code/python-day-2.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "    .dataframe tbody tr th:only-of-type {\n",
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       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>country</th>\n",
       "      <th>gdpPercap_1952</th>\n",
       "      <th>gdpPercap_1957</th>\n",
       "      <th>gdpPercap_1962</th>\n",
       "      <th>gdpPercap_1967</th>\n",
       "      <th>gdpPercap_1972</th>\n",
       "      <th>gdpPercap_1977</th>\n",
       "      <th>gdpPercap_1982</th>\n",
       "      <th>gdpPercap_1987</th>\n",
       "      <th>gdpPercap_1992</th>\n",
       "      <th>gdpPercap_1997</th>\n",
       "      <th>gdpPercap_2002</th>\n",
       "      <th>gdpPercap_2007</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Australia</td>\n",
       "      <td>10039.59564</td>\n",
       "      <td>10949.64959</td>\n",
       "      <td>12217.22686</td>\n",
       "      <td>14526.12465</td>\n",
       "      <td>16788.62948</td>\n",
       "      <td>18334.19751</td>\n",
       "      <td>19477.00928</td>\n",
       "      <td>21888.88903</td>\n",
       "      <td>23424.76683</td>\n",
       "      <td>26997.93657</td>\n",
       "      <td>30687.75473</td>\n",
       "      <td>34435.36744</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>New Zealand</td>\n",
       "      <td>10556.57566</td>\n",
       "      <td>12247.39532</td>\n",
       "      <td>13175.67800</td>\n",
       "      <td>14463.91893</td>\n",
       "      <td>16046.03728</td>\n",
       "      <td>16233.71770</td>\n",
       "      <td>17632.41040</td>\n",
       "      <td>19007.19129</td>\n",
       "      <td>18363.32494</td>\n",
       "      <td>21050.41377</td>\n",
       "      <td>23189.80135</td>\n",
       "      <td>25185.00911</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       country  gdpPercap_1952  gdpPercap_1957  gdpPercap_1962  \\\n",
       "0    Australia     10039.59564     10949.64959     12217.22686   \n",
       "1  New Zealand     10556.57566     12247.39532     13175.67800   \n",
       "\n",
       "   gdpPercap_1967  gdpPercap_1972  gdpPercap_1977  gdpPercap_1982  \\\n",
       "0     14526.12465     16788.62948     18334.19751     19477.00928   \n",
       "1     14463.91893     16046.03728     16233.71770     17632.41040   \n",
       "\n",
       "   gdpPercap_1987  gdpPercap_1992  gdpPercap_1997  gdpPercap_2002  \\\n",
       "0     21888.88903     23424.76683     26997.93657     30687.75473   \n",
       "1     19007.19129     18363.32494     21050.41377     23189.80135   \n",
       "\n",
       "   gdpPercap_2007  \n",
       "0     34435.36744  \n",
       "1     25185.00911  "
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pd.read_csv('data/gapminder_gdp_oceania.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "       country  gdpPercap_1952  gdpPercap_1957  gdpPercap_1962  \\\n",
      "0    Australia     10039.59564     10949.64959     12217.22686   \n",
      "1  New Zealand     10556.57566     12247.39532     13175.67800   \n",
      "\n",
      "   gdpPercap_1967  gdpPercap_1972  gdpPercap_1977  gdpPercap_1982  \\\n",
      "0     14526.12465     16788.62948     18334.19751     19477.00928   \n",
      "1     14463.91893     16046.03728     16233.71770     17632.41040   \n",
      "\n",
      "   gdpPercap_1987  gdpPercap_1992  gdpPercap_1997  gdpPercap_2002  \\\n",
      "0     21888.88903     23424.76683     26997.93657     30687.75473   \n",
      "1     19007.19129     18363.32494     21050.41377     23189.80135   \n",
      "\n",
      "   gdpPercap_2007  \n",
      "0     34435.36744  \n",
      "1     25185.00911  \n"
     ]
    }
   ],
   "source": [
    "data = pd.read_csv('data/gapminder_gdp_oceania.csv')\n",
    "print(data)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['country', 'gdpPercap_1952', 'gdpPercap_1957', 'gdpPercap_1962',\n",
       "       'gdpPercap_1967', 'gdpPercap_1972', 'gdpPercap_1977', 'gdpPercap_1982',\n",
       "       'gdpPercap_1987', 'gdpPercap_1992', 'gdpPercap_1997', 'gdpPercap_2002',\n",
       "       'gdpPercap_2007'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 2 entries, 0 to 1\n",
      "Data columns (total 13 columns):\n",
      " #   Column          Non-Null Count  Dtype  \n",
      "---  ------          --------------  -----  \n",
      " 0   country         2 non-null      object \n",
      " 1   gdpPercap_1952  2 non-null      float64\n",
      " 2   gdpPercap_1957  2 non-null      float64\n",
      " 3   gdpPercap_1962  2 non-null      float64\n",
      " 4   gdpPercap_1967  2 non-null      float64\n",
      " 5   gdpPercap_1972  2 non-null      float64\n",
      " 6   gdpPercap_1977  2 non-null      float64\n",
      " 7   gdpPercap_1982  2 non-null      float64\n",
