkuSd+YYsL92JmYBU5OMOQhs4Vw7/Fw6VOgnGDTdDiw\nArpfYy6LdRxxVhlzt8QT1MqNS7qcH5NEmwMJKEI0EUWZiaRpf0J9Zc+bHuG+LNxxnOyCYnz7T4Fe\nN4GH3+kMV7xgbpXIOlnM8l0p3DqobaPtvy4koAjRZOicJFLxJ0QCCj2sfpQ9x3MY2D7wzGBSieyC\nYiZ9sp6TRSXY7Joim50bL2jZlw8bW5WhWyk1TSmVopTaWSbtH0qpBKXUVus2psyxZ5RSB5RSe5VS\no8qkX6iU2mEde1tZM5uUUu5KqdlW+jqlVHSZcyYrpfZbt8ll0ttbeQ9Y57rV/a0QwrGc81JI0f6E\n+lZz7arzWOkSLDsSsqp9zvdbEth6LJPIAC/C/T25dVBbekbIHiaNqTptwenA6ArS39Ra97VuiwCU\nUj2AiUCMdc57SqnSZTunAvcAna1baZl3ARla607Am8BrVlmBwPPAIGAg8LxSqvTi8mvW83cCMqwy\nhGjW3AtSSdEBhPhICyXYx53OId7M25qA1rrK/Fprvlx3lJ4Rvky7YwCf3TWI/7u+V5Pe1vt8VGVA\n0VqvAtKrWd61wFda60Kt9WHgADBQKdUG8NVar9Xmr2MmcF2Zc2ZY9+cAI6zWyyhgmdY6XWudASwD\nRlvHLrfyYp1bWpYQzVNhDm72fHJdg3BzkWv+Zkn5dmyPz2LLscwq82+Lz2JPUg63DGzbCLUTlanL\nX+7DSqnt1iWx0pZDBHCsTJ54Ky3Cul8+/YxztNYlQBYQdI6ygoBMK2/5ss6ilLpXKbVRKbWxOewb\nL1qonGQAijxDHFyRpuOGCyLxcXdhxu9xVeb9av1RPF2dGdenZc/hcbTaBpSpQAegL3Ac+He91aie\naa0/1Fr311r3Dw6W4YOiibKWXdHeoQ6uSNPRyt2Fm/pHsmjHcVJyCirNl1NQzPxtiYzrE45PC16y\npimoVUDRWidrrW1aazvwEaaPAyABiCqTNdJKS7Dul08/4xyllAvgB6Sdo6w0wN/KW74sIZona9kV\nlxa+7Ep5k4ZEU2wz/SN7k3J4a/k+Pl596FSAKSyxMeP3OE4W2bhlkFzucrRaDRtWSrXRWpcuAXo9\nUDoCbD7wpVLqP0A4pvN9vdbappTKVkoNBtYBk4B3ypwzGVgD3AT8pLXWSqmlwP+VuZx2JfCMdWyl\nlfcr69x5tXkdQjQVtuwknAGPgDBHV6VJad+6FcO7BvP2iv28tXw/SpmNGf9v0W56RfixPyWXk0U2\nLmwXQJ/IqocWi4ZVZUBRSs0ChgOtlVLxmJFXw5VSfQENxAH3AWitY5VSXwO7gBLgQa21zSrqAcyI\nMU9gsXUD+AT4TCl1ANP5P9EqK10p9U9gg5XvRa116eCAp4CvlFIvAVusMoRotvIzjuOqXfANlEte\n5T12RRcUMLxrCGN6tSErv4i5mxNYcyiNGy+I5NIuwefcY0U0HlWdIXnni/79++uNGzc6uhpCnCX9\n8zs5uX8Veyb8zsgeElRE06KU2qS17l9VPhmfKERj2jEH1r5/VrLOTiJVll0RzZwsvSJEY8lKgPkP\nmxVzY64Dn9P9Jc4nk0nRAfSTWfKiGZMWihCNZdnfwV5ibpumn3HIvSCVVPwJ8paAIpovCShCNIYj\nv8POOezvfDcJrS8yuxDais2xkkI8S7LJc2uNs5N0LIvmSwKKEA3NboNFT1LiE8H42MG8kDTUTGTc\nvcAcz5VZ8uL8IAFFiIYWtxqSdzDTczJ5djeWl/Qm2zMS1n9kjlvLrsgsedHcSUARoqEl7QDg7aPt\n+NPIzvRrF8SX9pFw9Hc4vPrUsivOvjKpUTRvMspLiAZmS4olQwUQGBzG3Re3J8THnZfmDOXOwKW4\nz7gGe0gPnACPANn7XDRv0kIRooHlHdvOrpJInr2qO+4uzoztHY7dw59/RH4Mg+5Hpe6mSDvjGyTr\neInmTQKKEA3JbsMr6wB7dVuGdAwCwNPNmev7RfDtrhwyL32R2HGLmFL8JMF+Xg6urBB1IwFFiIaU\nfggXeyFprTrRyv30FeZbBralqMTOHz/fzPq8MH6195JZ8qLZk4AiRENKthbiDu1xRnL3Nr68cVNv\nth7L5MUfdpksElBEMycBRYgGVJCwA5tW+Lftedaxm/tHseDhYXQL86G1tzsBXrI5lGjeZJSXEA3o\n5LEdZOgwukZVPGmxU4gPCx6+iJOFNll+XTR70kIRogG5nNjNHh1FTLhvpXlcnZ3wk9aJOA9IQBGi\noRTl4Z0fzzHX9oT4SP+IOP9JQBGioaTswQlNYWA3R9dEiEYhAUU0Gyv3pvD2iv00l11GS46bEV7u\nEb0cXBMhGod0yosmJSu/GD/Ps/sTUrILeGTWFnIKSrBrzaMjuzigdjWTdWQrntqdiPbdHV0VIRqF\ntFBEkzH154P0e/FHFm4/ftaxF37YRWGJnZHdQ3lr+X7mbU1wQA1rpuR4LPt0BD0i/B1dFSEahQQU\n0ST8duAEbyzdg5uLE49/s5Xt8Zmnjq3YnczC7cd55PJOvHfbBQxsH8gTc7az6UiGA2tchbw0gtI3\ns41uRAe1cnRthGgUElCEwyVm5vPwrC10DPZm2Z8vpbW3O3fP2MiqfanM+D2O577fSZdQb+69pCNu\nLk68f/uFtPHz4L7PNnIs/aSjq1+x7bNx0cVsbn217MIoWgwJKMKhtNY8+tVWCottTL39QqICvfhk\n8gBOFtmYNG09z8+PBeD1m/rg5mL+XANbufHJ5AEUlti5e8ZGcgqKsdk1OxOyyDpZ7MiXY2hN8cYZ\nbLV3JKrrAEfXRohGI53ywqG2x2exPi6df1zTg04h3gB0DTOzx/cn59Ar0o8wX4+zZpF3CvFm6m0X\nMvnT9Yz732+k5RaSXVBC3yh/5tw/BBdnB35XStiEa9oeZtvu5qFBbR1XDyEambRQhEN9teEonq7O\n3HBh5Bnp7Vu34sqYMNr4eVa6JMlFnVvzyvW9UApG9wzjj8M7svVYJh+sOtQYVa+UbeN0TuJBTudr\nifD3dGhdhGhM0kIRDpNXWML8rYmM7d0GX4/aLT0yfkAU4wdEnXp8NP0kby3fx2VdQ+hxjuVOGkxh\nDnrHHBaUDGbCMBkuLFoWaaGIRpNbWMK4//3Kx6tNC2LBtkTyimxMHFh/l4VeurYn/l5uPPb1VgpL\nbPVWbrVtn42LLZ9ffUYzrGPrxn9+IRxIAopoNMt2JbE9PouXFu7m49WHmLX+KF1Cvbmgbf3N0who\n5cZrN/ZiT1IOry7eU2/lVktxAcU/v8Eme2f6DR2Fk4zuEi2MBBTRaOZtTSTC35Oreobx0sLdbIvP\nYuKAttVftv3YBlj3AZQUnjPb5d1CuXNYNJ/+FseyXcn1UPNq2jQd17wk3nO6hRv7R1WdX4jzjAQU\n0SjScgtZvf8E4/qG8/Yt/RgVE4qfpys3XBBRvQKyEuDLm2Hxk/D+xXDk9zOP718O7w2FrydBXhpP\nX9WNmHBfnpizjZ/2JPPCglhGv7WKbccyKy6/ropOUvjzG6yx9WDIiOsrXD5GiPOddMqLRrFwx3Fs\nds21fcNxdTaTE/OKbHi7V+NP0FYC394NJUVwzX9h1b/h06sgJAba9IGTabB/Kfi3hb2L4eg63K9/\nn//dOpCxb69myvSNuDk74eQE7/x0gI8n96+fF1WYa7b49QzAtvN73AtOMMv7cf41JLp+yheimZGA\nIhrFvK2JdA31oVuYGXmllDo7mOQkw8Zp0OsmaN35dPovr8LR3+H6D6HPBOh1s7n0deR3OLAMigtg\n5Asw+AFI3WOCz2fX0378DKZPuZj4jJOM6B7K9JW7eHNVPHEn8ohuXcflULQmZfrthBxfCYAz8Iut\nN9dde+OpCZhCtDSquSwFXh/69++vN27c6OhqtDjH0k9y8esreXJ0Vx4Y3qniTHYbzLwW4lYDCmKu\ng8AOsP9HSNoBfW+D6947+zytzc2pzId40UlTVtIOmLLEtGJ+fxu9/AUeKX6IoIET+Me4mDq9prT1\nswladC/T9DVsLW6Hn8olp90VvHnP1bKVrzjvKKU2aa2rbNpLC0U0uO+3mJWBr+kdXnmm1f8xwWTU\n/0FeKqz/GIpPQtQguOJFGHhvxecpZW5luXnBxC/gw8tg1i3QdhDEfodyduPZVvMZsXEIf76iS637\nOex5GTgveYpY3Z6RD73HGDc3Nh/NYEB0oAQT0aJJQBEN6mBqLu/9fJDhXYOJCvSqONPRtfDzK+ZS\n1uAHTIC4+C+gbeDhV7sn9g6BW7+CT0ZB7Pcw4u/gE06b7+9nYMkmZv7eidE9w0jLK6JPpD+ebs7V\nLnr/rMfpaMviyLCpjAk2l/DG9GpTu3oKcR6RgCIaTGGJjYe/3IKHqxOv3di74kxaw/cPgH8UXP2f\n060Nd++6VyCsF9yxwHTmtxsCtmL46SWeLFjCmGX9+PeyfQBMGtKOF6/tWa0i9/44ja7x37LY9yau\numJ03esoxHlEAopoMK8t3suu49l8Mrk/ob4eFWdK3ALpB+Had8GjAZZKibjw9H1nVxjyID2WPsPb\nF5egI/qzZHsiX288xqMjuxDYyg2AohI7B1Jy2Z+SQ0p2If2jA+gT6c+apV8xcO1f2ObSkwun/Fsu\nbwlRjgQU0SC2HM1g2m+HuWNoNCO6h1aecfcCUM7QdUzjVOyCSfDLa4w7+A+Ic2dc2n5esk/g87Wd\neGREZ3IKirnh3d9QJ/Yw2mkD/Z32cpAANrkEc5t9AfFu7Wn/4Hx8/WUXRiHKk4AiGsTHqw/j6+HC\nE6O6njvjnh8g+iLwCmycirl7w6VPwbqpENQZ5eTCn1Pnc/XvV3LvJR3469xt/C3rb1zivh2Nwhbc\nneKcPXgWrOKEZzsi7l+Im39Q49RViGamyoCilJoGjAVStNY9rbRAYDYQDcQB47XWGdaxZ4C7ABvw\niNZ6qZV+ITAd8AQWAX/SWmullDswE7gQSAMmaK3jrHMmA89ZVXlJaz3DSm8PfAUEAZuAP2iti+rw\nPoh6dCz9JIt3HufeSzrSqvxck9wU8Gpthvmm7oUT+yofwdVQhjxgbgDHt+H9wSVcVzyfe2a2oeuh\nGVziuh2GP4O68A5cfMLMP0lhLq1dPcGp+p33QrQ01ZmBNR0o3/v4NLBCa90ZWGE9RinVA5gIxFjn\nvKeUKv0PnArcA3S2bqVl3gVkaK07AW8Cr1llBQLPA4OAgcDzSqkA65zXgDetczKsMkQT8elvcTgp\nxeSh7c48kJsKb/WChX82j3fPNz+7Xd24FSyrTR90t7Hc67aYrAPreNL1G3SX0aYV4xN2Op+7twQT\nIapQZUDRWq8C0sslXwvMsO7PAK4rk/6V1rpQa30YOAAMVEq1AXy11mu1mUk5s9w5pWXNAUYo09s5\nClimtU63Wj/LgNHWscutvOWfXzhYdkExszccZWzvNrTxK7e51L4lUFIAm6abGfG7f4DIAeB7jvkp\njUBd9iyt9Em+9ngJFzd31Ng3z57bIoSoUm3XiAjVWh+37icBpb2uEcCxMvnirbQI63759DPO0VqX\nAFmYS1mVlRUEZFp5y5d1FqXUvUqpjUqpjampqTV5jaIWZq8/Rl6Rjbsu6nD2wb2LwTcSOl0Bi56A\n41uh+zWNX8nyQmMg5no8dCFOo152eIATormq86JDVoujya7forX+UGvdX2vdPzg42NHVOe8t2J5I\nv7b+9IosNyGxOB8O/gTdxsCNH5mFHAG6jW38SlZkzL/g+g/MKDAhRK3UNqAkW5exsH6mWOkJQNmN\nICKttATrfvn0M85RSrkAfpjO+crKSgP8rbzlyxIOdjT9JD3aVDCf5NAvUJIPXa8CzwCYNA/Gz4Sg\njo1fyYq0ag19JsqlLiHqoLYBZT4w2bo/GZhXJn2iUsrdGonVGVhvXR7LVkoNtvpAJpU7p7Ssm4Cf\nrFbPUuBKpVSA1Rl/JbDUOrbSylv++YUD5RWWkHmymIgAz7MP7l0Ebj7Q7iLz2L8t9Li2cSsohGhQ\n1Rk2PAsYDrRWSsVjRl69CnytlLoLOAKMB9BaxyqlvgZ2ASXAg1rr0o29H+D0sOHF1g3gE+AzpdQB\nTOf/RKusdKXUP4ENVr4XtdalgwOeAr5SSr0EbLHKEA6WkJkPQIR/uYBit5sO+c4jwcXNATUTQjSG\nKgOK1vqWSg6NqCT/y8DLFaRvBM5aMElrXQDcXElZ04BpFaQfwgwlFk1IQoYJKJHlWyiJWyA3ufFm\nwwshHEJ2AhL1Jv5UC6XcqsK7vjPLq3Qa6YBaCSEaiwQUUW8SMvJxdVaE+LifTjy6DtZONRtmNdby\nKkIIh5CAIupNQmY+bfw8cXKyRkrlpcGcO8Ev0ixNL4Q4r8nikKLeJGbmn+6Qt9th7j2QdwLu+hE8\nZXVeIc530kIR9SYhI//0kOENH8PBFTD6FQjv69iKCSEahQQUUS+KSuwk5xSYFkrmUVj+D9MJ33+K\no6smhGgkElBEvUjKKkBriPD3gAWPmhnnssiiEC2K9KGIehGfeRKAfhlLzKWuMf86vV6XEKJFkBaK\nqBelkxrb7ZsObfpAf9miRoiWRgKKqBcJmfkopXHNioO2Q82OjEKIFkX+60W9SMjIp5t3Pqo4DwLb\nO7o6QggHkIAi6kVCZj79WmWYB4EVbK4lhDjvSUAR9SIhM5/u7ifMgwBpoQjREklAEXVmt2uOZxbQ\n3iUVlJOM7hKihZKAIuosNbeQIpudCNtxs26X7HkiRIskAUXUWbw1ZDiwKEH6T4RowSSgiDqLzzCT\nGr3zjkr/iRAtmAQUUWd7knIIcs7DuTBTWihCtGASUESd7UzI4uLWueaBzEERosWSgCLqRGvNzoQs\nBvpmmQRpoQjRYklAEXWSmFVAxsliunuUzkGJdmh9hBCOIwFF1MmOeNMyaUsyeIeBWysH10gI4SgS\nUESdxCZm4eykCCiIl/4TIVo4CSiiTnYmZNE5xBunzDjpPxGihZOAIupkZ2I2fcPcIee4zEERooWT\nHRtFrSVnF5CaU8igAG0S5JKXEC2atFBEre1MMB3yvTzSTIIEFCFaNAkootZ2JmSjFLS1xZmEoM4O\nrY8QwrEkoIha25mYRYfWrXBLjTUd8h6+jq6SEMKBJKCIWrHbNdvjM+kZ4QdJ2yGsl6OrJIRwMAko\nolbWHEojObuQkR08ICMOwno7ukpCCAeTgCJq5Yt1R/D3cuXKIKtDXgKKEC2eBBRRYyk5BfwYm8zN\nF0binrrTJLaRgCJESycBRdTYNxvjKbFrbhnYFpJ2QKtg8A51dLWEEA4mAUXUiM2u+XLdUYZ2DKJD\nsDckbTMd8ko5umpCCAeTgCJqZNW+VBIy87ltUDsoKYKUPdJ/IoQAJKCIGlqxJxlvdxeu6BEKJ/aC\nvViGDAshAAkoooZ2JmTTI9wXNxcnOL7dJLbp49hKCSGaBAkootpsds2epGx6hvuZhKQd4Ooly9YL\nIYA6BhSlVJxSaodSaqtSaqOVFqiUWqaU2m/9DCiT/xml1AGl1F6l1Kgy6Rda5RxQSr2tlOnhVUq5\nK6VmW+nrlFLRZc6ZbD3HfqXU5Lq8DlE9h1JzKSi2ExNuLbGStB1CY8DJ2bEVE0I0CfXRQrlMa91X\na93fevw0sEJr3RlYYT1GKdUDmAjEAKOB95RSpZ9EU4F7gM7WbbSVfheQobXuBLwJvGaVFQg8DwwC\nBgLPlw1comHEJmYDEBPhazrkj2+XDnkhxCkNccnrWmCGdX8GcF2Z9K+01oVa68PAAWCgUqoN4Ku1\nXqu11sDMcueUljUHGGG1XkYBy7TW6VrrDGAZp4OQaCA7E7Jwd3GiU7A3HP4FinKgy6iqTxRCtAh1\nDSgaWK6U2qSUutdKC9VaH7fuJwGlM94igGNlzo230iKs++XTzzhHa10CZAFB5yjrLEqpe5VSG5VS\nG1NTU2v+CsUpsYnZdAvzwcXZCXbNA3df6DDc0dUSQjQRdQ0oF2mt+wJXAQ8qpS4pe9Bqceg6Pked\naK0/1Fr311r3Dw4OdmRVmjWtNbGJWfQI9wNbCexZaFonLu6OrpoQoomoU0DRWidYP1OA7zD9GcnW\nZSysnylW9gQgqszpkVZagnW/fPoZ5yilXAA/IO0cZYkGEp+RT3ZBiemQP/Ir5KdDj2sdXS0hRBNS\n64CilGqllPIpvQ9cCewE5gOlo64mA/Os+/OBidbIrfaYzvf11uWxbKXUYKt/ZFK5c0rLugn4yWr1\nLAWuVEoFWJ3xV1ppooHEJprtfntG+JnLXa5e0HGEg2slhGhKXOpwbijwnTXC1wX4Umu9RCm1Afha\nKXUXcAQYD6C1jlVKfQ3sAkqAB7XWNqusB4DpgCew2LoBfAJ8ppQ6AKRjRomhtU5XSv0T2GDle1Fr\nnV6H1yKqEJuYjbOToluIF+z+ATpfCW5ejq6WEKIJqXVA0VofAs6aIq21TgMq/OqqtX4ZeLmC9I1A\nz7EJbPoAABB/SURBVArSC4CbKylrGjCtZrUWtRWbmE3H4FZ4HN8AeSnQY5yjqySEaGJkpryolp0J\nWWaG/MEV4ORiWihCCFGGBBRxTlprPl59iJScQnpF+kH6IfBvC+4+jq6aEKKJqUsfijjPFRTbeHbu\nDuZuSWBUTCgTB7SF6XEQEO3oqgkhmiAJKKJSj3+zjYXbj/PYFV146LJOODkpyDgCbfo6umpCiCZI\nAoqo0KYj6f/f3p1HR1VnCRz/3myEEBIIOyQGUBYjoCyyjIoouGKLNqIOiM1g6/RMz7gc21annVa7\nj7bSrXbbLiOtdOPotNqt7XJUEBdEWWSVNQECJCAECCEhhEDWO3/8HlpgKpBQSb2q3M85derV771X\nuTdV9W793vIr3l9TwJ3j+nD72D6u8cgBd/2J9VCMMXWwYyjme1SVRz/IoXPbVtw2OmBo+uJ8d28F\nxRhTByso5nvmrt/Divxi7rqkL0kJAZ3Y4jx3bwXFGFMHKyjmGIcqqpkxJ4czOiczaWj6sTNLjvZQ\nMps/MGOM79kxFAPAgcNVzF6Ux58XbqO4vIpZ04a5UYUDFedBYiq0tp+eMcZ8nxWUFq6mVvm/pdt5\n4qONlJRXcXH/zvz0ojMYmllH0SjOs91dxpigrKC0YDm7S7nr9dVkF5QysncaD4zPcoM/BlOcD12y\nmi9AY0xEsYLSQn2+qZCfvrqSpIRYnpsyhCsGdMUb6LNutbXuGEq/K5ovSGNMRLGCEoGW5+3n2c9y\neXbKkGPPwqqHqlJYVsH2onK+2rafJ+dtom+Xtvx52rl0TU088RMcLICaStvlZYwJygpKBPrjp7l8\nvqmQN1d8w9RRPU+4/OY9B/nlO+tZvLXo27Yx/TrxzOQhJLc6ybdAiV2DYoypnxWUCLNjfzkLNhci\nArMW5jFlRKYbEqUOJeWVPD9/Cy99uY02reK457J+ZHVPITMtiV4d29S/i+t4dg2KMeYErKBEmNeW\nbUeAey/vz28+zOHTnL2My+rCkaoa5q7fTVxMDO2T4lm0pYi/LMqjrKKa64elc+/l/emQfAq//16c\nBwikZpxoSWNMC2UFxcdqa5Un521i1Y5i/nDjYFJbx/PG8m+4qF9npp/fi9mL8njxy62M6J3GrS8v\nZ8nW7360UgSuHNiN2y/uQ7+uIRhqvjgPUtMhLuHUn8sYE5WsoPhUVU0t9765hrdW7iRG4PoXFjN1\nZCaFByuYPOI04mNjmHZeTx79IIcJzyxk+/5yZlw3iEHpqew/VEnXlER6d0oOXUDF+ba7yxhTLyso\nYZZdUMqcdbvZtOcguXvLqFElMy2J0iPVbjytcX0ZdXoHpv9lGQ+/t4HuqYmM6dcZgBvOPY0/fLyZ\nXQcO86cfDeMir71JFOdBn3FN9/zGmIhnBSUMDhyu4t3Vu3hj2Q7W7jxAjEBmhzac3imZhDghv6ic\norJKHrl2AFNGuHGzXvnxCH48ezm3ju5NrHcQPrV1PC/fMpzkVvGh2a0VTPl+KNsN7Xo23d8wxkQ8\nKyhNTFV5f20B+UXlVNcoW/eVMWfdbiqqa+nftS0P/iCLa87pQfs29R+bOCejHUv/a+z3zugampnW\nlOFDdQW8cTPEJkCfS5r2bxljIpoVlCakqjz2YQ4vLNj6bVtKYhyThqVzw7DTGNAjpUGn7gY7PbjJ\nqMK7/wl5X8APX4Tu9kuNxpjgrKCE0JGqGhZvKaJT21ac0TmZp+Zt4oUFW5k6MpNfjD+ThNiY5i8K\np+KzR2HN63Dxf8OgSeGOxhjjc1ZQGklVyS44yJHqGgQ3Ntb/Ls6n6FAl4E7bVYWpIzP51YSzGnYR\noR+segUWzIDBU+GCu8MdjTEmAlhBaaQZczfy/Pwtx7SN7d+Zm0ZmcriqhuyCUjomt+LmUZmRV0y2\nfAbv3QG9L4KrnnLV0RhjTsAKSiO8vWonz8/fwsQh6Vx1djdqa5XenZLp1bHNt8tcObBbGCNspH2b\nYc0bsOR56NgPrn8ZYuPDHZUxJkJYQTlJqkpFdS2rd5Tw8zfXMKJXGo9NHEj88b9q2BwO7oHNH8E5\nUyDmFP5+bQ3kL4LcjyH3E9izFiTG9UyufhoSU0IXszEm6llBqYeq8sXmfcxelMcXm/dRWVMLQHr7\n1jx/09DwFBNVePsnsOVT93jI1IY/R20tZL8L8x+DwmyIiYOMkXDpIzBgIqREYO/KGBN2VlCOs3J7\nMXPW7WZr4SGyC0rZWXKYjskJTB5xGp3atqJtYhyXZHUh7QTXjTSZDe+4YpLYDub9EvqPh6Qg16Ic\nKoLcebB3g9udVboTqo7AkRIo2wMd+8IP/wR9L7feiDHmlFlB8ZSUV/L4nBxeW5pPUhykd0hlYI9U\n7r60L+MHdaNVXOyxK+xYBl+/Ar1GQ7/xEB/kR6qK82Deg9CmEwy6AdKHQVU5lOyAQ3vhcLG7Ev1w\nsbslpkLPC6DrQNj2Oaz+K1QcdKfuduwLc+538yY8BzPHwMcPwlW/h5WzYdksaN0O2mW64rFtAWiN\nuygx7XRolwHxrSEuEc4Y53ojMbF1x22MMQ0kqhruGJrNsH49dPmiBW4I9jWvUz7/KSoqDrMo4Xze\nO9iXwTWrmZy4hOSaEqTHUMgc5Y4zlO5yG+b+V0GfS2HpTHeNBrj2xHbQY4hbVgR6j4GB18Oe9fDW\nrVBb7W7VRyChLVQerDvA2AT3q4iBkjq64xqHCqHrANi9Fm6ZBxnD4aMHYNEfofNZsHc9dB/snqM4\nH1q1hTN/AFlXQ5eBEGvfHYwxjSMiK1R12AmXa1EFpXucLr+tDbUJKcRUlrKutidFtOO8mLXEUYNK\nHNLnEuh4BuQvhl2r3PGFlO5QddiNZyUxoLXu2/34J9wyq151PZHYeKgscxt9BFDXm7j+ZUjqANnv\nwc6V7vna94TkLtC6/Xe3+NZQXgT5C93zZoxwPYmqclfAls5014Vc/bRLqKIMnhvlitBl3vEPO8XX\nGBNiVlDq0D79dH3otivpVZXL+zKaoWMnMe283iRUlsCOpdBjKCR3+m6F6kpXJETcgeztiyHnfdcT\nGHhd8I130RZ3+i0K59/lCkUolBa4XWeBvY0jB1yvJFR/wxhjjmMFpQ5demfpv/z2NdLaJDDtn3rS\nOSXIcQ9jjDHfOtmC0qJ2rGekJfHYxEHhDsMYY6JSGC6kMMYYE42soBhjjAkJKyjGGGNCIqILiohc\nLiIbRSRXRO4LdzzGGNOSRWxBEZFY4FngCiAL+GcRyQpvVMYY03JFbEEBhgO5qrpVVSuB14AJYY7J\nGGNarEguKD2AHQGPv/HajDHGhEEkF5STIiK3ichyEVleWFgY7nCMMSZqRfKFjTuBjIDH6V7bMVR1\nJjATQEQOisjG5gmvyXUE9oU7iBCKpnyiKReIrnyiKRdovnwyT2ahSC4oy4A+ItILV0huBCafYJ2N\nJzN8QCQQkeXRkgtEVz7RlAtEVz7RlAv4L5+ILSiqWi0i/wHMBWKBWaq6PsxhGWNMixWxBQVAVT8A\nPgh3HMYYY1rAQfnjzAx3ACEUTblAdOUTTblAdOUTTbmAz/JpUcPXG2OMaTotrYdijDGmiVhBMcYY\nExIRXVBEZJaI7BWRdQFt54jIEhH52rugcbjXHi8is0VkrYhki8j9AesM9dpzReRpkfD8MHuQfM4W\nkcVefO+JSErAvPu9mDeKyGUB7WHPpyG5iMglIrLCa18hIhf7KZeG5hMw/zQRKRORnwW0hT2fRrzP\nBnnz1nvzE/2SS0Pz8ft2QEQyROQzEdng/b/v8NrTRGSeiGz27tsHrOOf7YCqRuwNGA0MAdYFtH0E\nXOFNXwnM96YnA69500lAHtDTe7wUGAkI8OHR9X2SzzLgQm96OvBrbzoLWA20AnoBW4BYv+TTwFwG\nA9296QHAzoB1wp5LQ/MJmP934G/Az/yUTwNfmzhgDXC297iDn95njcjH19sBoBswxJtuC2zyPusz\ngPu89vuAx71pX20HIrqHoqoLgP3HNwNHv12lArsC2tuISBzQGqgESkWkG5CiqkvUvQovA9c0efB1\nCJJPX2CBNz0PmOhNT8B9MCpUdRuQCwz3Sz4NyUVVV6nq0ddpPdBaRFr5JRcvxoa8NojINcA2XD5H\n23yRTwNzuRRYo6qrvXWLVLXGL7l4MTUkH19vB1S1QFVXetMHgWzcGIUTgNneYrMDYvPVdiCiC0oQ\ndwK/FZEdwO+Ao13avwOHgAJgO/A7Vd2Pe7G+CVjfb4NMrue7UZQn8d1wM8EGx/RzPsFyCTQRWKmq\nFfg7FwiSj4gkA/cCDx+3vJ/zCfba9AVUROaKyEoR+bnX7udcIHg+EbMdEJGeuN77V0AXVS3wZu0G\nunjTvtoORGNB+TfgLlXNAO4CXvLahwM1QHdc1/BuEekdnhAbZDrw7yKyAtcFrgxzPKei3lxE5Czg\nceBfwxBbYwTL5yHgKVUtC1dgjRAslzjgfGCKd3+tiIwNT4gNEiyfiNgOeF9K3gTuVNXSwHlej8OX\n13tE9JXyQfwIuMOb/hvwojc9GZijqlXAXhFZCAwDvsANLHlUnYNMhouq5uB2OyAifYHx3qxgg2Pu\nxKf51JMLIpIO/AO4WVW3eM2+zQXqzWcEcJ2IzADaAbUicgS3gfBlPvXk8g2wQFX3efM+wB2veAWf\n5gL15uP77YCIxOPeK6+q6lte8x4R6aaqBd7urL1eu6+2A9HYQ9kFXOhNXwxs9qa3e48RkTa4g1U5\nXjeyVERGemdB3Ay807whBycinb37GOAB4H+8We8CN3rHGnoBfYClfs4nWC4i0g54H3fQceHR5f2c\nCwTPR1UvUNWeqtoT+D3wqKo+4+d86nmfzQUGikiSd9zhQmCDn3OBevPx9XbA+9svAdmq+mTArHdx\nX5bx7t8JaPfPdqC5z2II5Q34K25faBXum9QtuG75CtyZD18BQ71lk3E9lvXABuCegOcZBqzDnSHx\nDN4IAj7J5w7cmR6bgMcCYwN+4cW8kYAzOPyQT0NywX3gDwFfB9w6+yWXxrw2Aes9xLFneYU9n0a8\nz27yPjfrgBl+yqUR7zVfbwdw2y/FnVl39LNwJe7suk9wX5A/BtIC1vHNdsCGXjHGGBMS0bjLyxhj\nTBhYQTHGGBMSVlCMMcaEhBUUY4wxIWEFxRhjTEhYQTHGGBMSVlCMiSAiEhvuGIwJxgqKMU1ERH4l\nIncGPH5ERO4QkXtEZJmIrBGRhwPmvy3u92DWi8htAe1lIvKEiKwGRjVzGsacNCsoxjSdWbghL44O\nAXIjbqTYPrhBCs8BhorIaG/56ao6FHeF8+0i0sFrbwN8papnq+qXzZmAMQ0RjYNDGuMLqponIkUi\nMhg33Pgq4FzcoIWrvMWScQVmAa6IXOu1Z3jtRbjRcd9sztiNaQwrKMY0rReBaUBXXI9lLPAbVX0h\ncCERGQOMA0aparmIzAcSvdlHVLWmuQI2prFsl5cxTesfwOW4nslc7zbd+70LRKSHNzJuKlDsFZP+\nuFFwjYko1kMxpgmpaqWIfAaUeL2Mj0TkTGCxG1WcMtxovnOAn4hINm7U2CXhitmYxrLRho1pQt7B\n+JXAJFXdfKLljYlktsvLmCYiIllALvCJFRPTElgPxRhjTEhYD8UYY0xIWEExxhgTElZQjDHGhIQV\nFGOMMSFhBcUYY0xI/D8NFy9fXGxMAQAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x14af4588>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "total_births.plot(title='Total births by sex and year')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 134,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "# 插入一个prop列，用于存放指定名字的婴儿数相对于总出生数的比例\n",
    "# 例如prop值为0.02表示每100名婴儿中有2名取了当前的这个名字\n",
    "# 先按year和sex分组，然后再将新列加到各个分组上\n",
    "def add_prop(group):\n",
    "    # 整数除法会向下圆整\n",
    "    births = group.births.astype(float)\n",
    "    \n",
    "    group['prop'] = births / births.sum()\n",
    "    return group \n",
    "\n",
    "names = names.groupby(['year', 'sex']).apply(add_prop)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 135,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>name</th>\n",
       "      <th>sex</th>\n",
       "      <th>births</th>\n",
       "      <th>year</th>\n",
       "      <th>prop</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Mary</td>\n",
       "      <td>F</td>\n",
       "      <td>7065</td>\n",
       "      <td>1880</td>\n",
       "      <td>0.077643</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Anna</td>\n",
       "      <td>F</td>\n",
       "      <td>2604</td>\n",
       "      <td>1880</td>\n",