      " 8   gdpPercap_1987  2 non-null      float64\n",
      " 9   gdpPercap_1992  2 non-null      float64\n",
      " 10  gdpPercap_1997  2 non-null      float64\n",
      " 11  gdpPercap_2002  2 non-null      float64\n",
      " 12  gdpPercap_2007  2 non-null      float64\n",
      "dtypes: float64(12), object(1)\n",
      "memory usage: 336.0+ bytes\n"
     ]
    }
   ],
   "source": [
    "data.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>gdpPercap_1952</th>\n",
       "      <th>gdpPercap_1957</th>\n",
       "      <th>gdpPercap_1962</th>\n",
       "      <th>gdpPercap_1967</th>\n",
       "      <th>gdpPercap_1972</th>\n",
       "      <th>gdpPercap_1977</th>\n",
       "      <th>gdpPercap_1982</th>\n",
       "      <th>gdpPercap_1987</th>\n",
       "      <th>gdpPercap_1992</th>\n",
       "      <th>gdpPercap_1997</th>\n",
       "      <th>gdpPercap_2002</th>\n",
       "      <th>gdpPercap_2007</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>country</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></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>Australia</th>\n",
       "      <td>10039.59564</td>\n",
       "      <td>10949.64959</td>\n",
       "      <td>12217.22686</td>\n",
       "      <td>14526.12465</td>\n",
       "      <td>16788.62948</td>\n",
       "      <td>18334.19751</td>\n",
       "      <td>19477.00928</td>\n",
       "      <td>21888.88903</td>\n",
       "      <td>23424.76683</td>\n",
       "      <td>26997.93657</td>\n",
       "      <td>30687.75473</td>\n",
       "      <td>34435.36744</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>New Zealand</th>\n",
       "      <td>10556.57566</td>\n",
       "      <td>12247.39532</td>\n",
       "      <td>13175.67800</td>\n",
       "      <td>14463.91893</td>\n",
       "      <td>16046.03728</td>\n",
       "      <td>16233.71770</td>\n",
       "      <td>17632.41040</td>\n",
       "      <td>19007.19129</td>\n",
       "      <td>18363.32494</td>\n",
       "      <td>21050.41377</td>\n",
       "      <td>23189.80135</td>\n",
       "      <td>25185.00911</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "             gdpPercap_1952  gdpPercap_1957  gdpPercap_1962  gdpPercap_1967  \\\n",
       "country                                                                       \n",
       "Australia       10039.59564     10949.64959     12217.22686     14526.12465   \n",
       "New Zealand     10556.57566     12247.39532     13175.67800     14463.91893   \n",
       "\n",
       "             gdpPercap_1972  gdpPercap_1977  gdpPercap_1982  gdpPercap_1987  \\\n",
       "country                                                                       \n",
       "Australia       16788.62948     18334.19751     19477.00928     21888.88903   \n",
       "New Zealand     16046.03728     16233.71770     17632.41040     19007.19129   \n",
       "\n",
       "             gdpPercap_1992  gdpPercap_1997  gdpPercap_2002  gdpPercap_2007  \n",
       "country                                                                      \n",
       "Australia       23424.76683     26997.93657     30687.75473     34435.36744  \n",
       "New Zealand     18363.32494     21050.41377     23189.80135     25185.00911  "
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data = pd.read_csv('data/gapminder_gdp_oceania.csv',index_col='country')\n",
    "data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Index: 2 entries, Australia to New Zealand\n",
      "Data columns (total 12 columns):\n",
      " #   Column          Non-Null Count  Dtype  \n",
      "---  ------          --------------  -----  \n",
      " 0   gdpPercap_1952  2 non-null      float64\n",
      " 1   gdpPercap_1957  2 non-null      float64\n",
      " 2   gdpPercap_1962  2 non-null      float64\n",
      " 3   gdpPercap_1967  2 non-null      float64\n",
      " 4   gdpPercap_1972  2 non-null      float64\n",
      " 5   gdpPercap_1977  2 non-null      float64\n",
      " 6   gdpPercap_1982  2 non-null      float64\n",
      " 7   gdpPercap_1987  2 non-null      float64\n",
      " 8   gdpPercap_1992  2 non-null      float64\n",
      " 9   gdpPercap_1997  2 non-null      float64\n",
      " 10  gdpPercap_2002  2 non-null      float64\n",
      " 11  gdpPercap_2007  2 non-null      float64\n",
      "dtypes: float64(12)\n",
      "memory usage: 208.0+ bytes\n"
     ]
    }
   ],
   "source": [
    "data.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>gdpPercap_1952</th>\n",
       "      <th>gdpPercap_1957</th>\n",
       "      <th>gdpPercap_1962</th>\n",
       "      <th>gdpPercap_1967</th>\n",
       "      <th>gdpPercap_1972</th>\n",
       "      <th>gdpPercap_1977</th>\n",
       "      <th>gdpPercap_1982</th>\n",
       "      <th>gdpPercap_1987</th>\n",
       "      <th>gdpPercap_1992</th>\n",