       "      <td>0.028618</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Emma</td>\n",
       "      <td>F</td>\n",
       "      <td>2003</td>\n",
       "      <td>1880</td>\n",
       "      <td>0.022013</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Elizabeth</td>\n",
       "      <td>F</td>\n",
       "      <td>1939</td>\n",
       "      <td>1880</td>\n",
       "      <td>0.021309</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Minnie</td>\n",
       "      <td>F</td>\n",
       "      <td>1746</td>\n",
       "      <td>1880</td>\n",
       "      <td>0.019188</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>Margaret</td>\n",
       "      <td>F</td>\n",
       "      <td>1578</td>\n",
       "      <td>1880</td>\n",
       "      <td>0.017342</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>Ida</td>\n",
       "      <td>F</td>\n",
       "      <td>1472</td>\n",
       "      <td>1880</td>\n",
       "      <td>0.016177</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>Alice</td>\n",
       "      <td>F</td>\n",
       "      <td>1414</td>\n",
       "      <td>1880</td>\n",
       "      <td>0.015540</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>Bertha</td>\n",
       "      <td>F</td>\n",
       "      <td>1320</td>\n",
       "      <td>1880</td>\n",
       "      <td>0.014507</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>Sarah</td>\n",
       "      <td>F</td>\n",
       "      <td>1288</td>\n",
       "      <td>1880</td>\n",
       "      <td>0.014155</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>Annie</td>\n",
       "      <td>F</td>\n",
       "      <td>1258</td>\n",
       "      <td>1880</td>\n",
       "      <td>0.013825</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>Clara</td>\n",
       "      <td>F</td>\n",
       "      <td>1226</td>\n",
       "      <td>1880</td>\n",
       "      <td>0.013474</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>Ella</td>\n",
       "      <td>F</td>\n",
       "      <td>1156</td>\n",
       "      <td>1880</td>\n",
       "      <td>0.012704</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>Florence</td>\n",
       "      <td>F</td>\n",
       "      <td>1063</td>\n",
       "      <td>1880</td>\n",
       "      <td>0.011682</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>Cora</td>\n",
       "      <td>F</td>\n",
       "      <td>1045</td>\n",
       "      <td>1880</td>\n",
       "      <td>0.011484</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>Martha</td>\n",
       "      <td>F</td>\n",
       "      <td>1040</td>\n",
       "      <td>1880</td>\n",
       "      <td>0.011429</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>Laura</td>\n",
       "      <td>F</td>\n",
       "      <td>1012</td>\n",
       "      <td>1880</td>\n",
       "      <td>0.011122</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>Nellie</td>\n",
       "      <td>F</td>\n",
       "      <td>995</td>\n",
       "      <td>1880</td>\n",
       "      <td>0.010935</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>Grace</td>\n",
       "      <td>F</td>\n",
       "      <td>982</td>\n",
       "      <td>1880</td>\n",
       "      <td>0.010792</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>Carrie</td>\n",
       "      <td>F</td>\n",
       "      <td>949</td>\n",
       "      <td>1880</td>\n",
       "      <td>0.010429</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>Maude</td>\n",
       "      <td>F</td>\n",
       "      <td>858</td>\n",
       "      <td>1880</td>\n",
       "      <td>0.009429</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>Mabel</td>\n",
       "      <td>F</td>\n",
       "      <td>808</td>\n",
       "      <td>1880</td>\n",
       "      <td>0.008880</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>Bessie</td>\n",
       "      <td>F</td>\n",
       "      <td>794</td>\n",
       "      <td>1880</td>\n",
       "      <td>0.008726</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>Jennie</td>\n",
       "      <td>F</td>\n",
       "      <td>793</td>\n",
       "      <td>1880</td>\n",
       "      <td>0.008715</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>Gertrude</td>\n",
       "      <td>F</td>\n",
       "      <td>787</td>\n",
       "      <td>1880</td>\n",
       "      <td>0.008649</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>Julia</td>\n",
       "      <td>F</td>\n",
       "      <td>783</td>\n",
       "      <td>1880</td>\n",
       "      <td>0.008605</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>Hattie</td>\n",
       "      <td>F</td>\n",
       "      <td>769</td>\n",
       "      <td>1880</td>\n",
       "      <td>0.008451</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>Edith</td>\n",
       "      <td>F</td>\n",
       "      <td>768</td>\n",
       "      <td>1880</td>\n",
       "      <td>0.008440</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>Mattie</td>\n",
       "      <td>F</td>\n",
       "      <td>704</td>\n",
       "      <td>1880</td>\n",
       "      <td>0.007737</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>Rose</td>\n",
       "      <td>F</td>\n",
       "      <td>700</td>\n",
       "      <td>1880</td>\n",
       "      <td>0.007693</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1690754</th>\n",
       "      <td>Zaviyon</td>\n",
       "      <td>M</td>\n",
       "      <td>5</td>\n",
       "      <td>2010</td>\n",
       "      <td>0.000003</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1690755</th>\n",
       "      <td>Zaybrien</td>\n",
       "      <td>M</td>\n",
       "      <td>5</td>\n",
       "      <td>2010</td>\n",
       "      <td>0.000003</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1690756</th>\n",
       "      <td>Zayshawn</td>\n",
       "      <td>M</td>\n",
       "      <td>5</td>\n",
       "      <td>2010</td>\n",
       "      <td>0.000003</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1690757</th>\n",
       "      <td>Zayyan</td>\n",
       "      <td>M</td>\n",
       "      <td>5</td>\n",
       "      <td>2010</td>\n",
       "      <td>0.000003</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1690758</th>\n",
       "      <td>Zeal</td>\n",
       "      <td>M</td>\n",
       "      <td>5</td>\n",
       "      <td>2010</td>\n",
       "      <td>0.000003</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1690759</th>\n",
       "      <td>Zealan</td>\n",
       "      <td>M</td>\n",
       "      <td>5</td>\n",
       "      <td>2010</td>\n",
       "      <td>0.000003</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1690760</th>\n",
       "      <td>Zecharia</td>\n",
       "      <td>M</td>\n",
       "      <td>5</td>\n",
       "      <td>2010</td>\n",
       "      <td>0.000003</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1690761</th>\n",
       "      <td>Zeferino</td>\n",
       "      <td>M</td>\n",
       "      <td>5</td>\n",
       "      <td>2010</td>\n",
       "      <td>0.000003</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1690762</th>\n",
       "      <td>Zekariah</td>\n",
       "      <td>M</td>\n",
       "      <td>5</td>\n",
       "      <td>2010</td>\n",
       "      <td>0.000003</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1690763</th>\n",
       "      <td>Zeki</td>\n",
       "      <td>M</td>\n",
       "      <td>5</td>\n",
       "      <td>2010</td>\n",
       "      <td>0.000003</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1690764</th>\n",
       "      <td>Zeriah</td>\n",
       "      <td>M</td>\n",
       "      <td>5</td>\n",
       "      <td>2010</td>\n",
       "      <td>0.000003</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1690765</th>\n",
       "      <td>Zeshan</td>\n",
       "      <td>M</td>\n",
       "      <td>5</td>\n",
       "      <td>2010</td>\n",
       "      <td>0.000003</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1690766</th>\n",
       "      <td>Zhyier</td>\n",
       "      <td>M</td>\n",
       "      <td>5</td>\n",
       "      <td>2010</td>\n",
       "      <td>0.000003</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1690767</th>\n",
       "      <td>Zildjian</td>\n",
       "      <td>M</td>\n",
       "      <td>5</td>\n",
       "      <td>2010</td>\n",
       "      <td>0.000003</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1690768</th>\n",
       "      <td>Zinn</td>\n",
       "      <td>M</td>\n",
       "      <td>5</td>\n",
       "      <td>2010</td>\n",
       "      <td>0.000003</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1690769</th>\n",
       "      <td>Zishan</td>\n",
       "      <td>M</td>\n",
       "      <td>5</td>\n",
       "      <td>2010</td>\n",
       "      <td>0.000003</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1690770</th>\n",
       "      <td>Ziven</td>\n",
       "      <td>M</td>\n",
       "      <td>5</td>\n",
       "      <td>2010</td>\n",
       "      <td>0.000003</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1690771</th>\n",
       "      <td>Zmari</td>\n",
       "      <td>M</td>\n",
       "      <td>5</td>\n",
       "      <td>2010</td>\n",
       "      <td>0.000003</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1690772</th>\n",
       "      <td>Zoren</td>\n",
       "      <td>M</td>\n",
       "      <td>5</td>\n",
       "      <td>2010</td>\n",
       "      <td>0.000003</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1690773</th>\n",
       "      <td>Zuhaib</td>\n",
       "      <td>M</td>\n",
       "      <td>5</td>\n",
       "      <td>2010</td>\n",
       "      <td>0.000003</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1690774</th>\n",
       "      <td>Zyeire</td>\n",
       "      <td>M</td>\n",
       "      <td>5</td>\n",
       "      <td>2010</td>\n",
       "      <td>0.000003</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1690775</th>\n",
       "      <td>Zygmunt</td>\n",
       "      <td>M</td>\n",
       "      <td>5</td>\n",
       "      <td>2010</td>\n",
       "      <td>0.000003</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1690776</th>\n",
       "      <td>Zykerion</td>\n",
       "      <td>M</td>\n",
       "      <td>5</td>\n",
       "      <td>2010</td>\n",
       "      <td>0.000003</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1690777</th>\n",
       "      <td>Zylar</td>\n",
       "      <td>M</td>\n",
       "      <td>5</td>\n",
       "      <td>2010</td>\n",
       "      <td>0.000003</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1690778</th>\n",
       "      <td>Zylin</td>\n",
       "      <td>M</td>\n",
       "      <td>5</td>\n",
       "      <td>2010</td>\n",
       "      <td>0.000003</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1690779</th>\n",
       "      <td>Zymaire</td>\n",
       "      <td>M</td>\n",
       "      <td>5</td>\n",
       "      <td>2010</td>\n",
       "      <td>0.000003</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1690780</th>\n",
       "      <td>Zyonne</td>\n",
       "      <td>M</td>\n",
       "      <td>5</td>\n",
       "      <td>2010</td>\n",
       "      <td>0.000003</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1690781</th>\n",
       "      <td>Zyquarius</td>\n",
       "      <td>M</td>\n",
       "      <td>5</td>\n",
       "      <td>2010</td>\n",
       "      <td>0.000003</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1690782</th>\n",
       "      <td>Zyran</td>\n",
       "      <td>M</td>\n",
       "      <td>5</td>\n",
       "      <td>2010</td>\n",
       "      <td>0.000003</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1690783</th>\n",
       "      <td>Zzyzx</td>\n",
       "      <td>M</td>\n",
       "      <td>5</td>\n",
       "      <td>2010</td>\n",
       "      <td>0.000003</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>1690784 rows × 5 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "              name sex  births  year      prop\n",
       "0             Mary   F    7065  1880  0.077643\n",
       "1             Anna   F    2604  1880  0.028618\n",
       "2             Emma   F    2003  1880  0.022013\n",
       "3        Elizabeth   F    1939  1880  0.021309\n",
       "4           Minnie   F    1746  1880  0.019188\n",
       "5         Margaret   F    1578  1880  0.017342\n",
       "6              Ida   F    1472  1880  0.016177\n",
       "7            Alice   F    1414  1880  0.015540\n",
       "8           Bertha   F    1320  1880  0.014507\n",
       "9            Sarah   F    1288  1880  0.014155\n",
       "10           Annie   F    1258  1880  0.013825\n",
       "11           Clara   F    1226  1880  0.013474\n",
       "12            Ella   F    1156  1880  0.012704\n",
       "13        Florence   F    1063  1880  0.011682\n",
       "14            Cora   F    1045  1880  0.011484\n",
       "15          Martha   F    1040  1880  0.011429\n",
       "16           Laura   F    1012  1880  0.011122\n",
       "17          Nellie   F     995  1880  0.010935\n",
       "18           Grace   F     982  1880  0.010792\n",
       "19          Carrie   F     949  1880  0.010429\n",
       "20           Maude   F     858  1880  0.009429\n",
       "21           Mabel   F     808  1880  0.008880\n",
       "22          Bessie   F     794  1880  0.008726\n",
       "23          Jennie   F     793  1880  0.008715\n",
       "24        Gertrude   F     787  1880  0.008649\n",
       "25           Julia   F     783  1880  0.008605\n",
       "26          Hattie   F     769  1880  0.008451\n",
       "27           Edith   F     768  1880  0.008440\n",
       "28          Mattie   F     704  1880  0.007737\n",
       "29            Rose   F     700  1880  0.007693\n",
       "...            ...  ..     ...   ...       ...\n",
       "1690754    Zaviyon   M       5  2010  0.000003\n",
       "1690755   Zaybrien   M       5  2010  0.000003\n",
       "1690756   Zayshawn   M       5  2010  0.000003\n",
       "1690757     Zayyan   M       5  2010  0.000003\n",
       "1690758       Zeal   M       5  2010  0.000003\n",
       "1690759     Zealan   M       5  2010  0.000003\n",
       "1690760   Zecharia   M       5  2010  0.000003\n",
       "1690761   Zeferino   M       5  2010  0.000003\n",
       "1690762   Zekariah   M       5  2010  0.000003\n",
       "1690763       Zeki   M       5  2010  0.000003\n",
       "1690764     Zeriah   M       5  2010  0.000003\n",
       "1690765     Zeshan   M       5  2010  0.000003\n",
       "1690766     Zhyier   M       5  2010  0.000003\n",
       "1690767   Zildjian   M       5  2010  0.000003\n",
       "1690768       Zinn   M       5  2010  0.000003\n",
       "1690769     Zishan   M       5  2010  0.000003\n",
       "1690770      Ziven   M       5  2010  0.000003\n",
       "1690771      Zmari   M       5  2010  0.000003\n",
       "1690772      Zoren   M       5  2010  0.000003\n",
       "1690773     Zuhaib   M       5  2010  0.000003\n",
       "1690774     Zyeire   M       5  2010  0.000003\n",
       "1690775    Zygmunt   M       5  2010  0.000003\n",
       "1690776   Zykerion   M       5  2010  0.000003\n",
       "1690777      Zylar   M       5  2010  0.000003\n",
       "1690778      Zylin   M       5  2010  0.000003\n",
       "1690779    Zymaire   M       5  2010  0.000003\n",
       "1690780     Zyonne   M       5  2010  0.000003\n",
       "1690781  Zyquarius   M       5  2010  0.000003\n",
       "1690782      Zyran   M       5  2010  0.000003\n",
       "1690783      Zzyzx   M       5  2010  0.000003\n",