       "      <th>gdpPercap_1997</th>\n",
       "      <th>gdpPercap_2002</th>\n",
       "      <th>gdpPercap_2007</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>2.000000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>2.00000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>2.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>10298.085650</td>\n",
       "      <td>11598.522455</td>\n",
       "      <td>12696.452430</td>\n",
       "      <td>14495.021790</td>\n",
       "      <td>16417.33338</td>\n",
       "      <td>17283.957605</td>\n",
       "      <td>18554.709840</td>\n",
       "      <td>20448.040160</td>\n",
       "      <td>20894.045885</td>\n",
       "      <td>24024.175170</td>\n",
       "      <td>26938.778040</td>\n",
       "      <td>29810.188275</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>365.560078</td>\n",
       "      <td>917.644806</td>\n",
       "      <td>677.727301</td>\n",
       "      <td>43.986086</td>\n",
       "      <td>525.09198</td>\n",
       "      <td>1485.263517</td>\n",
       "      <td>1304.328377</td>\n",
       "      <td>2037.668013</td>\n",
       "      <td>3578.979883</td>\n",
       "      <td>4205.533703</td>\n",
       "      <td>5301.853680</td>\n",
       "      <td>6540.991104</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>10039.595640</td>\n",
       "      <td>10949.649590</td>\n",
       "      <td>12217.226860</td>\n",
       "      <td>14463.918930</td>\n",
       "      <td>16046.03728</td>\n",
       "      <td>16233.717700</td>\n",
       "      <td>17632.410400</td>\n",
       "      <td>19007.191290</td>\n",
       "      <td>18363.324940</td>\n",
       "      <td>21050.413770</td>\n",
       "      <td>23189.801350</td>\n",
       "      <td>25185.009110</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>10168.840645</td>\n",
       "      <td>11274.086022</td>\n",
       "      <td>12456.839645</td>\n",
       "      <td>14479.470360</td>\n",
       "      <td>16231.68533</td>\n",
       "      <td>16758.837652</td>\n",
       "      <td>18093.560120</td>\n",
       "      <td>19727.615725</td>\n",
       "      <td>19628.685413</td>\n",
       "      <td>22537.294470</td>\n",
       "      <td>25064.289695</td>\n",
       "      <td>27497.598692</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>10298.085650</td>\n",
       "      <td>11598.522455</td>\n",
       "      <td>12696.452430</td>\n",
       "      <td>14495.021790</td>\n",
       "      <td>16417.33338</td>\n",
       "      <td>17283.957605</td>\n",
       "      <td>18554.709840</td>\n",
       "      <td>20448.040160</td>\n",
       "      <td>20894.045885</td>\n",
       "      <td>24024.175170</td>\n",
       "      <td>26938.778040</td>\n",
       "      <td>29810.188275</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>10427.330655</td>\n",
       "      <td>11922.958888</td>\n",
       "      <td>12936.065215</td>\n",
       "      <td>14510.573220</td>\n",
       "      <td>16602.98143</td>\n",
       "      <td>17809.077557</td>\n",
       "      <td>19015.859560</td>\n",
       "      <td>21168.464595</td>\n",
       "      <td>22159.406358</td>\n",
       "      <td>25511.055870</td>\n",
       "      <td>28813.266385</td>\n",
       "      <td>32122.777857</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>10556.575660</td>\n",
       "      <td>12247.395320</td>\n",
       "      <td>13175.678000</td>\n",
       "      <td>14526.124650</td>\n",
       "      <td>16788.62948</td>\n",
       "      <td>18334.197510</td>\n",
       "      <td>19477.009280</td>\n",
       "      <td>21888.889030</td>\n",
       "      <td>23424.766830</td>\n",
       "      <td>26997.936570</td>\n",
       "      <td>30687.754730</td>\n",
       "      <td>34435.367440</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       gdpPercap_1952  gdpPercap_1957  gdpPercap_1962  gdpPercap_1967  \\\n",
       "count        2.000000        2.000000        2.000000        2.000000   \n",
       "mean     10298.085650    11598.522455    12696.452430    14495.021790   \n",
       "std        365.560078      917.644806      677.727301       43.986086   \n",
       "min      10039.595640    10949.649590    12217.226860    14463.918930   \n",
       "25%      10168.840645    11274.086022    12456.839645    14479.470360   \n",
       "50%      10298.085650    11598.522455    12696.452430    14495.021790   \n",
       "75%      10427.330655    11922.958888    12936.065215    14510.573220   \n",
       "max      10556.575660    12247.395320    13175.678000    14526.124650   \n",
       "\n",
       "       gdpPercap_1972  gdpPercap_1977  gdpPercap_1982  gdpPercap_1987  \\\n",
       "count         2.00000        2.000000        2.000000        2.000000   \n",