       "\n",
       "[1690784 rows x 5 columns]"
      ]
     },
     "execution_count": 135,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 由于births是整数，所以我们在计算分式时必须将分子或分母转换成浮点数（Python3不需要）\n",
    "names"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 136,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "True"
      ]
     },
     "execution_count": 136,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 在做这样的分组处理时，一般都要做一些有效性检查，比如验证所有分组的prop的总和是否为1.\n",
    "# 由于是浮点数，所以使用np.allclose来检查这个分组总和是否足够接近1\n",
    "np.allclose(names.groupby(['year', 'sex']).prop.sum(), 1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 137,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# 取一个子集：每对sex/year组合的前1000个名字，这是一个分组操作\n",
    "def get_top1000(group):\n",
    "    return group.sort_values(by='births', ascending=False)[:1000]\n",
    "\n",
    "grouped = names.groupby(['year', 'sex'])\n",
    "top1000 = grouped.apply(get_top1000)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 139,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "pieces = []\n",
    "for year, group in names.groupby(['year', 'sex']):\n",
    "    pieces.append(group.sort_values(by='births', ascending=False)[:1000])\n",
    "top1000 = pd.concat(pieces, ignore_index=True)\n",
    "    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 140,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>name</th>\n",
       "      <th>sex</th>\n",
       "      <th>births</th>\n",
       "      <th>year</th>\n",
       "      <th>prop</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Mary</td>\n",
       "      <td>F</td>\n",
       "      <td>7065</td>\n",
       "      <td>1880</td>\n",
       "      <td>0.077643</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Anna</td>\n",
       "      <td>F</td>\n",
       "      <td>2604</td>\n",
       "      <td>1880</td>\n",
       "      <td>0.028618</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Emma</td>\n",
       "      <td>F</td>\n",
       "      <td>2003</td>\n",
       "      <td>1880</td>\n",
       "      <td>0.022013</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Elizabeth</td>\n",
       "      <td>F</td>\n",
       "      <td>1939</td>\n",
       "      <td>1880</td>\n",
       "      <td>0.021309</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Minnie</td>\n",
       "      <td>F</td>\n",
       "      <td>1746</td>\n",
       "      <td>1880</td>\n",
       "      <td>0.019188</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>Margaret</td>\n",
       "      <td>F</td>\n",
       "      <td>1578</td>\n",
       "      <td>1880</td>\n",
       "      <td>0.017342</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>Ida</td>\n",
       "      <td>F</td>\n",
       "      <td>1472</td>\n",
       "      <td>1880</td>\n",
       "      <td>0.016177</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>Alice</td>\n",
       "      <td>F</td>\n",
       "      <td>1414</td>\n",
       "      <td>1880</td>\n",
       "      <td>0.015540</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>Bertha</td>\n",
       "      <td>F</td>\n",
       "      <td>1320</td>\n",
       "      <td>1880</td>\n",
       "      <td>0.014507</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>Sarah</td>\n",
       "      <td>F</td>\n",
       "      <td>1288</td>\n",
       "      <td>1880</td>\n",
       "      <td>0.014155</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>Annie</td>\n",
       "      <td>F</td>\n",
       "      <td>1258</td>\n",
       "      <td>1880</td>\n",
       "      <td>0.013825</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>Clara</td>\n",
       "      <td>F</td>\n",
       "      <td>1226</td>\n",
       "      <td>1880</td>\n",
       "      <td>0.013474</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>Ella</td>\n",
       "      <td>F</td>\n",
       "      <td>1156</td>\n",
       "      <td>1880</td>\n",
       "      <td>0.012704</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>Florence</td>\n",
       "      <td>F</td>\n",
       "      <td>1063</td>\n",
       "      <td>1880</td>\n",
       "      <td>0.011682</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>Cora</td>\n",
       "      <td>F</td>\n",
       "      <td>1045</td>\n",
       "      <td>1880</td>\n",
       "      <td>0.011484</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>Martha</td>\n",
       "      <td>F</td>\n",
       "      <td>1040</td>\n",
       "      <td>1880</td>\n",
       "      <td>0.011429</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>Laura</td>\n",
       "      <td>F</td>\n",
       "      <td>1012</td>\n",
       "      <td>1880</td>\n",
       "      <td>0.011122</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>Nellie</td>\n",
       "      <td>F</td>\n",
       "      <td>995</td>\n",
       "      <td>1880</td>\n",
       "      <td>0.010935</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>Grace</td>\n",
       "      <td>F</td>\n",
       "      <td>982</td>\n",
       "      <td>1880</td>\n",
       "      <td>0.010792</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>Carrie</td>\n",
       "      <td>F</td>\n",
       "      <td>949</td>\n",
       "      <td>1880</td>\n",
       "      <td>0.010429</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>Maude</td>\n",
       "      <td>F</td>\n",
       "      <td>858</td>\n",
       "      <td>1880</td>\n",
       "      <td>0.009429</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>Mabel</td>\n",
       "      <td>F</td>\n",
       "      <td>808</td>\n",
       "      <td>1880</td>\n",
       "      <td>0.008880</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>Bessie</td>\n",
       "      <td>F</td>\n",
       "      <td>794</td>\n",
       "      <td>1880</td>\n",
       "      <td>0.008726</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>Jennie</td>\n",
       "      <td>F</td>\n",
       "      <td>793</td>\n",
       "      <td>1880</td>\n",
       "      <td>0.008715</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>Gertrude</td>\n",
       "      <td>F</td>\n",
       "      <td>787</td>\n",
       "      <td>1880</td>\n",
       "      <td>0.008649</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>Julia</td>\n",
       "      <td>F</td>\n",
       "      <td>783</td>\n",
       "      <td>1880</td>\n",
       "      <td>0.008605</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>Hattie</td>\n",
       "      <td>F</td>\n",
       "      <td>769</td>\n",
       "      <td>1880</td>\n",
       "      <td>0.008451</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>Edith</td>\n",
       "      <td>F</td>\n",
       "      <td>768</td>\n",
       "      <td>1880</td>\n",
       "      <td>0.008440</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>Mattie</td>\n",
       "      <td>F</td>\n",
       "      <td>704</td>\n",
       "      <td>1880</td>\n",
       "      <td>0.007737</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>Rose</td>\n",
       "      <td>F</td>\n",
       "      <td>700</td>\n",
       "      <td>1880</td>\n",
       "      <td>0.007693</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>261847</th>\n",
       "      <td>Yair</td>\n",
       "      <td>M</td>\n",
       "      <td>201</td>\n",
       "      <td>2010</td>\n",
       "      <td>0.000106</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>261848</th>\n",
       "      <td>Talan</td>\n",
       "      <td>M</td>\n",
       "      <td>201</td>\n",
       "      <td>2010</td>\n",
       "      <td>0.000106</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>261849</th>\n",
       "      <td>Keyon</td>\n",
       "      <td>M</td>\n",
       "      <td>201</td>\n",
       "      <td>2010</td>\n",
       "      <td>0.000106</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>261850</th>\n",
       "      <td>Kael</td>\n",
       "      <td>M</td>\n",
       "      <td>201</td>\n",
       "      <td>2010</td>\n",
       "      <td>0.000106</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>261851</th>\n",
       "      <td>Demarion</td>\n",
       "      <td>M</td>\n",
       "      <td>200</td>\n",
       "      <td>2010</td>\n",
       "      <td>0.000105</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>261852</th>\n",
       "      <td>Gibson</td>\n",
       "      <td>M</td>\n",
       "      <td>200</td>\n",
       "      <td>2010</td>\n",
       "      <td>0.000105</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>261853</th>\n",
       "      <td>Reagan</td>\n",
       "      <td>M</td>\n",
       "      <td>200</td>\n",
       "      <td>2010</td>\n",
       "      <td>0.000105</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>261854</th>\n",
       "      <td>Cristofer</td>\n",
       "      <td>M</td>\n",
       "      <td>199</td>\n",
       "      <td>2010</td>\n",
       "      <td>0.000105</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>261855</th>\n",
       "      <td>Daylen</td>\n",
       "      <td>M</td>\n",
       "      <td>199</td>\n",
       "      <td>2010</td>\n",
       "      <td>0.000105</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>261856</th>\n",
       "      <td>Jordon</td>\n",
       "      <td>M</td>\n",
       "      <td>199</td>\n",
       "      <td>2010</td>\n",
       "      <td>0.000105</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>261857</th>\n",
       "      <td>Dashawn</td>\n",
       "      <td>M</td>\n",
       "      <td>198</td>\n",
       "      <td>2010</td>\n",
       "      <td>0.000104</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>261858</th>\n",
       "      <td>Masen</td>\n",
       "      <td>M</td>\n",
       "      <td>198</td>\n",
       "      <td>2010</td>\n",
       "      <td>0.000104</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>261859</th>\n",
       "      <td>Rowen</td>\n",
       "      <td>M</td>\n",
       "      <td>197</td>\n",
       "      <td>2010</td>\n",
       "      <td>0.000104</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>261860</th>\n",
       "      <td>Yousef</td>\n",
       "      <td>M</td>\n",
       "      <td>197</td>\n",
       "      <td>2010</td>\n",
       "      <td>0.000104</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>261861</th>\n",
       "      <td>Thaddeus</td>\n",
       "      <td>M</td>\n",
       "      <td>197</td>\n",
       "      <td>2010</td>\n",
       "      <td>0.000104</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>261862</th>\n",
       "      <td>Kadin</td>\n",
       "      <td>M</td>\n",
       "      <td>197</td>\n",
       "      <td>2010</td>\n",
       "      <td>0.000104</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>261863</th>\n",
       "      <td>Dillan</td>\n",
       "      <td>M</td>\n",
       "      <td>197</td>\n",
       "      <td>2010</td>\n",
       "      <td>0.000104</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>261864</th>\n",
       "      <td>Clarence</td>\n",
       "      <td>M</td>\n",
       "      <td>197</td>\n",
       "      <td>2010</td>\n",
       "      <td>0.000104</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>261865</th>\n",
       "      <td>Slade</td>\n",
       "      <td>M</td>\n",
       "      <td>196</td>\n",
       "      <td>2010</td>\n",
       "      <td>0.000103</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>261866</th>\n",
       "      <td>Clinton</td>\n",
       "      <td>M</td>\n",
       "      <td>196</td>\n",
       "      <td>2010</td>\n",
       "      <td>0.000103</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>261867</th>\n",
       "      <td>Sheldon</td>\n",
       "      <td>M</td>\n",
       "      <td>196</td>\n",
       "      <td>2010</td>\n",
       "      <td>0.000103</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>261868</th>\n",
       "      <td>Keshawn</td>\n",
       "      <td>M</td>\n",
       "      <td>195</td>\n",
       "      <td>2010</td>\n",
       "      <td>0.000103</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>261869</th>\n",
       "      <td>Menachem</td>\n",
       "      <td>M</td>\n",
       "      <td>195</td>\n",
       "      <td>2010</td>\n",
       "      <td>0.000103</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>261870</th>\n",
       "      <td>Joziah</td>\n",
       "      <td>M</td>\n",
       "      <td>195</td>\n",
       "      <td>2010</td>\n",
       "      <td>0.000103</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>261871</th>\n",
       "      <td>Bailey</td>\n",
       "      <td>M</td>\n",
       "      <td>194</td>\n",
       "      <td>2010</td>\n",
       "      <td>0.000102</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>261872</th>\n",
       "      <td>Camilo</td>\n",
       "      <td>M</td>\n",
       "      <td>194</td>\n",
       "      <td>2010</td>\n",
       "      <td>0.000102</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>261873</th>\n",
       "      <td>Destin</td>\n",
       "      <td>M</td>\n",
       "      <td>194</td>\n",
       "      <td>2010</td>\n",
       "      <td>0.000102</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>261874</th>\n",
       "      <td>Jaquan</td>\n",
       "      <td>M</td>\n",
       "      <td>194</td>\n",
       "      <td>2010</td>\n",
       "      <td>0.000102</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>261875</th>\n",
       "      <td>Jaydan</td>\n",
       "      <td>M</td>\n",
       "      <td>194</td>\n",
       "      <td>2010</td>\n",
       "      <td>0.000102</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>261876</th>\n",
       "      <td>Maxton</td>\n",
       "      <td>M</td>\n",
       "      <td>193</td>\n",
       "      <td>2010</td>\n",
       "      <td>0.000102</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>261877 rows × 5 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "             name sex  births  year      prop\n",
       "0            Mary   F    7065  1880  0.077643\n",
       "1            Anna   F    2604  1880  0.028618\n",
       "2            Emma   F    2003  1880  0.022013\n",
       "3       Elizabeth   F    1939  1880  0.021309\n",
       "4          Minnie   F    1746  1880  0.019188\n",
       "5        Margaret   F    1578  1880  0.017342\n",
       "6             Ida   F    1472  1880  0.016177\n",
       "7           Alice   F    1414  1880  0.015540\n",
       "8          Bertha   F    1320  1880  0.014507\n",
       "9           Sarah   F    1288  1880  0.014155\n",
       "10          Annie   F    1258  1880  0.013825\n",
       "11          Clara   F    1226  1880  0.013474\n",
       "12           Ella   F    1156  1880  0.012704\n",
       "13       Florence   F    1063  1880  0.011682\n",
       "14           Cora   F    1045  1880  0.011484\n",
       "15         Martha   F    1040  1880  0.011429\n",
       "16          Laura   F    1012  1880  0.011122\n",
       "17         Nellie   F     995  1880  0.010935\n",
       "18          Grace   F     982  1880  0.010792\n",
       "19         Carrie   F     949  1880  0.010429\n",
       "20          Maude   F     858  1880  0.009429\n",
       "21          Mabel   F     808  1880  0.008880\n",
       "22         Bessie   F     794  1880  0.008726\n",
       "23         Jennie   F     793  1880  0.008715\n",
       "24       Gertrude   F     787  1880  0.008649\n",
       "25          Julia   F     783  1880  0.008605\n",
       "26         Hattie   F     769  1880  0.008451\n",
       "27          Edith   F     768  1880  0.008440\n",
       "28         Mattie   F     704  1880  0.007737\n",
       "29           Rose   F     700  1880  0.007693\n",
       "...           ...  ..     ...   ...       ...\n",
       "261847       Yair   M     201  2010  0.000106\n",
       "261848      Talan   M     201  2010  0.000106\n",
       "261849      Keyon   M     201  2010  0.000106\n",
       "261850       Kael   M     201  2010  0.000106\n",
       "261851   Demarion   M     200  2010  0.000105\n",
       "261852     Gibson   M     200  2010  0.000105\n",
       "261853     Reagan   M     200  2010  0.000105\n",
       "261854  Cristofer   M     199  2010  0.000105\n",
       "261855     Daylen   M     199  2010  0.000105\n",
       "261856     Jordon   M     199  2010  0.000105\n",
       "261857    Dashawn   M     198  2010  0.000104\n",
       "261858      Masen   M     198  2010  0.000104\n",
       "261859      Rowen   M     197  2010  0.000104\n",
       "261860     Yousef   M     197  2010  0.000104\n",
       "261861   Thaddeus   M     197  2010  0.000104\n",
       "261862      Kadin   M     197  2010  0.000104\n",
       "261863     Dillan   M     197  2010  0.000104\n",
       "261864   Clarence   M     197  2010  0.000104\n",
       "261865      Slade   M     196  2010  0.000103\n",
       "261866    Clinton   M     196  2010  0.000103\n",
       "261867    Sheldon   M     196  2010  0.000103\n",
       "261868    Keshawn   M     195  2010  0.000103\n",
       "261869   Menachem   M     195  2010  0.000103\n",
       "261870     Joziah   M     195  2010  0.000103\n",
       "261871     Bailey   M     194  2010  0.000102\n",
       "261872     Camilo   M     194  2010  0.000102\n",
       "261873     Destin   M     194  2010  0.000102\n",
       "261874     Jaquan   M     194  2010  0.000102\n",
       "261875     Jaydan   M     194  2010  0.000102\n",
       "261876     Maxton   M     193  2010  0.000102\n",
       "\n",
       "[261877 rows x 5 columns]"
      ]
     },
     "execution_count": 140,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "top1000"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 分析命名趋势"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 142,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "boys = top1000[top1000.sex == 'M']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 143,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "girls = top1000[top1000.sex == 'F']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 147,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "# 生成一张按year和name统计的总出生数透视表\n",
    "total_births = top1000.pivot_table('births', index='year', columns='name', aggfunc=sum)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 145,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
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       "      <td>104.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>112.0</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>26.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>48.0</td>\n",
       "      <td>9.0</td>\n",
       "      <td>44.0</td>\n",
       "      <td>99.0</td>\n",
       "      <td>71.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1901</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>80.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>87.0</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>26.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>56.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>31.0</td>\n",
       "      <td>58.0</td>\n",
       "      <td>57.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1902</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>78.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>91.0</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>34.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>58.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>23.0</td>\n",
       "      <td>58.0</td>\n",
       "      <td>66.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1903</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>93.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>91.0</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>19.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>64.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>41.0</td>\n",
       "      <td>83.0</td>\n",
       "      <td>74.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1904</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>117.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>80.0</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>27.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>46.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>35.0</td>\n",
       "      <td>54.0</td>\n",
       "      <td>74.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1905</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>96.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>73.0</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>24.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>66.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>24.0</td>\n",
       "      <td>55.0</td>\n",
       "      <td>61.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1906</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>96.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>72.0</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>19.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>59.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>37.0</td>\n",
       "      <td>64.0</td>\n",
       "      <td>58.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1907</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>130.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>79.0</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>19.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>53.0</td>\n",
       "      <td>11.0</td>\n",
       "      <td>39.0</td>\n",
       "      <td>92.0</td>\n",
       "      <td>72.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1908</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>114.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>84.0</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>23.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>70.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>31.0</td>\n",
       "      <td>59.0</td>\n",
       "      <td>53.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1909</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>142.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>57.0</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>22.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>59.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>39.0</td>\n",
       "      <td>57.0</td>\n",
       "      <td>76.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1981</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>14832.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>383.0</td>\n",
       "      <td>292.0</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1982</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>14538.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>372.0</td>\n",
       "      <td>275.0</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1983</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>14627.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>419.0</td>\n",
       "      <td>223.0</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>174.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1984</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>13387.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>357.0</td>\n",
       "      <td>249.0</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>200.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1985</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>13123.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>314.0</td>\n",
       "      <td>233.0</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>193.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1986</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>12685.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>369.0</td>\n",
       "      <td>228.0</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>213.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1987</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>12676.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>327.0</td>\n",
       "      <td>228.0</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>248.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1988</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>14393.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>404.0</td>\n",
       "      <td>226.0</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>238.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1989</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>15312.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>470.0</td>\n",
       "      <td>265.0</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>376.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1990</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>14545.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>507.0</td>\n",
       "      <td>311.0</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>478.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1991</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>14240.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>451.0</td>\n",
       "      <td>278.0</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>722.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1992</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>14494.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>430.0</td>\n",
       "      <td>260.0</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>978.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1993</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>13819.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>503.0</td>\n",
       "      <td>291.0</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1194.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1994</th>\n",
       "      <td>NaN</td>\n",
       "      <td>1451.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>14379.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>597.0</td>\n",
       "      <td>351.0</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1332.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1995</th>\n",
       "      <td>NaN</td>\n",
       "      <td>1254.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>13277.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>549.0</td>\n",
       "      <td>351.0</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1726.0</td>\n",
       "      <td>219.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1996</th>\n",
       "      <td>NaN</td>\n",
       "      <td>831.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>11956.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>552.0</td>\n",
       "      <td>349.0</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2063.0</td>\n",
       "      <td>339.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1997</th>\n",
       "      <td>NaN</td>\n",
       "      <td>1737.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>11156.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>645.0</td>\n",
       "      <td>386.0</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2363.0</td>\n",
       "      <td>407.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1998</th>\n",
       "      <td>NaN</td>\n",
       "      <td>1399.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>10539.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>661.0</td>\n",
       "      <td>398.0</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2690.0</td>\n",
       "      <td>478.0</td>\n",
       "      <td>225.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1999</th>\n",
       "      <td>NaN</td>\n",
       "      <td>1088.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>9846.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>211.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>710.0</td>\n",
       "      <td>430.0</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3238.0</td>\n",
       "      <td>561.0</td>\n",
       "      <td>257.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2000</th>\n",
       "      <td>NaN</td>\n",
       "      <td>1494.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>9548.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>222.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>660.0</td>\n",
       "      <td>432.0</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3783.0</td>\n",
       "      <td>691.0</td>\n",
       "      <td>320.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2001</th>\n",
       "      <td>NaN</td>\n",
       "      <td>3351.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>9529.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>244.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>687.0</td>\n",
       "      <td>526.0</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4642.0</td>\n",
       "      <td>822.0</td>\n",
       "      <td>439.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2002</th>\n",
       "      <td>NaN</td>\n",
       "      <td>4775.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>8993.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>256.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>600.0</td>\n",
       "      <td>514.0</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4883.0</td>\n",
       "      <td>1182.0</td>\n",
       "      <td>438.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2003</th>\n",
       "      <td>NaN</td>\n",
       "      <td>3670.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>8851.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>276.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>625.0</td>\n",
       "      <td>536.0</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>5080.0</td>\n",
       "      <td>1465.0</td>\n",
       "      <td>448.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2004</th>\n",
       "      <td>NaN</td>\n",
       "      <td>3482.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>8381.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>258.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>504.0</td>\n",
       "      <td>500.0</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>5359.0</td>\n",
       "      <td>1621.0</td>\n",
       "      <td>515.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2005</th>\n",
       "      <td>NaN</td>\n",
       "      <td>3452.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>7796.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>287.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>451.0</td>\n",
       "      <td>445.0</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4953.0</td>\n",
       "      <td>2266.0</td>\n",
       "      <td>502.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2006</th>\n",
       "      <td>NaN</td>\n",
       "      <td>3737.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>8279.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>297.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>404.0</td>\n",
       "      <td>440.0</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>5145.0</td>\n",