       "mean      16417.33338    17283.957605    18554.709840    20448.040160   \n",
       "std         525.09198     1485.263517     1304.328377     2037.668013   \n",
       "min       16046.03728    16233.717700    17632.410400    19007.191290   \n",
       "25%       16231.68533    16758.837652    18093.560120    19727.615725   \n",
       "50%       16417.33338    17283.957605    18554.709840    20448.040160   \n",
       "75%       16602.98143    17809.077557    19015.859560    21168.464595   \n",
       "max       16788.62948    18334.197510    19477.009280    21888.889030   \n",
       "\n",
       "       gdpPercap_1992  gdpPercap_1997  gdpPercap_2002  gdpPercap_2007  \n",
       "count        2.000000        2.000000        2.000000        2.000000  \n",
       "mean     20894.045885    24024.175170    26938.778040    29810.188275  \n",
       "std       3578.979883     4205.533703     5301.853680     6540.991104  \n",
       "min      18363.324940    21050.413770    23189.801350    25185.009110  \n",
       "25%      19628.685413    22537.294470    25064.289695    27497.598692  \n",
       "50%      20894.045885    24024.175170    26938.778040    29810.188275  \n",
       "75%      22159.406358    25511.055870    28813.266385    32122.777857  \n",
       "max      23424.766830    26997.936570    30687.754730    34435.367440  "
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.describe()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Read the data in gapminder_gdp_americas.csv (which should be in the same directory as gapminder_gdp_oceania.csv) into a variable called `americas` and display its summary statistics."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>gdpPercap_1952</th>\n",
       "      <th>gdpPercap_1957</th>\n",
       "      <th>gdpPercap_1962</th>\n",
       "      <th>gdpPercap_1967</th>\n",
       "      <th>gdpPercap_1972</th>\n",
       "      <th>gdpPercap_1977</th>\n",
       "      <th>gdpPercap_1982</th>\n",
       "      <th>gdpPercap_1987</th>\n",
       "      <th>gdpPercap_1992</th>\n",
       "      <th>gdpPercap_1997</th>\n",
       "      <th>gdpPercap_2002</th>\n",
       "      <th>gdpPercap_2007</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>25.000000</td>\n",
       "      <td>25.000000</td>\n",
       "      <td>25.000000</td>\n",
       "      <td>25.000000</td>\n",
       "      <td>25.000000</td>\n",
       "      <td>25.000000</td>\n",
       "      <td>25.000000</td>\n",
       "      <td>25.000000</td>\n",
       "      <td>25.000000</td>\n",
       "      <td>25.000000</td>\n",
       "      <td>25.000000</td>\n",
       "      <td>25.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>4079.062552</td>\n",
       "      <td>4616.043733</td>\n",
       "      <td>4901.541870</td>\n",
       "      <td>5668.253496</td>\n",
       "      <td>6491.334139</td>\n",
       "      <td>7352.007126</td>\n",
       "      <td>7506.737088</td>\n",
       "      <td>7793.400261</td>\n",
       "      <td>8044.934406</td>\n",
       "      <td>8889.300863</td>\n",
       "      <td>9287.677107</td>\n",
       "      <td>11003.031625</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>3001.727522</td>\n",
       "      <td>3312.381083</td>\n",
       "      <td>3421.740569</td>\n",
       "      <td>4160.885560</td>\n",
       "      <td>4754.404329</td>\n",
       "      <td>5355.602518</td>\n",
       "      <td>5530.490471</td>\n",
       "      <td>6665.039509</td>\n",
       "      <td>7047.089191</td>\n",
       "      <td>7874.225145</td>\n",
       "      <td>8895.817785</td>\n",
       "      <td>9713.209302</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>1397.717137</td>\n",
       "      <td>1544.402995</td>\n",
       "      <td>1662.137359</td>\n",
       "      <td>1452.057666</td>\n",
       "      <td>1654.456946</td>\n",
       "      <td>1874.298931</td>\n",
       "      <td>2011.159549</td>\n",
       "      <td>1823.015995</td>\n",
       "      <td>1456.309517</td>\n",
       "      <td>1341.726931</td>\n",
       "      <td>1270.364932</td>\n",
       "      <td>1201.637154</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>2428.237769</td>\n",
       "      <td>2487.365989</td>\n",
       "      <td>2750.364446</td>\n",
       "      <td>3242.531147</td>\n",
       "      <td>4031.408271</td>\n",
       "      <td>4756.763836</td>\n",
       "      <td>4258.503604</td>\n",
       "      <td>4140.442097</td>\n",
       "      <td>4439.450840</td>\n",
       "      <td>4684.313807</td>\n",
       "      <td>4858.347495</td>\n",
       "      <td>5728.353514</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>3048.302900</td>\n",
       "      <td>3780.546651</td>\n",
       "      <td>4086.114078</td>\n",
       "      <td>4643.393534</td>\n",