       "      <td>2839.0</td>\n",
       "      <td>530.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2007</th>\n",
       "      <td>NaN</td>\n",
       "      <td>3941.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>8914.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>313.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>349.0</td>\n",
       "      <td>468.0</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4925.0</td>\n",
       "      <td>3028.0</td>\n",
       "      <td>526.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2008</th>\n",
       "      <td>955.0</td>\n",
       "      <td>4028.0</td>\n",
       "      <td>219.0</td>\n",
       "      <td>8511.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>317.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>344.0</td>\n",
       "      <td>400.0</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4764.0</td>\n",
       "      <td>3438.0</td>\n",
       "      <td>492.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2009</th>\n",
       "      <td>1265.0</td>\n",
       "      <td>4352.0</td>\n",
       "      <td>270.0</td>\n",
       "      <td>7936.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>296.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>307.0</td>\n",
       "      <td>369.0</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>5120.0</td>\n",
       "      <td>3981.0</td>\n",
       "      <td>496.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2010</th>\n",
       "      <td>448.0</td>\n",
       "      <td>4628.0</td>\n",
       "      <td>438.0</td>\n",
       "      <td>7374.0</td>\n",
       "      <td>226.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>277.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>295.0</td>\n",
       "      <td>324.0</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>6200.0</td>\n",
       "      <td>5164.0</td>\n",
       "      <td>504.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>258.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>131 rows × 6868 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "name   Aaden  Aaliyah  Aarav    Aaron  Aarush   Ab  Abagail  Abb  Abbey  \\\n",
       "year                                                                      \n",
       "1880     NaN      NaN    NaN    102.0     NaN  NaN      NaN  NaN    NaN   \n",
       "1881     NaN      NaN    NaN     94.0     NaN  NaN      NaN  NaN    NaN   \n",
       "1882     NaN      NaN    NaN     85.0     NaN  NaN      NaN  NaN    NaN   \n",
       "1883     NaN      NaN    NaN    105.0     NaN  NaN      NaN  NaN    NaN   \n",
       "1884     NaN      NaN    NaN     97.0     NaN  NaN      NaN  NaN    NaN   \n",
       "1885     NaN      NaN    NaN     88.0     NaN  6.0      NaN  NaN    NaN   \n",
       "1886     NaN      NaN    NaN     86.0     NaN  NaN      NaN  NaN    NaN   \n",
       "1887     NaN      NaN    NaN     78.0     NaN  NaN      NaN  NaN    NaN   \n",
       "1888     NaN      NaN    NaN     90.0     NaN  NaN      NaN  NaN    NaN   \n",
       "1889     NaN      NaN    NaN     85.0     NaN  NaN      NaN  NaN    NaN   \n",
       "1890     NaN      NaN    NaN     96.0     NaN  NaN      NaN  6.0    NaN   \n",
       "1891     NaN      NaN    NaN     69.0     NaN  NaN      NaN  NaN    NaN   \n",
       "1892     NaN      NaN    NaN     95.0     NaN  NaN      NaN  NaN    NaN   \n",
       "1893     NaN      NaN    NaN     81.0     NaN  NaN      NaN  NaN    NaN   \n",
       "1894     NaN      NaN    NaN     79.0     NaN  NaN      NaN  NaN    NaN   \n",
       "1895     NaN      NaN    NaN     94.0     NaN  NaN      NaN  NaN    NaN   \n",
       "1896     NaN      NaN    NaN     69.0     NaN  NaN      NaN  NaN    NaN   \n",
       "1897     NaN      NaN    NaN     87.0     NaN  NaN      NaN  NaN    NaN   \n",
       "1898     NaN      NaN    NaN     89.0     NaN  NaN      NaN  NaN    NaN   \n",
       "1899     NaN      NaN    NaN     71.0     NaN  NaN      NaN  NaN    NaN   \n",
       "1900     NaN      NaN    NaN    104.0     NaN  NaN      NaN  NaN    NaN   \n",
       "1901     NaN      NaN    NaN     80.0     NaN  NaN      NaN  NaN    NaN   \n",
       "1902     NaN      NaN    NaN     78.0     NaN  NaN      NaN  NaN    NaN   \n",
       "1903     NaN      NaN    NaN     93.0     NaN  NaN      NaN  NaN    NaN   \n",
       "1904     NaN      NaN    NaN    117.0     NaN  NaN      NaN  NaN    NaN   \n",
       "1905     NaN      NaN    NaN     96.0     NaN  NaN      NaN  NaN    NaN   \n",
       "1906     NaN      NaN    NaN     96.0     NaN  NaN      NaN  NaN    NaN   \n",
       "1907     NaN      NaN    NaN    130.0     NaN  NaN      NaN  NaN    NaN   \n",
       "1908     NaN      NaN    NaN    114.0     NaN  NaN      NaN  NaN    NaN   \n",
       "1909     NaN      NaN    NaN    142.0     NaN  NaN      NaN  NaN    NaN   \n",
       "...      ...      ...    ...      ...     ...  ...      ...  ...    ...   \n",
       "1981     NaN      NaN    NaN  14832.0     NaN  NaN      NaN  NaN  383.0   \n",
       "1982     NaN      NaN    NaN  14538.0     NaN  NaN      NaN  NaN  372.0   \n",
       "1983     NaN      NaN    NaN  14627.0     NaN  NaN      NaN  NaN  419.0   \n",
       "1984     NaN      NaN    NaN  13387.0     NaN  NaN      NaN  NaN  357.0   \n",
       "1985     NaN      NaN    NaN  13123.0     NaN  NaN      NaN  NaN  314.0   \n",
       "1986     NaN      NaN    NaN  12685.0     NaN  NaN      NaN  NaN  369.0   \n",
       "1987     NaN      NaN    NaN  12676.0     NaN  NaN      NaN  NaN  327.0   \n",
       "1988     NaN      NaN    NaN  14393.0     NaN  NaN      NaN  NaN  404.0   \n",
       "1989     NaN      NaN    NaN  15312.0     NaN  NaN      NaN  NaN  470.0   \n",
       "1990     NaN      NaN    NaN  14545.0     NaN  NaN      NaN  NaN  507.0   \n",
       "1991     NaN      NaN    NaN  14240.0     NaN  NaN      NaN  NaN  451.0   \n",
       "1992     NaN      NaN    NaN  14494.0     NaN  NaN      NaN  NaN  430.0   \n",
       "1993     NaN      NaN    NaN  13819.0     NaN  NaN      NaN  NaN  503.0   \n",
       "1994     NaN   1451.0    NaN  14379.0     NaN  NaN      NaN  NaN  597.0   \n",
       "1995     NaN   1254.0    NaN  13277.0     NaN  NaN      NaN  NaN  549.0   \n",
       "1996     NaN    831.0    NaN  11956.0     NaN  NaN      NaN  NaN  552.0   \n",
       "1997     NaN   1737.0    NaN  11156.0     NaN  NaN      NaN  NaN  645.0   \n",
       "1998     NaN   1399.0    NaN  10539.0     NaN  NaN      NaN  NaN  661.0   \n",
       "1999     NaN   1088.0    NaN   9846.0     NaN  NaN    211.0  NaN  710.0   \n",
       "2000     NaN   1494.0    NaN   9548.0     NaN  NaN    222.0  NaN  660.0   \n",
       "2001     NaN   3351.0    NaN   9529.0     NaN  NaN    244.0  NaN  687.0   \n",
       "2002     NaN   4775.0    NaN   8993.0     NaN  NaN    256.0  NaN  600.0   \n",
       "2003     NaN   3670.0    NaN   8851.0     NaN  NaN    276.0  NaN  625.0   \n",
       "2004     NaN   3482.0    NaN   8381.0     NaN  NaN    258.0  NaN  504.0   \n",
       "2005     NaN   3452.0    NaN   7796.0     NaN  NaN    287.0  NaN  451.0   \n",
       "2006     NaN   3737.0    NaN   8279.0     NaN  NaN    297.0  NaN  404.0   \n",
       "2007     NaN   3941.0    NaN   8914.0     NaN  NaN    313.0  NaN  349.0   \n",
       "2008   955.0   4028.0  219.0   8511.0     NaN  NaN    317.0  NaN  344.0   \n",
       "2009  1265.0   4352.0  270.0   7936.0     NaN  NaN    296.0  NaN  307.0   \n",
       "2010   448.0   4628.0  438.0   7374.0   226.0  NaN    277.0  NaN  295.0   \n",
       "\n",
       "name  Abbie  ...     Zoa     Zoe    Zoey   Zoie  Zola  Zollie  Zona  Zora  \\\n",
       "year         ...                                                            \n",
       "1880   71.0  ...     8.0    23.0     NaN    NaN   7.0     NaN   8.0  28.0   \n",
       "1881   81.0  ...     NaN    22.0     NaN    NaN  10.0     NaN   9.0  21.0   \n",
       "1882   80.0  ...     8.0    25.0     NaN    NaN   9.0     NaN  17.0  32.0   \n",
       "1883   79.0  ...     NaN    23.0     NaN    NaN  10.0     NaN  11.0  35.0   \n",
       "1884   98.0  ...    13.0    31.0     NaN    NaN  14.0     6.0   8.0  58.0   \n",
       "1885   88.0  ...     6.0    27.0     NaN    NaN  12.0     6.0  14.0  48.0   \n",
       "1886   84.0  ...    13.0    25.0     NaN    NaN   8.0     NaN  20.0  52.0   \n",
       "1887  104.0  ...     9.0    34.0     NaN    NaN  23.0     NaN  28.0  46.0   \n",
       "1888  137.0  ...    11.0    42.0     NaN    NaN  23.0     7.0  30.0  42.0   \n",
       "1889  107.0  ...    14.0    29.0     NaN    NaN  22.0     NaN  29.0  53.0   \n",
       "1890  140.0  ...     NaN    42.0     NaN    NaN  32.0     7.0  27.0  60.0   \n",
       "1891  124.0  ...     NaN    34.0     NaN    NaN  29.0     6.0  14.0  52.0   \n",
       "1892  119.0  ...     NaN    34.0     NaN    NaN  27.0     NaN  25.0  66.0   \n",
       "1893  115.0  ...     NaN    23.0     NaN    NaN  34.0     6.0  15.0  67.0   \n",
       "1894  118.0  ...     NaN    28.0     NaN    NaN  51.0     NaN  23.0  66.0   \n",
       "1895   92.0  ...     NaN    34.0     NaN    NaN  60.0    11.0  38.0  55.0   \n",
       "1896  121.0  ...     NaN    36.0     NaN    NaN  47.0     NaN  38.0  72.0   \n",
       "1897   97.0  ...     NaN    35.0     NaN    NaN  51.0     NaN  28.0  67.0   \n",
       "1898  120.0  ...     NaN    30.0     NaN    NaN  62.0     NaN  28.0  65.0   \n",
       "1899   87.0  ...     NaN    27.0     NaN    NaN  49.0     6.0  31.0  56.0   \n",
       "1900  112.0  ...     NaN    26.0     NaN    NaN  48.0     9.0  44.0  99.0   \n",
       "1901   87.0  ...     NaN    26.0     NaN    NaN  56.0     NaN  31.0  58.0   \n",
       "1902   91.0  ...     NaN    34.0     NaN    NaN  58.0     NaN  23.0  58.0   \n",
       "1903   91.0  ...     NaN    19.0     NaN    NaN  64.0     NaN  41.0  83.0   \n",
       "1904   80.0  ...     NaN    27.0     NaN    NaN  46.0     NaN  35.0  54.0   \n",
       "1905   73.0  ...     NaN    24.0     NaN    NaN  66.0     8.0  24.0  55.0   \n",
       "1906   72.0  ...     NaN    19.0     NaN    NaN  59.0     NaN  37.0  64.0   \n",
       "1907   79.0  ...     NaN    19.0     NaN    NaN  53.0    11.0  39.0  92.0   \n",
       "1908   84.0  ...     NaN    23.0     NaN    NaN  70.0     NaN  31.0  59.0   \n",
       "1909   57.0  ...     NaN    22.0     NaN    NaN  59.0     NaN  39.0  57.0   \n",
       "...     ...  ...     ...     ...     ...    ...   ...     ...   ...   ...   \n",
       "1981  292.0  ...     NaN     NaN     NaN    NaN   NaN     NaN   NaN   NaN   \n",
       "1982  275.0  ...     NaN     NaN     NaN    NaN   NaN     NaN   NaN   NaN   \n",
       "1983  223.0  ...     NaN   174.0     NaN    NaN   NaN     NaN   NaN   NaN   \n",
       "1984  249.0  ...     NaN   200.0     NaN    NaN   NaN     NaN   NaN   NaN   \n",
       "1985  233.0  ...     NaN   193.0     NaN    NaN   NaN     NaN   NaN   NaN   \n",
       "1986  228.0  ...     NaN   213.0     NaN    NaN   NaN     NaN   NaN   NaN   \n",
       "1987  228.0  ...     NaN   248.0     NaN    NaN   NaN     NaN   NaN   NaN   \n",
       "1988  226.0  ...     NaN   238.0     NaN    NaN   NaN     NaN   NaN   NaN   \n",
       "1989  265.0  ...     NaN   376.0     NaN    NaN   NaN     NaN   NaN   NaN   \n",
       "1990  311.0  ...     NaN   478.0     NaN    NaN   NaN     NaN   NaN   NaN   \n",
       "1991  278.0  ...     NaN   722.0     NaN    NaN   NaN     NaN   NaN   NaN   \n",
       "1992  260.0  ...     NaN   978.0     NaN    NaN   NaN     NaN   NaN   NaN   \n",
       "1993  291.0  ...     NaN  1194.0     NaN    NaN   NaN     NaN   NaN   NaN   \n",
       "1994  351.0  ...     NaN  1332.0     NaN    NaN   NaN     NaN   NaN   NaN   \n",
       "1995  351.0  ...     NaN  1726.0   219.0    NaN   NaN     NaN   NaN   NaN   \n",
       "1996  349.0  ...     NaN  2063.0   339.0    NaN   NaN     NaN   NaN   NaN   \n",
       "1997  386.0  ...     NaN  2363.0   407.0    NaN   NaN     NaN   NaN   NaN   \n",
       "1998  398.0  ...     NaN  2690.0   478.0  225.0   NaN     NaN   NaN   NaN   \n",
       "1999  430.0  ...     NaN  3238.0   561.0  257.0   NaN     NaN   NaN   NaN   \n",
       "2000  432.0  ...     NaN  3783.0   691.0  320.0   NaN     NaN   NaN   NaN   \n",
       "2001  526.0  ...     NaN  4642.0   822.0  439.0   NaN     NaN   NaN   NaN   \n",
       "2002  514.0  ...     NaN  4883.0  1182.0  438.0   NaN     NaN   NaN   NaN   \n",
       "2003  536.0  ...     NaN  5080.0  1465.0  448.0   NaN     NaN   NaN   NaN   \n",
       "2004  500.0  ...     NaN  5359.0  1621.0  515.0   NaN     NaN   NaN   NaN   \n",
       "2005  445.0  ...     NaN  4953.0  2266.0  502.0   NaN     NaN   NaN   NaN   \n",
       "2006  440.0  ...     NaN  5145.0  2839.0  530.0   NaN     NaN   NaN   NaN   \n",
       "2007  468.0  ...     NaN  4925.0  3028.0  526.0   NaN     NaN   NaN   NaN   \n",
       "2008  400.0  ...     NaN  4764.0  3438.0  492.0   NaN     NaN   NaN   NaN   \n",
       "2009  369.0  ...     NaN  5120.0  3981.0  496.0   NaN     NaN   NaN   NaN   \n",
       "2010  324.0  ...     NaN  6200.0  5164.0  504.0   NaN     NaN   NaN   NaN   \n",
       "\n",
       "name  Zula   Zuri  \n",
       "year               \n",
       "1880  27.0    NaN  \n",
       "1881  27.0    NaN  \n",
       "1882  21.0    NaN  \n",
       "1883  25.0    NaN  \n",
       "1884  27.0    NaN  \n",
       "1885  38.0    NaN  \n",
       "1886  43.0    NaN  \n",
       "1887  33.0    NaN  \n",
       "1888  45.0    NaN  \n",
       "1889  55.0    NaN  \n",
       "1890  65.0    NaN  \n",
       "1891  45.0    NaN  \n",
       "1892  53.0    NaN  \n",
       "1893  70.0    NaN  \n",
       "1894  64.0    NaN  \n",
       "1895  55.0    NaN  \n",
       "1896  65.0    NaN  \n",
       "1897  79.0    NaN  \n",
       "1898  83.0    NaN  \n",
       "1899  60.0    NaN  \n",
       "1900  71.0    NaN  \n",
       "1901  57.0    NaN  \n",
       "1902  66.0    NaN  \n",
       "1903  74.0    NaN  \n",
       "1904  74.0    NaN  \n",
       "1905  61.0    NaN  \n",
       "1906  58.0    NaN  \n",
       "1907  72.0    NaN  \n",
       "1908  53.0    NaN  \n",
       "1909  76.0    NaN  \n",
       "...    ...    ...  \n",
       "1981   NaN    NaN  \n",
       "1982   NaN    NaN  \n",
       "1983   NaN    NaN  \n",
       "1984   NaN    NaN  \n",
       "1985   NaN    NaN  \n",
       "1986   NaN    NaN  \n",
       "1987   NaN    NaN  \n",
       "1988   NaN    NaN  \n",
       "1989   NaN    NaN  \n",
       "1990   NaN    NaN  \n",
       "1991   NaN    NaN  \n",
       "1992   NaN    NaN  \n",
       "1993   NaN    NaN  \n",
       "1994   NaN    NaN  \n",
       "1995   NaN    NaN  \n",
       "1996   NaN    NaN  \n",
       "1997   NaN    NaN  \n",
       "1998   NaN    NaN  \n",
       "1999   NaN    NaN  \n",
       "2000   NaN    NaN  \n",
       "2001   NaN    NaN  \n",
       "2002   NaN    NaN  \n",
       "2003   NaN    NaN  \n",
       "2004   NaN    NaN  \n",
       "2005   NaN    NaN  \n",
       "2006   NaN    NaN  \n",
       "2007   NaN    NaN  \n",
       "2008   NaN    NaN  \n",
       "2009   NaN    NaN  \n",
       "2010   NaN  258.0  \n",
       "\n",
       "[131 rows x 6868 columns]"
      ]
     },
     "execution_count": 145,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "total_births"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 148,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([<matplotlib.axes._subplots.AxesSubplot object at 0x0000000014AF47F0>,\n",
       "       <matplotlib.axes._subplots.AxesSubplot object at 0x000000001759E908>,\n",
       "       <matplotlib.axes._subplots.AxesSubplot object at 0x0000000016AAD828>,\n",
       "       <matplotlib.axes._subplots.AxesSubplot object at 0x000000001A276438>], dtype=object)"
      ]
     },
     "execution_count": 148,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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YUpKXEsu10wq5eupgspNjQ/47a+/yUVzT0usEvqm9i688vZQPNlVz53mjOWFYBlc89BGv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\n8ecIqvtXZ2ynsXkms55unnQM63hd5w/0DGRc53FM2jqJsZvHsiNhBx/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XdcJ0C5kLPGhf\n9yAwx/58LjBAKVVGKRUB1ALWa61jgTNKqZb2riODLznm3LnuBpbm1b9aiJJk6ZGlhJcN54XIF/I1\nFbW4foGegYzrPI5sWzbD/hhGUkbSRdtPpp5kyrYp/HfDfzl65qglMZ7NPMuELRPoPqs7/436LxH+\nEUzqOonIite88yjyaUCdAbQPbc+oqFHsTtxtdThCiBIov1VBmmDK7XkAB4CHMUn5j0AYcBhTbi/R\nvv+/MSX5soHntNYL7esjuVBubyGme4lWSnkC3wFNgURggNb6QF4xyeBFURKkZqXSdkZbBtQdwIjm\nI6wOp8TbELeBxxY/xs0Vbuaz2z5jZcxK5uyfw5pja7BpG27KDY2mZ/WeDG00lAj/iGufNJekjCQO\nnzl8fjl69ihhZcO4Pfx2qgdUv2x/rTU7EnYw/+B8/rf3f5zNOku7Ku14rPFjNKnQpLA+tsglMT2R\nu+behb+HPzN6zcDTzdPqkIQQTqBQy+05IkmsRUmw9MhSnl32LBO7TuSWSrdYHU6pMG//PF5b9Rpu\nyo1snU1Fn4r0rt6b3jV64+vuy5TtU/hx949k2jLpFt6NIQ2HULtc7Sv2yc2x5bDpxCYWHVrE0iNL\nOZl28vw2F+VCiHcIcSlxaDR1ytWhe0R3uod3J8uWxcKDC1lwcAGHzxzGzcWNjlU7MqTRkOsqpydu\nzOqY1Ty+5HFqBtSkd43e3B5+O5V8K1kdlhDCgUliLYQTGLl6JL8d+o2V967E3dX5ay47ix92/cCO\nhB30rN6TFhVbXNYFJyEtgak7pjJj1wzSstPwdfeldrna1CpXi9rlahPiHcKqmFUsPryYhPQEvNy8\naFelHY2DG1OtbDWqla1GqG8o7q7unEw9ye+Hf2fhwYX8c/Kf8++hULSo2IIe1XvQKawT/mWKZnpd\ncWXzD8zn+13fs+XkFgBurnAzPSJ60D2iu1wLIcRlJLEWwsFpren8U2duqnATozqMsjoccQWn0k+x\n+PBi9pzaw95Te9lzag/JWckAeLp60i60Hd3Cu9GuSju83b2veb6Y5BgWH1qMm4sbXcO7UsG7QlF/\nBHENR88eZeHBhcw/MJ8DSQcI9gpmVIdR0hVHCHERSayFcHA7E3bS/9f+vN3mbfrV7Gd1OCIftNbE\npsQSkxxDg/IN8pVMC+egtWZL/BZeXfkqscmxjGgxggF1BkhZPiEEkP/EWkoQCGGRFdErUCjaVmlr\ndSgin5RSVPatTPOKzSWpLmGUUtwUfBMzes2gdZXWvLfuPf7z139Izy4ds80JIQqHJNZCWGRl9Eoa\nBjWUWeCEcCBlPcryecfPGXbTMObun8sDCx9w+NrnQgjHIYm1EBZISEtga/xWbg291epQhBCXcFEu\nPNnkScZ2HEvM2RgGLhjIvlP7rA5LCOEEJLEWwgKrYlah0ZJYC+HA2ldtz/Se03FVrgz5fQj7T++3\nOiQhhIOTxFoIC6yIXkEFrwrUC6xndShCiDxE+EcwsdtEXJQLQxYN4UBSnnOXCSFKOUmshShmWTlZ\nrDm2hnah7aTigBBOoLp/dSZ1nQTAkEVDOJh00OKIhBCOShJrIYrZphObSM5Klm4gQjiR6gHVmdRt\nEjZtY8iiIRxKOmR1SEIIBySJtRDF7M/oP3F3cadlpZZWhyKEuA41AmowqeskcnQOQxYNISY5xuqQ\nhBAORhJrIYrZn9F/0qJiC6mDLIQTqlmuJhO6TiAtJ40nFj9BYnqi1SEJIRyIJNZCFKPDZw5z6Mwh\n2oW2szoUIcQNql2uNl90+oLYlFiGLRlGSlaK1SEJIRyEJNZCFKMVR1cASP9qIZxc0wpN+aT9J+xK\n3MVzy54jKyfL6pCEEA5AEmshionWmll7Z1G/fH2q+lW1OhwhRAG1r9qeka1HsjZ2Lf9e9W9s2mZ1\nSEIIi7lZHYAQpcWaY2s4kHSA99q+Z3UoQohC0q9mPxLTExm9cTQBngG80uIVXJS0WQlRWkliLUQx\n+W7ndwR5BdEtvJvVoQghCtHDDR4mIS2Bb3d8y4a4DTzd9Gk6Vu0odeqFKIXkZ7UQxeBg0kFWxazi\n3jr34uHqYXU4QohCpJTipciX+OjWj8i2ZfPcsucYMH8AK6NXorW2OjwhRDHKd2KtlHJVSv2tlPrV\n/jpQKbVYKbXX/lgu176vKqX2KaV2K6W65VrfTCm11b5tjLL/nFdKlVFKzbSvX6eUCi+8jyiE9abv\nnI67izv31L7H6lCEEEVAKcXtEbczu+9s3mnzDkkZSQz7YxgPLHyALzZ/wfwD89mesJ3UrFSrQxVC\nFKHr6QryLLATKGt//Qrwh9b6A6XUK/bXLyul6gMDgAZAZWCJUqq21joH+BJ4FFgHLAC6AwuBIcAp\nrXVNpdQA4EPg3gJ/OiEcQFJGEnP3z6Vn9Z6U9ypvdThCiCLk5uJG35p96RHRg9n7ZvPdju/4+p+v\n0VxouQ7xDuH1lq/Tvmp7CyMVQhSFfCXWSqlQoCfwLvCCfXVfoIP9+VRgOfCyff0MrXUGcFAptQ9o\noZQ6BJTVWq+1n/NboB8mse4LjLSf62dgrFJKabmHJkqA2Xtnk5adxqB6g6wORQhRTNxd3elfpz/9\n6/QnIyeDI2eOnK9jP3f/XN5a8xbzKs6TiaKEKGHy2xXkU2AEkLuWUIjWOtb+PA4IsT+vAhzNtV+0\nfV0V+/NL1190jNY6G0gCLmvaU0o9ppSKUkpFnTx5Mp+hC2GdbFs23+/6nuYVm1MnsI7V4QghLFDG\ntQy1ytWic7XODG00lLdav8WJtBNM3j7Z6tCEEIXsmom1UqoXcEJrvfFq+9hblou8dVlrPV5rHam1\njgwODi7qtxOiwJYdXUZsSiwD6w20OhQhhINoUqEJ3cO7M2XbFOJS4qwORwhRiPLTYt0G6GPvyjED\n6KiUmgYcV0pVArA/nrDvHwPknv0i1L4uxv780vUXHaOUcgP8gYQb+DxCOJRpO6ZRxbcKHUI7WB2K\nEMKBPN/seWzaxmebPrM6FCFEIbpmYq21flVrHaq1DscMSlyqtR4EzAUetO/2IDDH/nwuMMBe6SMC\nqAWst3cbOaOUammvBjL4kmPOnetu+3tI/2rh1LYnbGfTiU3cX/d+XF1crQ5HCOFAKvtWZnCDwfx6\n4Fe2ntxqdThCiEJSkDrWHwBdlFJ7gc7212ittwM/AjuA34Cn7BVBAIYBE4F9wH7MwEWASUB5+0DH\nFzAVRoRwWjZtY9zmcXi7eXNHrTusDkcI4YCGNhpKec/y/Dfqv1LvWogS4rpmXtRaL8dU/0BrnQB0\nusp+72IqiFy6PgpoeIX16YAU+BUlxqioUfwZ/ScvN38ZPw8/q8MRQjggH3cfnmn6DCPXjGTR4UV0\nD+9udUhCiAKSmReFKGTTd05n6o6pDKw3UAYtCiHy1K9mP+qUq8OnGz8lIyfD6nCEEAUkibUQhWjp\nkaV8uP5DOlbtyL8i/4V9clEhhLgiVxdX/tX8X8QkxzB1+1SrwxFCFJAk1kIUki0nt/Dy/7N33/FV\nV/cfx1/njuQmN3sSCGGJIIhiRUHEiatWcVdQWpXinrW27t1f1bq1juJuXXW1Wq0LRHEhwwECCshM\nGNn73uSO8/vjXmJAkAAh9yZ5P33cx733u+773mPCJ+ee7/nOuJJhOcO4/cDbdcKiiLTJyIKRHNHn\nCB755hG+r/w+1nFEZAeosBZpB6trV3PxBxeTk5TDA4c+QJIrKdaRRKQTuW7UdWQkZnDVx1dpSIhI\nJ6bCWmQHhW2Yyz68jJAN8chhj5Cd9JOLhoqI/KxMTyZ/3v/PLK1eyn1z74t1HBHZTiqsRXbQ9FXT\nWVy1mKv3vZq+6X1jHUdEOqn9e+3PhMETeHbRs3y25rNYxxGR7aDCWmQHWGuZMn8KRalFmipLRHbY\n7/f+Pf3S+3H9J9dT01QT6zgiso1UWIvsgM/XfM7CioVM2n2STlYUkR2W5Eri9gNup9Jfyc2f36wL\nx4h0MiqsRXbAlPlTyE/OZ9yAcbGOIiJdxJDsIVy414W8v/J93vjhjVjHEZFtoMJaZDt9uf5L5q6f\ny5lDz8TtdMc6joh0IWcNPYu98/fmps9v4r0V78U6joi0kQprke302PzHyPJkcdKuJ8U6ioh0MU6H\nkwcOfYDds3fnjzP+yH+W/ifWkUSkDVRYi2yHhRUL+aTkE34z5Deas1pEdoq0hDT+fvjfGdljJNd/\nej3PLXou1pFEZCtUWItsh8fnP06qO5VTB50a6ygi0oUlu5P529i/cWjvQ7l91u1MmTdFJzSKxDEV\n1iLbaFn1MqaunMr4weNJTUiNdRwR6eISnAncffDdHNv/WB786kHunXuvimuROOWKdQCRzmTDvNUe\nl4eJQybGOo6IdBMuh4s/j/kzye5knlrwFA2BBq4ddS0Oo/4xkXiiwlqkDWqaanh96eu8vPhlVtSu\n4IwhZ5DlyYp1LBHpRhzGwbUjryXFncIT3z5BQ7CBW/e/FbdDsxKJxAsV1iI/Y17ZPP71/b94Z/k7\nNIeb2TN3T/5vzP/xy36/jHU0EemGjDFctvdlpCSkcP+X99MYaOTOg+4k0ZkY62giggprkS16ZsEz\n3DXnLrxuLycMPIFTdj2FQVmDYh1LRITJwybjdXv5yxd/4cJpF/LAIQ+Q7E6OdSyRbm+rg7OMMb2N\nMdONMQuNMQuMMZdGl2cZY943xiyJ3me22udqY8xSY8z3xpgjWy3f2xgzP7ruAWOMiS5PNMb8K7r8\nC2NM3/Z/qyJtY63lka8f4a45d3FEnyOYdso0rht1nYpqEYkrEwZP4P/G/B+z181m8nuT+bb821hH\nEun22nLWQxD4g7V2CDAKuNAYMwS4CphmrR0ITIs+J7puPDAUOAp42BjjjB7rEeBsYGCm2d6UAAAg\nAElEQVT0dlR0+e+AKmvtLsC9wB3t8N5Etpm1lrvn3M3D3zzMcQOO468H/hWv2xvrWCIimzVuwDju\nOfgeVtauZMJbEzhv6nl8Xfp1rGOJdFtbLayttWuttV9GH9cBi4BewHHAM9HNngGOjz4+DnjRWttk\nrV0OLAX2NcYUAGnW2pk2Mk/QPzbZZ8OxXgHGbujNFukoYRvm1pm38szCZ5gweAK37H8LTodz6zuK\niMTQ2KKxvHvSu1z6i0tZWL6Q37z9Gya/N5kv1n5BIBSIdTyRbmWbxlhHh2jsBXwB5Ftr10ZXrQPy\no497ATNb7VYcXRaIPt50+YZ9VgNYa4PGmBogGyjflnwi26Mp1MTK2pU8+e2TvLXsLSYPm8wle12C\n/rYTkc4iJSGFycMmc9rg03h58cs89e1TTH5vMi7jom96XwZmDGRg5kAGZQ1iv4L9cDs1k4jIztDm\nwtoYkwK8Clxmra1tXXRYa60xZqfPVm+MOQc4B6CoqGhnv5x0QY2BRmauncnc9XNZXrOc5TXLKakv\nwRL53/fSX1zK5GGTY5xSRGT7JLuTOWPoGZw66FQ+XP0h31V+x5LqJXxd9jVvr3gbgIGZA7l1/1sZ\nmj00xmlFup42FdbGGDeRovo5a+1r0cXrjTEF1tq10WEepdHlJUDvVrsXRpeVRB9vurz1PsXGGBeQ\nDlRsmsNaOwWYAjBixAhddkq2ylrL8prlfFzyMR+XfMzc9XMJhoMkOhPpm9aX3XN259gBx9IvvR+D\nMgfRP6N/rCOLiOwwj8vDUf2O4qh+R7Usq2uu4/M1n3PHrDs4/a3TmbT7JM7b8zwSnAkxTCrStWy1\nsI6OdX4CWGStvafVqjeAM4Dbo/evt1r+vDHmHqAnkZMUZ1lrQ8aYWmPMKCJDSX4LPLjJsT4HTgY+\nsLpeq2ynsA0zr2we01ZNY9qqaayuWw3ALhm78JvdfsMBhQcwPHe4vgoVkW4lNSGVI/oewciCkdw5\n+04em/8YH6z6gFv3v5VhucNiHU+kSzBbq1+NMWOAj4H5QDi6+BoixfFLQBGwEvi1tbYyus+1wCQi\nM4pcZq19O7p8BPA0kAS8DVwcHUbiAf5JZPx2JTDeWrvs53KNGDHCzpkzZ1vfr+xEYRvm/i/vZ23D\nWm7a76adPqdqU6iJKn8Vlf7KlvuvSr9i+urplPvKcTlcjOwxkkOLDuWAXgdQkFKwU/OIiHQmHxd/\nzM2f30yZr4xz9ziXc/c4Vydsi2yBMWautXbEVrfrrB3DKqzjSyAc4IZPb+DNZW8CsFfeXjw09iFS\nE1Lb7TUaAg3MXDOTj4o/4tOSTyn1lf5kmyRXEgf0OoCxRWM5oPCAdn19EZGupq65jttn3c4bP7zB\n/j3357YDbiPTk7n1HUW6GRXW0mGaQk1c8dEVfLj6Qy7Z6xKK0oq4asZVDMwcyN8P//t2/5Ku8lex\nuGox31V+xyclnzBn/RyC4SCp7lRG9xrNoMxBZHoyyfRkkuXJIiMxg54pPXVpXxGRbWCt5dUlr/KX\nL/5CTlIO9xx8D7vn7B7rWCJxRYW1tIviumJmrZvFl+u/pCClgMOKDmPXzF1bpqJrCDRw6QeX8sW6\nL7hm5DVMGDwBgBnFM7j8w8spTClkyhFTyEvOAyK/wL+v+p63lr3FnHVzSHQlkuJOwev2kuJOwe10\ns6JmBYurFlPmK2vJ0T+9PwcWHsiBhQcyPG84bofGR4uItKcF5Qu4/MPLKfOVcdW+V3HKrqdo2lGR\nKBXWXdCGtmrLL7pQOERVUxUVvorIzb/xfbmvnAp/BXXNdWR6MslLziMvKY+85DzSE9NZVLmIL9Z+\nQUl9ZOKWjMQMaptrCdswRalFHNbnMMb0GsN9c+9jQcUCbt3/Vo4dcOxGGWavm81F0y4iy5PFn8f8\nmbnr5/LWsrdYVrMMl3ExPG84ECnOGwIN1AfqaQo1UZRaxMDMgeyauSu7Zu7KwMyB5CTltPOnKSIi\nm6r2V3PVJ1fxacmn7N9rfyYMmsCYXmM09lq6PRXWXcjymuX8e8m/ef2H12kINJCblEtech45STnk\nJefhMI6fFM7VTdWEbfgnx0pwJJCdlE22J5vspGxSE1KpaqqirLGMssYyqpqqAEhLSGOfHvswsmAk\nI3uMpF96Pyr8FXyw6gOmrpzKrHWzCNkQboebOw+6k7FFYzebfX7ZfM6beh61zbUA/CLvF/yq/684\nos8RZHgydt6HJiIi2yVswzy94Gn+ufCflPvKyU/O56SBJ3HCwBPo4e0R63giMaHCOsastVQ1VeFy\nuEh0JpLgSMAYg7WW2uZa1jWsY33jetY1rKPCV0FqQio5yTnkJuWSm5RLakIqM4pn8NqS1/iy9Etc\nxsWBhQdSlFZEaWMpZb5IIVzaWErYhjcqljd6vMl9ijvlZ3u8m0PNVPoryU3K/dkeimp/NZ+s+YQB\n6QPYLXu3n/0sllUv47M1n3Fo0aH0TOm53Z+piIh0nEA4wEerP+KVxa/w2ZrPMMYwPHc4/TP60zet\nL33T+tInrQ+9UntpeJ50eSqsY8Ray/TV03n0m0dZVLloo3VuhxuHcdAUamrz8fqm9eWEgScwbsA4\nDYcQEZGYKK4r5rUlrzFr3SxW1q6kuqm6ZV2CI4FBWYMYmj2UoTlD2T17d/ql99tpw0caA418U/YN\nc9fPjfSoe/PpkdyDgpQCCrwF5CblkuRK0vhwaVcqrDtY2IaZunIqU+ZN4fuq7+md2puTBp6E2+Gm\nOdxMc6iZplATYRsmJymHHt4e5Cfn08Pbg+ykbOqb6ynzlVHeWE6Zr4xKfyXDcoaxd/7e+uUgIiJx\npdpfzYraFaysXcmSqiUsqFjAwoqFNAYbgcjUp/3T+7NLxi7skrELAzIG0DetL43BxpYhi5X+Sqqb\nqslJyqF/en/6p/cnLzmv5d88ay01TTUU1xdTXFfMwoqFzF0/l4UVCwnaIA7jICMxg0p/5U/yOYyD\nZFdy5OZOJi0hjT1y92CfHvuwd/7epCemd+jnJZ2fCut2VtNUw4KKBSyqWESlvxKLbTmZ0GL5Yu0X\nLK1eSt+0vpyzxzn8st8vcTnadMV4ERGRTi8UDrGydiXfVnzLwoqFLK1eyg/VP1DuK9/iPg7j2Oh8\noBR3Cv3S+xEIByiuK6Y+UN+yzu1wt3Q47Z2/N8PzhuN1e2kONbcMrVzXsI4yXxmNgUYaAg34gj4a\nA42U+8uZVzaPplATBsPgrMGM6DGCwVmD6ZfWj37p/UhJSNmpn490biqs26gp1MTnaz7nk5JP8Af9\nuJ1u3I7IzelwtvyVvGF2DIj8JW4wGGPY8F/PlJ5M2n0SR/Y9UmdPi4iIRFX7q1lavZTVdavxur1k\nJ2WT5cmKnEDvTqXCX8Gy6mX8UPMDy6qXsbx2OQmOBApTCylMKYzcpxZSlFqEx+XZ7hzNoWbml89n\n1rpZzFk3h69Lv6Y53NyyPi85j37p/Uh1p+J0OHEYB07jxGmc5Hvz2S1rN3bL3o2e3p76JrkbUmEN\nBMNBVtaubDmB0OP04HF5CIQDfFLyCVNXTuXjko/xBX143V5SE1IJhAIEbZBAKEAgHCA/OZ8h2UM2\nuukrJBERkc5tQ6/4spplLK9ZzrLqZayoXYEv6CMYDhK2YUI2RDAcpNxXTsiGgMisWbtl7UZhaiFu\nh5sEZ0Lk5kjAYRwb1RDBcJBAONByC4Z/XLfRsg3PW6+LPk52J29xQoLWjzMSM3AYR4w/1a6rrYV1\nlxur0BxqZubamby/8n2mr55OTVPNFrfN9mRzTP9jOKzoMPbpsQ9up85qFhER6Q7cDjf90iPDQLbG\nH/SzpGoJiyoXRW4Vi5hRPKPlHKoNnXKtj+1yuFq+AXc73biMa6NvxTesT3Ylt6xPcCa0bL9hu/pA\nfct0ukuqllDhryAYDv4ko8M4yEzM/EkBvuHqxFmeLDI9kfV5yXmayWUn6bQ91nmD8uwZU87A4/K0\n9ESXNpYyo3gG9YF6UtwpHNT7IEb3HI3B0BRqwh/04w/5sdYyoscI9sjZQ8M2REREZIeFwiHChHEZ\n104dKrJh2t5Nr1+x4YTQTS8Kt7mZyBzGQX5yPr1SetEzpSe9Unq1FOEbCvFMTyap7lR1OkZ1+R7r\nQCjAd5Xf4Qv6WormJFcSh/c5nMP6HMaoglEkOBNiHVNERES6AafDiZOd31lnjCE9MZ30xHT6p/ff\n6vaNgUYq/ZVU+auoaqqi3FfOmvo1lNSXsKZ+DTPXzqSssQzL5jtaExwJeN3elluiMxGnw4nL4cJp\nnC3DbTfMwJLsSibJnURaQhoF3gJ6pvSkwFtAWkJatxib3ml7rONtuj0RERGRzigQDlDtr44U4E1V\nVPmrqPRX0hBooD5QT2OgkfpAPQ2BBppDzYTCIQLhQMsY9KZQE76gr2UWFn/I/5PX8Lq95Cfnk5GY\nQUZiBumJ6ZHHngzyk/Mp8EbnIU/OjctZ1bp8j7WIiIiI7Di3w01uci65ybntcrxQOER1UzVrG9ay\npn5Ny31pYynVTdWsrl/Nt+XfUt1UvdHMLBAZppKblEtaYhop7pSWnvIUdwqZnszIFaqTc1vuc5Jy\nSHQmtkvu9qDCWkRERETajdPhbJm1ZPec3X9228ZAI+sa17Gufh1rG9aytmEt6xrWUddcR0OwgWp/\ndcuc5lX+qpbZWVpLT0wnNylSZOcl55GTlLNxAZ6US3ZSdodckVOFtYiIiIjERLI7ueXKm1sTtmGq\n/JFx4qWNpS33Zb4yyn3llDWWMXvdbMp8ZZudOcVgSHIlbTRmfMPJmtmeyPzqWUlZLbOobLhtyzl7\nKqxFREREJO45jKOlJ3xQ1qAtbhe2YWqaaijzlVHWWEaZr4wqfxUNgQYag400BiK3ukAdVf4qfqj+\ngQpfxU+GpWyQ6k5tc8a4KayNMUcB9wNO4HFr7e0xjiQiIiIinYzDOFqmDtw1c9c27WOtpTHYSKWv\nkgp/ZOrC1rfP+bxNx4mLWUGMMU5gMXA4UAzMBiZYaxduaR/NCiIiIiIiHaGts4LEy7Uv9wWWWmuX\nWWubgReB42KcSURERESkzeKlsO4FrG71vDi6TERERESkU4iXwrpNjDHnGGPmGGPmlJWVxTqOiIiI\niEiLeDl5sQTo3ep5YXTZRqy1U4ApAMYYnzFmQcfEk21UBKyKdQjZLLVN/FLbxC+1TfxS28SvrtY2\nfdqyUbycvOgicvLiWCIF9WzgNGvtFgtnY0yZtbZ9LhEk7UptE7/UNvFLbRO/1DbxS20Tv7pr28RF\nj7W1NmiMuQh4l8h0e0/+XFEdVb3zk8l2UtvEL7VN/FLbxC+1TfxS28Svbtk2cVFYA1hr/wf8bxt2\nqdlZWWSHqW3il9omfqlt4pfaJn6pbeJXt2ybTnXy4iamxDqAbJHaJn6pbeKX2iZ+qW3il9omfnXL\ntomLMdYiIiIiIp1dZ+6xFhERERGJGyqsRURERETagQprEREREZF2oMJaRERERKQdqLAWEREREWkH\nKqxFRERERNqBCmsRERERkXagwlpEREREpB2osBYRERERaQcqrEVERERE2oEKaxERERGRdqDCWkRE\nRESkHaiwFhERERFpByqsRURERETagQprEREREZF24Ip1gO2Vk5Nj+/btG+sYIiIiItLFzZ07t9xa\nm7u17TptYd23b1/mzJkT6xgiIiIi0sUZY1a2ZTsNBRERERERaQcqrEVERERE2oEKaxER2UjFE0+w\n8owzsdbGOoqISKfSacdYi4hI+wusL6Xswb9h/X78CxeSNHRorCOJSDsKBAIUFxfj9/tjHSUueTwe\nCgsLcbvd27W/CmsREWlR/tBD2FAInE7q3n9fhbVIF1NcXExqaip9+/bFGBPrOHHFWktFRQXFxcX0\n69dvu46hoSAiIgJA07JlVL/6Kpnjx5O8zz7Uvfd+rCOJSDvz+/1kZ2erqN4MYwzZ2dk71JuvwlpE\nRAAou/c+HB4POeefR+rhh9G8bBlNS5fGOpaItDMV1Vu2o5+NCmsREcH39dfUvf8+Wb+bhCsri9TD\nDgeg9r33YpxMRLoaYwwTJ05seR4MBsnNzeWYY47ZpuOsWbOGk08+GYAPP/xwm/ffGVRYi4hsA2st\n/sWLu9SMGdZa1t91F86cHLLPOAMAd34eSXvtRd37U2OcTkS6Gq/Xy7fffovP5wPg/fffp1evXtt0\njGAwSM+ePXnllVd2RsTtpsJaRKSNrLWs//P/sXzccdT85/VYx2k39R99hG/OXHIvvACH19uyPPWI\nI2hatIjm1atjmE5EuqKjjz6at956C4AXXniBCRMmtKybNWsW++23H3vttRejR4/m+++/B+Dpp59m\n3LhxHHrooYwdO5YVK1aw++67b3TccDjMwIEDKSsra3m+yy67UFZWxplnnskll1zC6NGj6d+//04p\nyjUriIhIG1hrKb39Dqqeew6TnEz5o4+QfuwxGFfn/jVqQyHK7r4Hd58iMqJfqW6QevjhlN5xB3Xv\nvUf2734Xk3yh2lqaV63GkeQhccCAmGQQ6arW/eUvNC36rl2PmbjbYHpcc81Wtxs/fjy33HILxxxz\nDPPmzWPSpEl8/PHHAAwePJiPP/4Yl8vF1KlTueaaa3j11VcB+PLLL5k3bx5ZWVmsWLHiJ8d1OBxM\nnDiR5557jssuu4ypU6ey5557kpubC8DatWv55JNP+O677xg3blzLUJL20rn/RRAR6QDWWsruuZfK\nZ54hc+JEkvfdh5JLLqX27bdJP/bYWMfbITVv/JemJUvodd+9mE3mbU0o7IVnyBBqO7Cwbpg5k6p/\n/YvA6mKaV68mXFMDgPF42PWzT3EkJ3dIDhHZufbYYw9WrFjBCy+8wNFHH73RupqaGs444wyWLFmC\nMYZAINCy7vDDDycrK+tnjz1p0iSOO+44LrvsMp588knOOuuslnXHH388DoeDIUOGsH79+vZ9U6iw\nFpEuLlRTg0lMxOHxbPcxyv/2EBWPPUbG+FPJv/YasJbEXXel/JFHSTv6aIzT2Y6JO064qYmyBx7A\nM2wYqUceudltUo84grL77iOwbh3uHj12ap5ASQnFF16ESUrCM2gQacN2J6F3EWG/j/IHHqRx7pek\nHDBmp2YQ6U7a0rO8M40bN44rrriCDz/8kIqKipbl119/PYcccgj//ve/WbFiBQcffHDLOm+r4Wpb\n0rt3b/Lz8/nggw+YNWsWzz33XMu6xMTElsc741wZjbEWkS4rWFHBD786huJLL93uY5Q/+ijlDz1E\n+kkn0uOGGzDGYBwOcs4/j+Zly6h79912TNyxqp57nuDateT94Q9bnGIq9YgjAHb6SYw2HGbNtdeB\ntfR98UWKnnicghtvJHvSWWSfdRbG7aZh5uc7NYOIdKxJkyZx4403MmzYsI2W19TUtJzM+PTTT2/X\nsSdPnszEiRM55ZRTcHZg54cKaxHpkqy1rL3+BkLl5TR8NIOmJUu2+Rg1b7xB2X33k37cOApuuQXj\n+PFXZuoRR5AwYADljzyCDYfbM3qHCNXWUv73v+M94AC8o0ZucbvE/v1IHLgLdTt52r2qF16gceZM\n8q66koTCjWcHcCQlkTR8OI2fz9ypGUSkYxUWFnLJJZf8ZPmf/vQnrr76avbaay+CweB2HXvcuHHU\n19dvNAykQ1hrf/YGPAmUAt+2WpYFvA8sid5ntlp3NbAU+B44stXyvYH50XUPACa6PBH4V3T5F0Df\nrWWy1rL33ntbEZEtqXzpJbtw0GC7/r777KI9h9s11123TfsHq6rs9/uNtstPHW/DgcBmt6l+4792\n4aDBtuadd9sjcodaf9fdduHg3axv0aKtblt6//124W5DbKC8fKdkaVq+3C4avpddOflsGw6HN5/h\noYfswsG72UBl5U7JINJdLFy4MNYROsTs2bPtmDFjtmvfzX1GwBzbhvq0LT3WTwNHbbLsKmCatXYg\nMC36HGPMEGA8MDS6z8PGmA39748AZwMDo7cNx/wdUGWt3QW4F7ijDZlERLaoeeVK1t92O8n7jSL3\n4otJP+44al5/g2BlZZuPUXrvfYRqauhx041bnPkj7ehfktC3b6TXOgbzWgcrK6l85hlWn3c+te+8\n0+YMgfXrqfzHP0g79hg8gwdvdfvUI46AcJi6qdN2NPJP2FCINVdfg3G7KfjzrVsckuIdtR9YS+MX\ns9o9g4h0LbfffjsnnXQSt912W4e/9lYLa2vtDGDTf42OA56JPn4GOL7V8hettU3W2uVEeqH3NcYU\nAGnW2pnRqv8fm+yz4VivAGONrrUpItvJBoOs+dOVGJeLnrfdhnE4yPrNRGxzM9UvvdSmY/i++Ybq\nl14ia+LEny08jdNJ9nnn0vTdd9RPn95eb+Fn2WCQuunTKb74EpYcdDDrb7sd3zffUHLZ7ym+6GIC\n60u3eozyv/0NwmFyL2nb2PPEQYNwFxXtlOEglU8/je+rr+hx3bW48/O3uF3SsN1xJCdrnLWIbNVV\nV13FypUrGTOm40923t4x1vnW2rXRx+uADb8NewGtryRQHF3WK/p40+Ub7WOtDQI1QPbmXtQYc44x\nZo4xZs6Gib9FRFqreOwxfN98Q48bbmiZxSJxl13wjhlD1XPPY5ubf3Z/Gwqx9uabceXmknPxxVt9\nvfRjjsHduzflDz2803ut/YsXs/TQsRSffwGNc+eSdfrp9HvjdQZ+PIO8P/6Rhk8+Ydkxx1D18stb\nzNL0ww9Uv/oamadN+MlY5i0xxpB2xOE0fPopi/cbzbJxx7Fq8tmsufoayh95hFB9w3a9n6YlSyi7\n735SDz+MtK1MW2jcbpL32UfjrEUkru3wdHvWWmuM6ZDvQK21U4ApACNGjOg61xMWkXbhm/8tZQ89\nTNqvfkX6Mb/aaF3WGb9l9dnnUPvOO6SPG7fFY1S98CJNCxfR6757caZsfVon43KRc965rL32Olac\n8mucaWk4vF4cyck4vF48Q4eSOvZQnBkZO/z+yh98kLDfT+FDfyPlwAM3mnc6+3eTSD1sLGuvu551\n199A7ZtvkXPBBSTv/YuNhrKU3nsvjqQkss87b5teO2vSJBxeL4F16wmWlREsLaVpyRJq/lNK3dRp\n9H5sCq6tzC3bWqimhpLL/4AjJYUeN920xSEgrSXvN4r6jz4isHYt7oKCbcovIj+y1rbpZ6472tEO\nku0trNcbYwqstWujwzw2fPdYAvRutV1hdFlJ9PGmy1vvU2yMcQHpQAUiItug8csvWfOnK3Hl5NDj\nhut/st47ZgwJAwZQ+fQzpB177Gb/UQmUllJ23314999/i/M6b076uHE0LV5M05IlhBsaCJaVEm5o\nJFRXR9Xzz7P2RhfekSNJPfIIUg87bJsK0A2ali2jbuo0ss87l9SxYze7TUKfPhQ98zTVL79C6Z13\nsuqMM3Cmp5NyyCGkHjYWR3Iy9VOnkXvZpbgyM7fp9V1ZWeScf/5Pltd9+CEll/2elRNOo/cTT7Sp\nFzxU38Cqc86hecUKCh99BFf2Zr+k/AnvfvsB0PD5TDJOPGGb8otIhMfjoaKiguzsbBXXm7DWUlFR\ngWcHrntg2lKZG2P6Am9aa3ePPr8TqLDW3m6MuQrIstb+yRgzFHge2BfoSeTExoHW2pAxZhZwCZGZ\nP/4HPGit/Z8x5kJgmLX2PGPMeOBEa+2vt5ZpxIgRds6cOdvxlkWkKwlWVlJ6193UvPYaroICet1z\nN8l77bXZbate/BfrbrqJPs/+k+QRI36yvuSKP1L33nv0f+N1Evr23eFs1lr8CxZS9+671L77LoFV\nqyA65jv/6qu36Vhrrr2W2rf+xy4fTGtTYR5uaKD+k0+pmzaV+g8/IlxbC4AzN4dd3n23Xa9g2Pjl\nV6w+7zwciYn0fvxxPIN23XIuv5/V555H45w59LrvXtIOP7zNr2PDYZaMOQDvmP3p9de/tkd0kW4n\nEAhQXFyM3++PdZS45PF4KCwsxL3JlWiNMXOttT