       "      <td>5305.445256</td>\n",
       "      <td>6281.290855</td>\n",
       "      <td>6434.501797</td>\n",
       "      <td>6360.943444</td>\n",
       "      <td>6618.743050</td>\n",
       "      <td>7113.692252</td>\n",
       "      <td>6994.774861</td>\n",
       "      <td>8948.102923</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>3939.978789</td>\n",
       "      <td>4756.525781</td>\n",
       "      <td>5180.755910</td>\n",
       "      <td>5788.093330</td>\n",
       "      <td>6809.406690</td>\n",
       "      <td>7674.929108</td>\n",
       "      <td>8997.897412</td>\n",
       "      <td>7807.095818</td>\n",
       "      <td>8137.004775</td>\n",
       "      <td>9767.297530</td>\n",
       "      <td>8797.640716</td>\n",
       "      <td>11977.574960</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>13990.482080</td>\n",
       "      <td>14847.127120</td>\n",
       "      <td>16173.145860</td>\n",
       "      <td>19530.365570</td>\n",
       "      <td>21806.035940</td>\n",
       "      <td>24072.632130</td>\n",
       "      <td>25009.559140</td>\n",
       "      <td>29884.350410</td>\n",
       "      <td>32003.932240</td>\n",
       "      <td>35767.433030</td>\n",
       "      <td>39097.099550</td>\n",
       "      <td>42951.653090</td>\n",
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       "  </tbody>\n",
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       "</div>"
      ],
      "text/plain": [
       "       gdpPercap_1952  gdpPercap_1957  gdpPercap_1962  gdpPercap_1967  \\\n",
       "count       25.000000       25.000000       25.000000       25.000000   \n",
       "mean      4079.062552     4616.043733     4901.541870     5668.253496   \n",
       "std       3001.727522     3312.381083     3421.740569     4160.885560   \n",
       "min       1397.717137     1544.402995     1662.137359     1452.057666   \n",
       "25%       2428.237769     2487.365989     2750.364446     3242.531147   \n",
       "50%       3048.302900     3780.546651     4086.114078     4643.393534   \n",
       "75%       3939.978789     4756.525781     5180.755910     5788.093330   \n",
       "max      13990.482080    14847.127120    16173.145860    19530.365570   \n",
       "\n",
       "       gdpPercap_1972  gdpPercap_1977  gdpPercap_1982  gdpPercap_1987  \\\n",
       "count       25.000000       25.000000       25.000000       25.000000   \n",
       "mean      6491.334139     7352.007126     7506.737088     7793.400261   \n",
       "std       4754.404329     5355.602518     5530.490471     6665.039509   \n",
       "min       1654.456946     1874.298931     2011.159549     1823.015995   \n",
       "25%       4031.408271     4756.763836     4258.503604     4140.442097   \n",
       "50%       5305.445256     6281.290855     6434.501797     6360.943444   \n",
       "75%       6809.406690     7674.929108     8997.897412     7807.095818   \n",
       "max      21806.035940    24072.632130    25009.559140    29884.350410   \n",
       "\n",
       "       gdpPercap_1992  gdpPercap_1997  gdpPercap_2002  gdpPercap_2007  \n",
       "count       25.000000       25.000000       25.000000       25.000000  \n",
       "mean      8044.934406     8889.300863     9287.677107    11003.031625  \n",
       "std       7047.089191     7874.225145     8895.817785     9713.209302  \n",
       "min       1456.309517     1341.726931     1270.364932     1201.637154  \n",
       "25%       4439.450840     4684.313807     4858.347495     5728.353514  \n",
       "50%       6618.743050     7113.692252     6994.774861     8948.102923  \n",
       "75%       8137.004775     9767.297530     8797.640716    11977.574960  \n",
       "max      32003.932240    35767.433030    39097.099550    42951.653090  "
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "americas = pd.read_csv('data/gapminder_gdp_americas.csv', index_col='country')\n",
    "americas.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>continent</th>\n",
       "      <th>gdpPercap_1952</th>\n",
       "      <th>gdpPercap_1957</th>\n",
       "      <th>gdpPercap_1962</th>\n",
       "      <th>gdpPercap_1967</th>\n",
       "      <th>gdpPercap_1972</th>\n",
       "      <th>gdpPercap_1977</th>\n",
       "      <th>gdpPercap_1982</th>\n",
       "      <th>gdpPercap_1987</th>\n",
       "      <th>gdpPercap_1992</th>\n",
       "      <th>gdpPercap_1997</th>\n",
       "      <th>gdpPercap_2002</th>\n",
       "      <th>gdpPercap_2007</th>\n",
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       "    <tr>\n",
       "      <th>country</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
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       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