/9h2MTWy2sjTEvAAcDOcB64EbgP8BLQBGwEvi1\ntbYyuv21wCQgCFxmrX07unwEkRlGkoC3gYujw0g8wD+BvYicJDneWrtsa8FVWIt0bzYUivTM3nsv\n4YYGss86k5zzz//ZgjHs87Hk4EPw7rsvhQ8+8OPy5mZqXnuNdTfdTM6FF5J78UXtn9damr7/nsqn\nn6HmP/+h4C9/aXOva2DdOpYefgSZp5yy2d74rb52IEDjnDnUfzQD75gxpIzZf5uPsTX+xYtZPfls\nwn4/vR99hORf/OKnOZqbKb74EupnzKDnHbf/7JCcLSm5/HIaZ89hlxkfqbdNRDpMuxXW8UqFtUj3\nFW5qYtWZZ+H76iuS992XHjdcT+Iuu7Rp39K776HiiScY8N67EAxS9dLL1Lz2GqHqajxDh9LnuWd3\n6PLnW2NDIVadNQnfvHn0e/klEgcO3Oo+6+/4K5X/+AcD3n2HhMLCrW4fK4GSElb9bjKBtWtJ++Uv\nSR6xN8kjRuDu0wfCYUquuIK6t9+hx003kTn+1O16jaqXXmLdDTfS/603SRwwoJ3fgYjI5qmwFpEu\nq/7jj1l99jnkX3M1mb/5zTb1XAbWrWPpYYfjys4muH49OJ2kjh1L5vhTSR41aqOrK+4sgdJSlp9w\nIs6MDPq9/NLP9rKHampYesihpIwdS68743/4Q7CykvV//j8aPv+cUFUVAM6cHNz5+fgXLCDvj38k\n+3eTtvv4zcXF/HDY4eRfdx1ZE09vr9giIj+rrYW1LmkuIp1O46zZ4HaTcfLJ2zwcwN2jB5m/PgWT\nkEDuZZeyy/QPKHzgfryjR3dIUQ3gzsuj11130rxsGetuufVnt6164QXCjY1kT/5dh2TbUa6sLHrd\nczcDP/uU/m+9SY+bb8Y7ej/Cfj+5l1++Q0U1QEJhIe7CQs1nLSJxaYen2xMR6WiNs2aRtPvu230C\nXo8bbmjnRNvOu99+5FxwAeUPPUTyPvuQcdKJP9km7PdT+Y9/4j3oQDyDBsUg5Yiy1JAAACAASURB\nVPYzxpA4YACJAwaQeepWz0ffJt79RlH7zrvYUAjjdG59BxGRDqIeaxHpVMKNjfgWLCB5n31iHWWH\n5VxwPskjR7Lu1lvxL178k/XVr71GqLKSnMmTY5AufiWPGkW4rg7/ggWxjiIishEV1iLSqTR+9RUE\ngyTvu2+so+ww43TS6647caSksHLCaaw65xzKH/07jbNnE25ooPKJJ0kaPpykzUwN2J15R40CIvNZ\ni4jEEw0FEZFOpXHWbHA6Sd5reKyjtAtXbi5FTzxO1XPP0/jlXMpmfBxZ4XBAOEz+NVdrWrlNuLKz\nSdx1Vxpmfk7OuefEOo6ISAsV1iLSqTTOno1n96E4vFu/3Hhn4Rk0iIJbbgYgWFWF76uv8X31Jba5\nmZRDDolxuvjk3W8UVS/+i7Dfv1OnRxQR2RYaCiIinUbY58M3fz7eLjAMZEtcmZmkHnoIeX/4A/lX\nX91hM5V0NikHH4xtaqLuvfdiHUVEpIV+Y4tIp+H7+msIBLrEiYuyY5JHjiShXz8q//lsrKOIiLRQ\nYS0inUbj7NngcJC0mctlS/diHA4yTz8d//z5+L75JtZxREQAFdYi0ok0zJqFZ+hQnCkpsY4icSD9\n+ONxeL1UPvtcrKOIiAAqrEWkkwj7/fi/madhINLCmeIl/cQTqX3nHYJlZbGOIyKiwlpEOgffN/Ow\ngQDJ+2hOZ/lR1umnQSBA1b9einUUEREV1iLSOTTOmgUOB8l77x3rKBJHEvr2xXvgAVT960Vsc3Os\n44hIN6fCWkQ6hcbZs/EMHowzLS3WUSTOZE2cSKisnNp3NfWeiMSWCmsRiXvhpiZ8X3+t8dWyWd4x\nY0jo04eqZzX1nojElgprEYl7/nnzsM3NJO+rwlp+asPUe75vvsE3f36s44hIN6bCWkTiXsPs2WCM\nxlfLFqWfeAKO5GT1WotITKmwFpG41zhrNomDBuHMyIh1FIlTzpQU0k84gdr/vU2wvDzWcUSkm1Jh\nLSJxLdzcrPHV0iaZE0/HhkJUPPZ4rKOISDelwlpE4lr9tGlYv1/jq2WrEvv1I/3446l64QUCa9bE\nOo6IdEMqrEUkbjXMnMmaK6/CM2QIKWPGxDqOdAK5F10I1lL20EOxjiIi3ZAKaxGJS41ffsnqCy4k\noU8fej/xOI6kpFhHkk7A3bMnmadNoObf/6Fp2bJYxxGRbkaFtYjEHd/8b1l9zrm48/IoevIJXJmZ\nsY4knUj2uefi8Hgou/+BWEcRkW5GhbWIxBX/94tZPXkyzvR0ip56EldubqwjSSfjysoi66yzqHv3\nXXzzv411HBHpRlRYi0jc8C9ezKpJkzAeD0VPP4W7oCDWkaSTyjrrTJwZGZTde2+so4hIN6LCWkTi\nQt20aawcPwEchqKnniKhd+9YR5JOzJmSQvZ559Lw2Wc0zJwZ6zgi0k2osBaRmLLhMGUPP0zxhReR\n0L8//V5+mcT+/WIdS7qAzAkTcBUUUHrPvVhrYx1HRLoBFdYiEjPhhgZKLvs95Q88SNq4Y+nz7D9x\n9+gR61jSRTgSE8m96EL88+ZR++ZbsY4jIt2ACmsRiYlASQkrJpxG3dSp5F15JT3vuAOHxxPrWNLF\npB93HEl77snaG2+kacmSWMcRkS5OhbWIdDhrLSVXXklg7Vp6PzaF7LPOxBgT61jSBRmXi14PPIDD\nm0zxRRcTqq2NdSQR6cJ2qLA2xqwwxsw3xnxtjJkTXZZljHnfGLMkep/ZavurjTFLjTHfG2OObLV8\n7+hxlhpjHjD6F1akS2uYMQPfnLnkXf57UvbfP9ZxpItz5+dReP/9NJeUsOaPf8KGw7GOJCJdVHv0\nWB9irR1urR0RfX4VMM1aOxCYFn2OMWYIMB4YChwFPGyMcUb3eQQ4GxgYvR3VDrlEJA7ZcJjSe+7F\nXVRExsknxzqOdBPJv/gF+ddcTf1HH1H+N13uXER2jp0xFOQ44Jno42eA41stf9Fa22StXQ4sBfY1\nxhQAadbamTZy2vY/Wu0jIl1M7Ztv0vT99+ReegnG7Y51HOlGMidMIP3EEyl/+GHqpk2LdRwR6YJ2\ntLC2wFRjzFxjzDnRZfnW2rXRx+uA/OjjXsDqVvsWR5f1ij7edLmIdDHh5mbK7n+AxCG7kfbLX8Y6\njnQzxhh63HgDnt13Z82frqTphx9iHUlEupgdLazHWGuHA78ELjTGHNh6ZbQHut0mDzXGnGOMmWOM\nmVNWVtZehxWRDlL94r8IlJSQd/kfMA6dOy0dz5GYSOGDD2A8HladeRb+xYtjHUlEupAd+pfNWlsS\nvS8F/g3sC6yPDu8gel8a3bwEaH0ptcLospLo402Xb+71plhrR1hrR+Tm5u5IdBHpYKH6BsoffZTk\nUaPw7j861nGkG3MXFNDn6acAWPWb3+KbPz/GiUSkq9juwtoY4zXGpG54DBwBfAu8AZwR3ewM4PXo\n4zeA8caYRGNMPyInKc6KDhupNcaMis4G8ttW+4hIF1H51FOEKivJ+8PlmlpPYi5x4ED6PP8cjtRU\nVp1xJg1fzIp1JBHpAnakxzof+MQY8w0wC3jLWvsOcDtwuDFmCXBY9DnW2gXAS8BC4B3gQmttKHqs\nC4DHiZzQ+APw9g7kEpE4E6yooPKpp0g98kiShg2LdRwRABJ696bPc8/i6lnA6rPPpm769FhHEpFO\nzkSGQXc+I0aMsHPmzIl1DBFpg3W3/pmqF1+k/3//S2L/frGOI7KRYFUVq88+B/9335H/pz+R8etT\ndBVQEdmIMWZuq6mlt0hnD4nITtX41VdUPf88maeeqqJa4pIrM5Oip58ieZ8RrP/LX1h6yKGUPfAA\ngdLSre8sItKKeqxFZKcJNzWx/IQTCft99H/jvzhTvLGOJLJF1loav5hF5TPPUP/hh+BykX700WT+\n9jckDR0a63giEkNt7bF2dUQYEemeyv/2EM3LltH78cdVVEvcM8bgHTUS76iRNK9YQeWzz1H92mvU\nvP46ySNGkHnGb0k99FCM07n1g4lIt6ShICKyU/jmf0vFk0+SfvJJpIzZP9ZxRLZJQt++9LjuWgZ+\nOJ28K68ksGYNJRdfwg9HHkXlM88Qqq+PdUQRiUMaCiIi7S7c3MyKk04mVFtL/zf/izM1NdaRRHaI\nDQapm/YBlf/4B765czEeD97Ro0k99BBSDjoIl66tINKlaSiIiMRMxaOP0rRkCYWPPqKiWroE43KR\nduQRpB15BL7531Lz739T9+F06j/4AADPnnuQeuhYMk4+CVd2dozTikisqMdaRNqVf9Eilp/ya9J/\ndTQ977gj1nFEdhprLU2LF1M/fTp1H0zHP28eJiGB9OOPJ+usM0nsp1lwRLqKtvZYq7AWkXYTWF/K\nqt9NIlRTw4D//hdnRkasI4l0mKbly6l86mlq/vMfbCBAythDyZ70O5J/sVeso4nIDtI81iLSoZqW\nLGHFhPEE16yl1513qaiWbiexXz8KbrmZXT6YRvZ559I4ew4rTzuNdbfcig0EYh1PRDqACmsR2WEN\nX8xixWmnYwMB+jz7T7yjRsY6kkjMuHJyyLv0UgZ+MI2sM8+k6vnnWXX2OQSrqmIdTUR2MhXWIrJD\nat58i9WTJ+PKy6Pfiy/iGTIk1pFE4oLD6yX/qispuO02fHPnsuLU8TQtXRrrWCKyE6mwFpHtYq2l\n/LHHWHPFFSTtuSd9n38Od69esY4lEncyTjieon88Q7ixkRWnjqdu+vRYRxKRnUSFtYhsMxsOU3r7\nHZTdfQ9pR/+S3k8+gTM9PdaxROJW8l570e/ll0jo04fiCy5k7c03E1izJtaxRKSdqbAWkW1iAwHW\nXn01lc88Q+bEifS86y4cCQmxjiUS99wFBfR57lkyxp9K9SuvsvTIo1h7/fU0r14d62gi0k403Z6I\ntFnY76fk95dTP306OZdcTM7552OMiXUskU4nsGYNFY8/QfUrr2BDIdKPOYaciy8iobAw1tFEZDM0\n3Z6ItKtQXR2rJk+m/sMP6XHjDeRecIGKapHt5O7Zkx43XM+A998na+JEat99l+XHn0DdtGmxjiYi\nO0CFtYhsVbCsjJW/+S2+b+bR6+67yJwwIdaRRLoEd34e+VdfRf8334yMv77wIkrvvQ8bCsU6mohs\nBxXWIvKzmouLWXH6RJpXrqT3ww+TdvTRsY4k0uUkFPaiz/PPkXHKyVT8/e+sPvtsgpWVsY4lItvI\nFesAIhK//N8vZvXkyYSbm+nz1JMkDR8e60giXZYjMZGCW28lafhw1t18C8tPOpm8y3+PKycHR0oK\nDm8KjhQvrsxMjNsd67gishkqrEVksxq//IrV552Hw+Oh77P/JHHgwFhHEukWMk46icTBgym55FLW\n/PFPP1nvzMgg74o/kH7iiRiHvngWiSeaFUREfqJ+xgyKL7kUV34eRU88SUKhLvwi0tHCfj/Ny5cT\nrq8nVF9PuL6BcH0dNW++hW/uXJKGD6fHTTfiGTw41lFFury2zgqiwlpENtIw8wtWTZ5M4q4DKZoy\nBVdOTqwjiUgr1lpq/vM6pX/9K6HaWrImnk7OxRfjTEmJdTSRLkuFtYhss7Dfz7Jxx2GMoe8rL+NM\nTY11JBHZglB1NaX33Uf1v17CmZFBysEHk3LgAXhHj9aVUEXaWVsLa42xFpEW5Q8/QmDVKoqeflpF\ntUicc2ZkUHDTTWSceCIVTz1F3bRp1Pz73+BwkDR8ON4x+5M8YgRJw4bhSEqKdVyRbkGFtYgAkRlA\nKp58kvQTTsA7amSs44hIGyXtsQeF996LDQbxzZtP/cczaPj4E8ofeDCygdOJZ/BgkoYPJ2n4cNw9\n8nGkpeFMTcWRloYjOVknQYq0Ew0FERFsOMzKCafRvGoV/f/3Fq7MzFhHEpEdFKquxvfNNzR+9RW+\nr77GN38+trHxpxs6naQccjB5f/gDif36dXxQkU5AQ0FEpM2qXnwR3zff0POvd6ioFukinBkZpBx0\nECkHHQSADQZp+mEZoapKQjW1hOtqCdXWEVy/juqXX2HZh+PIOv00cs4/H2dGRozTi3RO6rEW6eYC\n69ez7FfHkLTHHvR+4nGMMbGOJCIdLFhWRtmDf6P6lVdwpKaSe+EFZIwfjyMhIdbRROKCZgURkTYp\nvvgS6mfMoP9/3yChqCjWcUQkhvzfL6b0jjto+OwzcDhwFxSQ0KcId+8iEop64y4owJmVhTMzE2dG\nBs7MTBXf0i1oKIiIbFHY56NxzlzqPphG3fvvk/v736uoFhE8g3al9xOP0/j55zTOmUPzqtU0r1qF\n/913CVVXb3YfR0oKrh75uHsU/Hifm4txucDhwDgMOBzgcODwenGmpeFISWm5Jxgk7PcT9vmwfj9h\nnx9nagrunj1xeL075X3acBjb3IzD49kpx/85odpagqWlkc8iPR2TlPSz3xRaawlVVtK8YkXLDWtx\n9eyJu+XWC2fK9n1W1lqs349JTNRJrO1AhbVINxBubKRp8WIa535Jw6ef0DhnLra5GZOQQOovjyJ7\n0lmxjigiccIYg3f0aLyjR2+0PFRbS2DdOkLV1YSqqqP3VQTLywmuX0dg7Tr8331HqLy83bI409Nx\n9YoUj06vl3BTM7apCdvkjzwOBMDajW6W6Dfxlh+Xh8OEfT7CjY2RAt7nixw/M5PEAQNIGLgLiQN2\nIXFAfxxJSdhgMHILBLHBAMadgMObjDMlBYfXG/mDwFpCNTWRz6GmhlB1DeGGemxzABsIRPcPEG5o\nIFBSQqC4mOaSEsI1NRt/3gkJkd7/9HRwOjd+LzZMcH0p4bq6H3dwuyP3gcBGx3F4vZFvE7IycWVk\n4szKwuH1Rj6v5ibC/qbIHy5+P+G6OkJ1dYRrawnV1UE4DA4HzrQ0nOnpODLScaan40zPiN5Hbxk/\nPnakp0dyp6aCw0G4oSF63HrCDfU/Pq6PvlZ9A7a5OXqcjB+/9UhPi7zXUBjCIWwoBOEwxuWKFPsJ\nCZGbOyGyvrkZ29xMOHofLC8nsLqY5tWrCKwuJrB6dcsfga3HZBiXC1dWFs7sbFxZmTizsnFmZuBI\nSsaR5MF4knB4EjGJiZEMrf8fCAXb/P+shoKIdDFhnw/fV1/h+3YBTd8twr/ou5YeDoDEgQPx7r8/\n3v33J3nE3prfVkTaVbi5mVBlJYRC2GhRSziMDQYJNzREiq262pZiy7icGI/nxwIn0UOotobAmjWR\ngnTNGgJr1mAbfRiPB5OYiCMxMfLY5QJjwADGYDDR59Ee4Ohj4zCYpCQcycmR10lOxrjdBEqKaVr6\nA01Ll25cvLYjk5CAu1cv3IWFJPQuxN2rEFd+PmFfY6Qo33CrqYGwbXk/kV5sgys3h4S+/Ujo15eE\nvn1xFxSAw0GwrJzAmsjnE1y7lsD6UkJVVYQqKwlWVRGqqiLc0IDxJOJI9LS690SnWkzFmZqGIy0V\nR3Jy5I+O6B8IoZqNb+Ha2q28SdPyb8wWORwYtxvb1NReH+3Gh09PJ6GwEHdRb1yZWRv/PwDY5mZC\nVZUEKyoJVVQQrKzcpjYf8v13nWsoiDHmKOB+wAk8bq29PcaRRDqFsM+H7+uvaZg1i8ZZs/HNm9fS\nk+EuLMSz22DSjvkVnsGD8ew+DHd+XowTi0hX5khIwNGjR6xjbBNrLcGyMpqXLcMGApGC3enEuNwY\nt6ul5zlcXx/546C+HmMMzoyMSM9ttHfXkeLFuN0YdwImwR3pdd1Jwyvc+XmR3+d77bVTjt+aDYUI\n1dZGCu/Wt+pIjz02jCMlFUdqSqRoT0nFmeLF0eqxSU7GGEO4qanl245QdTWh2trIHz9OZ6T4drrA\nYSJDhJqbsU3NLb3UOB04Wnqw3ZHe/swsEop6b9fVRm0gQLipCevztbpvxjgdkf8HXK7I67hcUFDQ\npmPGRY+1McYJLAYOB4qB2cAEa+3CLe2jHmvpasJNTZFf2vX10a/SGrBN/shXXk1Nka8X/T4C69YT\nKC4mUFJCc0kxobLo165OJ56hQ/Huuw/JI0eStOeeONPSYvumREREuoDOdvLivsBSa+0yAGPMi8Bx\nwBYLa5FN+RYsiHyt6DCRnoboyTIYB9BqDB5Ex67Z6ACsH5d7Bg/+2ZNlbDhM/YcfbnSSTdjXiPX5\nI2OyWl4jcjwb/HE8mG1uxgaaCfubImPPGuoJ19W3FNN2k/FyW+R04i4owF1YSMqBB+Lu1YukoUNJ\n2ntvnCkp2/35iYiIyI6Jl8K6F7C61fNiQNdUlm2y/rbb8M2Zu0PH6PvqKyQNHfqz2xRfcOHmV7ii\nP07GYKL3OJ3REy/cONzRr688HpwpKbjz8nH0HxD56iwlBYc35cfHG55HT6QwCQkt966srMjXUiIi\nIhJXOtW/zsaYc4BzAIo0NZhsose11xKqrYueVRwGG46eXWx/PLFl05NaWk50iZwoktCnz8++hnE4\n6Pfaq5ETbTyeyMkw0ZNpNE2RiIhI9xYvhXUJ0LvV88Loso1Ya6cAUyAyxrpjokln4dltt455nSFD\nOuR1REREpHOJly622cBAY0w/Y0wCMB54I8aZRERERETaLC56rK21QWPMRcC7RKbbe9JauyDGsURE\nRERE2iwuptvbHsYYH6DiOz4VAatiHUI2S20Tv9Q28UttE7/UNvGrq7VNH2tt7tY26syFdVlb3qB0\nPLVN/FLbxC+1TfxS28QvtU386q5tEy9jrLdHdawDyBapbeKX2iZ+qW3il9omfqlt4le3bJvOXFjX\nxDqAbJHaJn6pbeKX2iZ+qW3il9omfnXLtunMhfWUWAeQLVLbxC+1TfxS28QvtU38UtvEr27ZNp12\njLWIiIiISDzpzD3WIiIiIiJxQ4W1iIiIiGwzY4yJdYZ4E/eFtRotfqlt4pfaJn6pbeKX2iZ+qW3i\nljvWAeJNXBbWxpihxpiDAawGgccVtU38UtvEL7VN/FLbxC+1TfwyxuxnjHkZuMsYM8QY44x1pngR\nVycvGmMcwN+AQ4lcrecL4HVr7RxjjMNaG45pwG5MbRO/1DbxS20Tv9Q28UttE9+MMXnA20TaqDfQ\nC5hjrX3MGGO6+x9B8dZjnQmkWGsHA6cDFcAfjDEp+kGKuQzUNvFKbRO/9Dstfqlt4pfaJr7tCXxv\nrX0KuBt4DTjOGLOrtdZ292E7MS+sjTG/MMbsGn2aDuxvjPFaa8uAV4Eq4KLott26sTqaMaa/MSY5\n+jQbGK22iQ/GmD7GGE/0qdomjhhjxhhjdok+zUBtEzeMMScbYy6IPk1DbRM3VAvEL2PMBGPMzcaY\ncdFFXwH7GGMGWGsbgNnAHOBc0LCdmBXWxph+xpi3gIeAfxpjDrfWLgM+Ay6LbraWyA/UcGNMQXdv\nrI5ijCkwxswAngVeN8YMs9YuAT4CLo9upraJgehYtv8ATwNvGGMGRdtmJvq5iTljzHBgBjDBGJNm\nrf0B+By1TUwZY1KMMa8CVwBVxhiXtXY58Clqm5hSLRC/TMR5wJ+AFcCdxpjJQD3wT+DS6KbVwFQg\n2RhTEIus8SSWPdZXAF9ba/cDXgcmRZc/SeQv1X7W2iCwHvADyZs/jLSHTXoATgVmW2tHA9OAq4wx\nvyBSzI0yxvRX23ScDW1jjBkMPAJMt9YeAswnMsYN4An0c9PhNtNz1hN4H3ACB0WX6XdaDGzSNr2B\n9dbaUdbaF4BQdPnTRNpGv9M60CZto1ogTkX/gNkPuD067ONC4GBgLPAmMMAYc1h0eE4FkbHW3fIy\n5q11aGFtjOlhjNkwNYsPCEQfpwGLol+ffgLMAu4CsNZ+C/QBmjoyazfk2eSxG8BaeztQSuQHaT2R\nk0jujK5T23SMDW1TA1xlrb0/+vwWIj0EuUS+ivsS+CuobTqQZ5Pn1cASIoXbPsaYJGvtdCLto99p\nHat12+wBFAJEh4LcaIwZAywg0muttulYHmgpsBtQLRA3jDG/NcYcZIzJii5aBPSKfsszFfiWSLFd\nDrwA3Bdtr7GAARJikTuedEhhbYwZa4z5mMhXPQ9EF38M7GKM+Qo4ikgPz/NE/hq6HehhjHnQGPMt\nsBKo0biq9meMOdwY8z6Rr3jGRxcvByqMMUXR5y8Cw4iMe7sN6Km22fk2aZtfW2vXWms/b/VZDwP8\n1toya209kUK7l9pm52vVNn9t9XMDkTb5EphCpHi4xhhzCpGfmwK1zc63SdtMiC7+ElhrjHny/9u7\n/1ir6zqO48/XFNfCtEWh1rSoXEquJIRiSfZDU/9K1EzMUimNWqjTNKu1ppmKqdkonUo/ra01G9HS\nmYoasSk6JHGNmBSOH0kqhUqIIr364/Mhrwh6r3zPOd977+ux3e2ec88593P22vd73ufzfX++X0pR\nsB74BnAM8D3gTZJ+kGw6azv7NFMK6P1TC/RObfnYR9JdwCmUBaOzJO0BrAJGA1vXjfwKeDcwyvYv\nKC2jF1COdJ9ve33X30DL7Nrpf6CyGOESyiznfODnkibbnls3lO/aPrY+9nngE7Zvl3Qs8A7gdtu/\n6/Q4h6P6LfNiSj4rgfMkvZHSy3YU8B5Jq2wvlPRF4Gjb90uaArydZNMx28nmXEnvtH0JZbvdTDkk\nunTrc2w/J+kYyg4w2XTIy2RzMaUXdA9gJHAkMAb4su1NdZ+W7aaDtpPNVyS9Gfg+pS/0MGCS7c2S\n1gGTbV8v6TjKdnNbsumMHXze7Gf7CknLgEtTC3SfpF1sb5H0OmCN7ZNVzkk9q/58nnLawwmSHrX9\niKQngeOBxbYvk7Sb7ed69y7apSOFtco5KKl9NwcD99m+qX772QCskLRb/X2VpANtLwXuAs6WJNv/\npLQeRIO2yeb9wCLbc+vf5lFOnfMzSsvHoZSM7qb0U32wPnctsLbbYx/qXiGbO4GrJM22/Vh9ykcp\nixaR9E3gJ7ZXU1p3okH9zOZaYG/gdOBbwM3AbZR2nV2y3XRGP7K5krIGYS4wDjgB+CXwIHCcynmR\nHyPbTeNeIZs7KNvNjcC/SC3QVbV4/jawi6RbKBMCWwBqoT2DMlEwlnIEYQqlnepS4L+UxaXUx6eo\n7qPxVhBJpwGrKYEBLAHGS7qBsthqNDATuIbSozMKOFPSWcB1lJWl0QHbyeYh4ERJY+rtXSkrf2dS\nDmWvAa6UdAFwNaXAjg7oRzYjgL9R+w3rodBDKIt7/ggcQDkdVTSsn9msoBTTN1H2YZNsn03pR3ya\n0nsYDevnPm0FcLnt+ZSZ63MkfZVySHtBfZ3k07B+bjd/r39/GngDqQW6QtJhwCLK+cKXUzLYDHxE\n0kQoxTVwITDT9jxKTXCopIX1eXf3YOiDQqNXXpS0O6XfZmufzlTby1QWV50KbLB9rcr5d9dQDss9\nRfkm9D7gWtv3Njag+L/tZHOS7b9KuhrYC9iP8gE0s/6cYvtxSUcDE4A7bS/ozeiHtgFmcxlwBvAP\nyo5xPXCu7cW9GPtQN8BsLgc+Y/uJPs8fYXvzS185dtar2KdNs71W0gTK580S2/f0ZvRD26vYbo6v\n9x1OmTBILdBBkiYDb7N9Y719DeWLzzPADNvj69GG0ZR2kPNqC8jrgZG21/Rq7INB45c0rz1TKyVd\nBrzV9tQa0A3AT23/qT7uh8DNtm9pdACxQ9tkM8b2p+rhoD2BsbYXSNqX8u11uu1NPR3wMDLAbD5H\nme0Za/uBHg57WBhANhdRtptnlcsud0X2ae01gGwuBk5PO0H3qFz4bQvwfG37+DRwkO2vSfoz8CPb\nsyQdQpm4mfqyLxgv0ngriO2V9derKec4PLp+wCwHrpf0Lklfp/TrLt3R60TztslmjKQj6+GeJ/vM\nRk8HNvLC6Y+iCwaYjWxvSlHdHQPI5hng+fqcFNVdkH1aew0gm//wwnnFowtsb7T9bM0D4Ajg8fr7\nacCBkn5POZ1ePmcGqPEZ6xe9uPQF4GTbk+vtK4B9KAX9+bZXdeyfx8uq2Zxk+7B6eyLl9FMjqIdM\nezm+4SzZtFeyaa9k017Jpp3qEQRTFlrPsL1c5ewtTwAHASvS9jFwHSus7YQ2TAAAApBJREFUtx4K\nlXQTZbX1RuDXwEO2n+nIP41+2SabRykn3L8DeNjlEszRI8mmvZJNeyWb9ko27VUX7e4GzAbmUK56\nuY5SZD/Vy7ENZh27QEzdkF5LaX4/AVhp+74U1b23TTZTKdncmp1c7yWb9ko27ZVs2ivZtJfLzOo4\nygVhzgHm2D4lRfXO6fQFYr5E6c85wnYuQ9ouyaa9kk17JZv2SjbtlWzaazWlLeeqZNOMTvdYZ2V8\nSyWb9ko27ZVs2ivZtFeyieGko4V1RERERMRw0bEe64iIiIiI4SSFdUREREREA1JYR0REREQ0IIV1\nREREREQDUlhHRERERDQghXVERLxEvdxxREQMQArriIhBTtJFks7uc/s7ks6SdJ6k+yUtkXRhn7//\nVtIiSX+RdEaf+zdIulLSg8CkLr+NiIhBL4V1RMTg92Pgs1AuxgGcCKwF9gcmAgcD4yV9qD5+mu3x\nwCHAmZJG1ftHAgttv9f2gm6+gYiIoaDTlzSPiIgOs/2IpHWSxgF7AYuBCcDH6+8Au1MK7fmUYnpK\nvX/fev86YAvwm26OPSJiKElhHRExNMwGTgX2psxgfwy41PZ1fR8k6cPA4cAk2xsl3Q28pv55k+0t\n3RpwRMRQk1aQiIihYQ5wFGWm+g/1Z5qk3QEkvUXSaGBP4N+1qD4A+ECvBhwRMdRkxjoiYgiw/Zyk\nu4D1ddb5NkkHAvdIAtgAnAzcCkyXtBRYBtzbqzFHRAw1st3rMURExE6qixYfAD5p++FejyciYjhK\nK0hExCAnaSywHJiXojoioncyYx0RERER0YDMWEdERERENCCFdUREREREA1JYR0REREQ0IIV1RERE\nREQDUlhHRERERDQghXVERERERAP+BxLMesWQDXFMAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x15aa0a58>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "subset = total_births[['John', 'Harry', 'Mary', 'Marilyn']]\n",
    "subset.plot(subplots=True, figsize=(12,10), grid=False, title='Number of births per year')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 评估命名多样性的增长"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 149,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "table = top1000.pivot_table('prop', index='year', columns='sex', aggfunc=sum)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 152,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x1cd111d0>"
      ]
     },
     "execution_count": 152,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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P8N7zvi+E0bP9UcFRf3ewvUABQESkHesLK/nvN7bz6Dt7qG+Kc8KMUXz25Oks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\nohQARERSlAKAiEiK+v/KIFxqJD/QsQAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1cd110b8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "table.plot(title='Sum of the table1000.prop by year and sex', yticks=np.linspace(0,1.2,13), xticks=range(1880, 2020, 10))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 求前面多少个名字的人数加起来才够50%"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 158,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "df = boys[boys.year == 2010]\n",
    "df\n",
    "# 先计算prop的累计和cumsum，然后通过searchsorted方法找出0.3应该被插入在哪个位置才能保证不破坏顺序\n",
    "prop_cumsum = df.sort_values(by='prop', ascending=False).prop.cumsum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 159,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "260877    0.011523\n",
       "260878    0.020934\n",
       "260879    0.029959\n",
       "260880    0.038930\n",
       "260881    0.047817\n",
       "260882    0.056579\n",
       "260883    0.065155\n",
       "260884    0.073414\n",
       "260885    0.081528\n",
       "260886    0.089621\n",
       "Name: prop, dtype: float64"
      ]
     },
     "execution_count": 159,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "prop_cumsum[0:10]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 160,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([116], dtype=int64)"
      ]
     },
     "execution_count": 160,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "prop_cumsum.searchsorted(0.5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 161,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# 由于书序索引是从0开始的，因为我们要给结果加1， 即最终结果为117\n",