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       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Argentina</th>\n",
       "      <td>Americas</td>\n",
       "      <td>5911.315053</td>\n",
       "      <td>6856.856212</td>\n",
       "      <td>7133.166023</td>\n",
       "      <td>8052.953021</td>\n",
       "      <td>9443.038526</td>\n",
       "      <td>10079.026740</td>\n",
       "      <td>8997.897412</td>\n",
       "      <td>9139.671389</td>\n",
       "      <td>9308.418710</td>\n",
       "      <td>10967.281950</td>\n",
       "      <td>8797.640716</td>\n",
       "      <td>12779.379640</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Bolivia</th>\n",
       "      <td>Americas</td>\n",
       "      <td>2677.326347</td>\n",
       "      <td>2127.686326</td>\n",
       "      <td>2180.972546</td>\n",
       "      <td>2586.886053</td>\n",
       "      <td>2980.331339</td>\n",
       "      <td>3548.097832</td>\n",
       "      <td>3156.510452</td>\n",
       "      <td>2753.691490</td>\n",
       "      <td>2961.699694</td>\n",
       "      <td>3326.143191</td>\n",
       "      <td>3413.262690</td>\n",
       "      <td>3822.137084</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Brazil</th>\n",
       "      <td>Americas</td>\n",
       "      <td>2108.944355</td>\n",
       "      <td>2487.365989</td>\n",
       "      <td>3336.585802</td>\n",
       "      <td>3429.864357</td>\n",
       "      <td>4985.711467</td>\n",
       "      <td>6660.118654</td>\n",
       "      <td>7030.835878</td>\n",
       "      <td>7807.095818</td>\n",
       "      <td>6950.283021</td>\n",
       "      <td>7957.980824</td>\n",
       "      <td>8131.212843</td>\n",
       "      <td>9065.800825</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Canada</th>\n",
       "      <td>Americas</td>\n",
       "      <td>11367.161120</td>\n",
       "      <td>12489.950060</td>\n",
       "      <td>13462.485550</td>\n",
       "      <td>16076.588030</td>\n",
       "      <td>18970.570860</td>\n",
       "      <td>22090.883060</td>\n",
       "      <td>22898.792140</td>\n",
       "      <td>26626.515030</td>\n",
       "      <td>26342.884260</td>\n",
       "      <td>28954.925890</td>\n",
       "      <td>33328.965070</td>\n",
       "      <td>36319.235010</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Chile</th>\n",
       "      <td>Americas</td>\n",
       "      <td>3939.978789</td>\n",
       "      <td>4315.622723</td>\n",
       "      <td>4519.094331</td>\n",
       "      <td>5106.654313</td>\n",
       "      <td>5494.024437</td>\n",
       "      <td>4756.763836</td>\n",
       "      <td>5095.665738</td>\n",
       "      <td>5547.063754</td>\n",
       "      <td>7596.125964</td>\n",
       "      <td>10118.053180</td>\n",
       "      <td>10778.783850</td>\n",
       "      <td>13171.638850</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          continent  gdpPercap_1952  gdpPercap_1957  gdpPercap_1962  \\\n",
       "country                                                               \n",
       "Argentina  Americas     5911.315053     6856.856212     7133.166023   \n",
       "Bolivia    Americas     2677.326347     2127.686326     2180.972546   \n",
       "Brazil     Americas     2108.944355     2487.365989     3336.585802   \n",
       "Canada     Americas    11367.161120    12489.950060    13462.485550   \n",
       "Chile      Americas     3939.978789     4315.622723     4519.094331   \n",
       "\n",
       "           gdpPercap_1967  gdpPercap_1972  gdpPercap_1977  gdpPercap_1982  \\\n",
       "country                                                                     \n",
       "Argentina     8052.953021     9443.038526    10079.026740     8997.897412   \n",
       "Bolivia       2586.886053     2980.331339     3548.097832     3156.510452   \n",
       "Brazil        3429.864357     4985.711467     6660.118654     7030.835878   \n",
       "Canada       16076.588030    18970.570860    22090.883060    22898.792140   \n",
       "Chile         5106.654313     5494.024437     4756.763836     5095.665738   \n",
       "\n",
       "           gdpPercap_1987  gdpPercap_1992  gdpPercap_1997  gdpPercap_2002  \\\n",
       "country                                                                     \n",
       "Argentina     9139.671389     9308.418710    10967.281950     8797.640716   \n",
       "Bolivia       2753.691490     2961.699694     3326.143191     3413.262690   \n",
       "Brazil        7807.095818     6950.283021     7957.980824     8131.212843   \n",
       "Canada       26626.515030    26342.884260    28954.925890    33328.965070   \n",
       "Chile         5547.063754     7596.125964    10118.053180    10778.783850   \n",
       "\n",
       "           gdpPercap_2007  \n",
       "country                    \n",