    "# 拿1990年的数据来比较，这个数字要小得多：\n",
    "df = boys[boys.year == 1900] "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 174,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "in1990 = df.sort_values(by='prop', ascending=False).prop.cumsum()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 173,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([25], dtype=int64)"
      ]
     },
     "execution_count": 173,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "in1990.searchsorted(0.5) + 1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 185,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "year  sex\n",
       "1880  F       38\n",
       "      M       14\n",
       "1881  F       38\n",
       "      M       14\n",
       "1882  F       38\n",
       "      M       15\n",
       "1883  F       39\n",
       "      M       15\n",
       "1884  F       39\n",
       "      M       16\n",
       "1885  F       40\n",
       "      M       16\n",
       "1886  F       41\n",
       "      M       16\n",
       "1887  F       41\n",
       "      M       17\n",
       "1888  F       42\n",
       "      M       17\n",
       "1889  F       43\n",
       "      M       18\n",
       "1890  F       44\n",
       "      M       19\n",
       "1891  F       44\n",
       "      M       20\n",
       "1892  F       44\n",
       "      M       20\n",
       "1893  F       44\n",
       "      M       21\n",
       "1894  F       45\n",
       "      M       22\n",
       "            ... \n",
       "1996  F      122\n",
       "      M       64\n",
       "1997  F      129\n",
       "      M       67\n",
       "1998  F      138\n",
       "      M       70\n",
       "1999  F      146\n",
       "      M       73\n",
       "2000  F      155\n",
       "      M       77\n",
       "2001  F      164\n",
       "      M       81\n",
       "2002  F      170\n",
       "      M       83\n",
       "2003  F      178\n",
       "      M       87\n",
       "2004  F      191\n",
       "      M       92\n",
       "2005  F      199\n",
       "      M       96\n",
       "2006  F      209\n",
       "      M       99\n",
       "2007  F      223\n",
       "      M      103\n",
       "2008  F      234\n",
       "      M      109\n",
       "2009  F      241\n",
       "      M      114\n",
       "2010  F      246\n",
       "      M      117\n",
       "dtype: int64"
      ]
     },
     "execution_count": 185,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "def get_quantile_count(group, q=0.5):\n",
    "    group = group.sort_values(by='prop', ascending=False)\n",
    "    return (group.prop.cumsum().searchsorted(q) + 1)[0]\n",
    "# 上面函数返回值需要加括号并取值，不然返回的是一个单值列表\n",
    "diversity = top1000.groupby(['year', 'sex']).apply(get_quantile_count)\n",
    "diversity"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 186,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th>sex</th>\n",
       "      <th>F</th>\n",
       "      <th>M</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>year</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1880</th>\n",
       "      <td>38</td>\n",
       "      <td>14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1881</th>\n",
       "      <td>38</td>\n",
       "      <td>14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1882</th>\n",
       "      <td>38</td>\n",
       "      <td>15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1883</th>\n",
       "      <td>39</td>\n",
       "      <td>15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1884</th>\n",
       "      <td>39</td>\n",
       "      <td>16</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "sex    F   M\n",
       "year        \n",
       "1880  38  14\n",
       "1881  38  14\n",
       "1882  38  15\n",
       "1883  39  15\n",
       "1884  39  16"
      ]
     },
     "execution_count": 186,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "diversity = diversity.unstack('sex')\n",
    "diversity.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 188,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x2048eac8>"
      ]
     },
     "execution_count": 188,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
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JXinl9zbsP8LGA0Xcek4SAQE+nIbYGFhyP7gq4fI/tei2gC2hiV4p5fde+2Yv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\nAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x204a2390>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "diversity.plot(title='Number of popular names in top 50%')  \n",
    "# diversity"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 最后一个字母的变革"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 190,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "# 将全部出生数据在年度、性别以及末字母上进行聚合\n",
    "# 从name列取出最后一个字母\n",
    "get_last_letter = lambda x:x[-1]\n",
    "last_letters = names.name.map(get_last_letter)\n",
    "last_letters.name = 'last_letter'\n",
    "\n",
    "table = names.pivot_table('births', index=last_letters, columns=['sex', 'year'], aggfunc=sum)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 191,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# 选出具有代表性的三年，并输出前几行\n",
    "subtable = table.reindex(columns=[1910, 1960, 2010], level='year')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 192,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr>\n",
       "      <th>sex</th>\n",
       "      <th colspan=\"3\" halign=\"left\">F</th>\n",
       "      <th colspan=\"3\" halign=\"left\">M</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>year</th>\n",
       "      <th>1910</th>\n",
       "      <th>1960</th>\n",
       "      <th>2010</th>\n",
       "      <th>1910</th>\n",
       "      <th>1960</th>\n",
       "      <th>2010</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>last_letter</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>a</th>\n",
       "      <td>108376.0</td>\n",
       "      <td>691247.0</td>\n",
       "      <td>670605.0</td>\n",
       "      <td>977.0</td>\n",
       "      <td>5204.0</td>\n",
       "      <td>28438.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>b</th>\n",
       "      <td>NaN</td>\n",
       "      <td>694.0</td>\n",
       "      <td>450.0</td>\n",
       "      <td>411.0</td>\n",
       "      <td>3912.0</td>\n",
       "      <td>38859.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>c</th>\n",
       "      <td>5.0</td>\n",
       "      <td>49.0</td>\n",
       "      <td>946.0</td>\n",
       "      <td>482.0</td>\n",
       "      <td>15476.0</td>\n",
       "      <td>23125.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>d</th>\n",
       "      <td>6750.0</td>\n",
       "      <td>3729.0</td>\n",
       "      <td>2607.0</td>\n",
       "      <td>22111.0</td>\n",
       "      <td>262112.0</td>\n",
       "      <td>44398.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>e</th>\n",
       "      <td>133569.0</td>\n",
       "      <td>435013.0</td>\n",
       "      <td>313833.0</td>\n",
       "      <td>28655.0</td>\n",
       "      <td>178823.0</td>\n",
       "      <td>129012.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "sex                 F                            M                    \n",
       "year             1910      1960      2010     1910      1960      2010\n",
       "last_letter                                                           \n",
       "a            108376.0  691247.0  670605.0    977.0    5204.0   28438.0\n",
       "b                 NaN     694.0     450.0    411.0    3912.0   38859.0\n",
       "c                 5.0      49.0     946.0    482.0   15476.0   23125.0\n",
       "d              6750.0    3729.0    2607.0  22111.0  262112.0   44398.0\n",
       "e            133569.0  435013.0  313833.0  28655.0  178823.0  129012.0"
      ]
     },
     "execution_count": 192,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "subtable.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 193,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "sex  year\n",
       "F    1910     396416.0\n",
       "     1960    2022062.0\n",
       "     2010    1759010.0\n",
       "M    1910     194198.0\n",
       "     1960    2132588.0\n",
       "     2010    1898382.0\n",
       "dtype: float64"
      ]
     },
     "execution_count": 193,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 按出生数对表进行规范化处理，以便计算各性别各末字母占总出生人数的比例\n",
    "subtable.sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 194,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "letter_prop = subtable / subtable.sum().astype(float)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 196,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "import matplotlib.pyplot as ply"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 197,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x20b87630>"
      ]
     },
     "execution_count": 197,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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N/OhHP2L+/Pn87Gc/46CDDgLgZS97GT/72c+et+/g4CDTp0/fVp4+fTqDg4M9j9GkS5Ik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\nQJKuiIiIiB5I0hURERHRA/8Ff7DF9nVn2RkAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x204a2e48>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, axes = plt.subplots(2, 1, figsize=(10,8))\n",
    "letter_prop['M'].plot(kind='bar', rot=0, ax =axes[0], title='Male')\n",
    "letter_prop['F'].plot(kind='bar', rot=0, ax =axes[1], title='Female', legend=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 198,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "letter_prop = table /table.sum().astype(float)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 199,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "dny_ts = letter_prop.ix[['d', 'n', 'y'], 'M'].T"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 200,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th>last_letter</th>\n",
       "      <th>d</th>\n",
       "      <th>n</th>\n",
       "      <th>y</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>year</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1880</th>\n",
       "      <td>0.083055</td>\n",
       "      <td>0.153213</td>\n",
       "      <td>0.075760</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1881</th>\n",
       "      <td>0.083247</td>\n",
       "      <td>0.153214</td>\n",
       "      <td>0.077451</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1882</th>\n",
       "      <td>0.085340</td>\n",
       "      <td>0.149560</td>\n",
       "      <td>0.077537</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1883</th>\n",
       "      <td>0.084066</td>\n",
       "      <td>0.151646</td>\n",
       "      <td>0.079144</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1884</th>\n",
       "      <td>0.086120</td>\n",
       "      <td>0.149915</td>\n",
       "      <td>0.080405</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "last_letter         d         n         y\n",
       "year                                     \n",
       "1880         0.083055  0.153213  0.075760\n",
       "1881         0.083247  0.153214  0.077451\n",
       "1882         0.085340  0.149560  0.077537\n",
       "1883         0.084066  0.151646  0.079144\n",
       "1884         0.086120  0.149915  0.080405"
      ]
     },
     "execution_count": 200,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dny_ts.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 201,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x21305160>"
      ]
     },
     "execution_count": 201,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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O/Q6nt2mJwr81uLhrCV1fcuVr+zXXBv6kH4D80zBorpZoACqLISteK30GtoOu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\nAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x21315470>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "dny_ts.plot()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "###  变成女孩名字的男孩名字（以及相反的情况）"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 202,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# 找出以lesl开头的一组名字：\n",
    "all_names= top1000.name.unique()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 203,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "mask = np.array(['lesl' in x.lower() for x in all_names])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 205,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "lesley_like = all_names[mask]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 207,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array(['Leslie', 'Lesley', 'Leslee', 'Lesli', 'Lesly'], dtype=object)"
      ]
     },
     "execution_count": 207,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "lesley_like"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 208,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# 利用这个结果过滤其他的名字，并按名字分子计算出生数以查看相对频率：\n",
    "filtered = top1000[top1000.name.isin(lesley_like)]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 209,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "name\n",
       "Leslee      1082\n",
       "Lesley     35022\n",
       "Lesli        929\n",
       "Leslie    370429\n",
       "Lesly      10067\n",
       "Name: births, dtype: int64"
      ]
     },
     "execution_count": 209,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "filtered.groupby('name').births.sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 210,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# 按性别和年度进行聚合，并按年度进行规范化处理\n",
    "table = filtered.pivot_table('births', index='year', columns='sex', aggfunc='sum')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 211,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "table = table.div(table.sum(1), axis = 0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 212,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th>sex</th>\n",
       "      <th>F</th>\n",
       "      <th>M</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>year</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2006</th>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2007</th>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2008</th>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2009</th>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2010</th>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "sex     F   M\n",
       "year         \n",
       "2006  1.0 NaN\n",
       "2007  1.0 NaN\n",
       "2008  1.0 NaN\n",
       "2009  1.0 NaN\n",
       "2010  1.0 NaN"
      ]
     },
     "execution_count": 212,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "table.tail()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 213,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x2123d748>"
      ]
     },
     "execution_count": 213,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
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e8tWrV/nhhx+ydOnSrFy5suGAK1E0hgwZQgBMTEw07DT9559/SKb9mnV1dWWVKlWk925k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\nuQshhBmS5C6EEGbo/wFPS4RtMYJ8KwAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x204cb048>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "table.plot(style={'M':'k-',  'F':'k--'})"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 结束"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 2",
   "language": "python",
   "name": "python2"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 2
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython2",
   "version": "2.7.13"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}