       "Argentina    12779.379640  \n",
       "Bolivia       3822.137084  \n",
       "Brazil        9065.800825  \n",
       "Canada       36319.235010  \n",
       "Chile        13171.638850  "
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "americas.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Puerto Rico</th>\n",
       "      <td>Americas</td>\n",
       "      <td>3081.959785</td>\n",
       "      <td>3907.156189</td>\n",
       "      <td>5108.344630</td>\n",
       "      <td>6929.277714</td>\n",
       "      <td>9123.041742</td>\n",
       "      <td>9770.524921</td>\n",
       "      <td>10330.989150</td>\n",
       "      <td>12281.341910</td>\n",
       "      <td>14641.587110</td>\n",
       "      <td>16999.433300</td>\n",
       "      <td>18855.606180</td>\n",
       "      <td>19328.70901</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Trinidad and Tobago</th>\n",
       "      <td>Americas</td>\n",
       "      <td>3023.271928</td>\n",
       "      <td>4100.393400</td>\n",
       "      <td>4997.523971</td>\n",
       "      <td>5621.368472</td>\n",
       "      <td>6619.551419</td>\n",
       "      <td>7899.554209</td>\n",
       "      <td>9119.528607</td>\n",
       "      <td>7388.597823</td>\n",
       "      <td>7370.990932</td>\n",
       "      <td>8792.573126</td>\n",
       "      <td>11460.600230</td>\n",
       "      <td>18008.50924</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>United States</th>\n",
       "      <td>Americas</td>\n",
       "      <td>13990.482080</td>\n",
       "      <td>14847.127120</td>\n",
       "      <td>16173.145860</td>\n",
       "      <td>19530.365570</td>\n",
       "      <td>21806.035940</td>\n",
       "      <td>24072.632130</td>\n",
       "      <td>25009.559140</td>\n",
       "      <td>29884.350410</td>\n",
       "      <td>32003.932240</td>\n",
       "      <td>35767.433030</td>\n",
       "      <td>39097.099550</td>\n",
       "      <td>42951.65309</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Uruguay</th>\n",
       "      <td>Americas</td>\n",
       "      <td>5716.766744</td>\n",
       "      <td>6150.772969</td>\n",
       "      <td>5603.357717</td>\n",
       "      <td>5444.619620</td>\n",
       "      <td>5703.408898</td>\n",
       "      <td>6504.339663</td>\n",
       "      <td>6920.223051</td>\n",
       "      <td>7452.398969</td>\n",
       "      <td>8137.004775</td>\n",
       "      <td>9230.240708</td>\n",
       "      <td>7727.002004</td>\n",
       "      <td>10611.46299</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Venezuela</th>\n",
       "      <td>Americas</td>\n",
       "      <td>7689.799761</td>\n",
       "      <td>9802.466526</td>\n",
       "      <td>8422.974165</td>\n",
       "      <td>9541.474188</td>\n",
       "      <td>10505.259660</td>\n",
       "      <td>13143.950950</td>\n",
       "      <td>11152.410110</td>\n",
       "      <td>9883.584648</td>\n",
       "      <td>10733.926310</td>\n",
       "      <td>10165.495180</td>\n",
       "      <td>8605.047831</td>\n",
       "      <td>11415.80569</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                    continent  gdpPercap_1952  gdpPercap_1957  gdpPercap_1962  \\\n",
       "country                                                                         \n",
       "Puerto Rico          Americas     3081.959785     3907.156189     5108.344630   \n",
       "Trinidad and Tobago  Americas     3023.271928     4100.393400     4997.523971   \n",
       "United States        Americas    13990.482080    14847.127120    16173.145860   \n",
       "Uruguay              Americas     5716.766744     6150.772969     5603.357717   \n",
       "Venezuela            Americas     7689.799761     9802.466526     8422.974165   \n",
       "\n",
       "                     gdpPercap_1967  gdpPercap_1972  gdpPercap_1977  \\\n",
       "country                                                               \n",
       "Puerto Rico             6929.277714     9123.041742     9770.524921   \n",
       "Trinidad and Tobago     5621.368472     6619.551419     7899.554209   \n",
       "United States          19530.365570    21806.035940    24072.632130   \n",
       "Uruguay                 5444.619620     5703.408898     6504.339663   \n",
       "Venezuela               9541.474188    10505.259660    13143.950950   \n",
       "\n",
       "                     gdpPercap_1982  gdpPercap_1987  gdpPercap_1992  \\\n",
       "country                                                               \n",
       "Puerto Rico            10330.989150    12281.341910    14641.587110   \n",
       "Trinidad and Tobago     9119.528607     7388.597823     7370.990932   \n",
       "United States          25009.559140    29884.350410    32003.932240   \n",
       "Uruguay                 6920.223051     7452.398969     8137.004775   \n",
       "Venezuela              11152.410110     9883.584648    10733.926310   \n",
       "\n",
       "                     gdpPercap_1997  gdpPercap_2002  gdpPercap_2007  \n",
       "country                                                              \n",
       "Puerto Rico            16999.433300    18855.606180     19328.70901  \n",
       "Trinidad and Tobago     8792.573126    11460.600230     18008.50924  \n",
       "United States          35767.433030    39097.099550     42951.65309  \n",
       "Uruguay                 9230.240708     7727.002004     10611.46299  \n",
       "Venezuela              10165.495180     8605.047831     11415.80569  "
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "americas.tail()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [],
   "source": [
    "americas.to_csv('test-americas.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'Americas'"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "americas.iloc[0,0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "2677.3263469999997"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "americas.iloc[1,1]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "5911.315053"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "americas.iloc[0,1]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "2194.926204"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "americas.loc[\"Honduras\",\"gdpPercap_1952\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "continent         Americas\n",
       "gdpPercap_1952     3112.36\n",
       "gdpPercap_1957     3457.42\n",
       "gdpPercap_1962     3634.36\n",
       "gdpPercap_1967     4643.39\n",
       "gdpPercap_1972     4688.59\n",
       "gdpPercap_1977     5486.37\n",
       "gdpPercap_1982     3470.34\n",
       "gdpPercap_1987     2955.98\n",
       "gdpPercap_1992     2170.15\n",
       "gdpPercap_1997     2253.02\n",
       "gdpPercap_2002     2474.55\n",
       "gdpPercap_2007     2749.32\n",
       "Name: Nicaragua, dtype: object"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "americas.loc[\"Nicaragua\",:]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['Argentina', 'Bolivia', 'Brazil', 'Canada', 'Chile', 'Colombia',\n",
       "       'Costa Rica', 'Cuba', 'Dominican Republic', 'Ecuador', 'El Salvador',\n",
       "       'Guatemala', 'Haiti', 'Honduras', 'Jamaica', 'Mexico', 'Nicaragua',\n",
       "       'Panama', 'Paraguay', 'Peru', 'Puerto Rico', 'Trinidad and Tobago',\n",
       "       'United States', 'Uruguay', 'Venezuela'],\n",
       "      dtype='object', name='country')"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "americas.index"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['continent', 'gdpPercap_1952', 'gdpPercap_1957', 'gdpPercap_1962',\n",
       "       'gdpPercap_1967', 'gdpPercap_1972', 'gdpPercap_1977', 'gdpPercap_1982',\n",
       "       'gdpPercap_1987', 'gdpPercap_1992', 'gdpPercap_1997', 'gdpPercap_2002',\n",
       "       'gdpPercap_2007'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "americas.columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "8797.640716"
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "americas.loc['Argentina','gdpPercap_2002']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "country\n",
       "Argentina               8797.640716\n",
       "Bolivia                 3413.262690\n",
       "Brazil                  8131.212843\n",
       "Canada                 33328.965070\n",
       "Chile                  10778.783850\n",
       "Colombia                5755.259962\n",
       "Costa Rica              7723.447195\n",
       "Cuba                    6340.646683\n",
       "Dominican Republic      4563.808154\n",
       "Ecuador                 5773.044512\n",
       "El Salvador             5351.568666\n",
       "Guatemala               4858.347495\n",
       "Haiti                   1270.364932\n",
       "Honduras                3099.728660\n",
       "Jamaica                 6994.774861\n",
       "Mexico                 10742.440530\n",
       "Nicaragua               2474.548819\n",
       "Panama                  7356.031934\n",
       "Paraguay                3783.674243\n",
       "Peru                    5909.020073\n",
       "Puerto Rico            18855.606180\n",
       "Trinidad and Tobago    11460.600230\n",
       "United States          39097.099550\n",
       "Uruguay                 7727.002004\n",
       "Venezuela               8605.047831\n",
       "Name: gdpPercap_2002, dtype: float64"
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "americas.loc[:,'gdpPercap_2002']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "' is a'"
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "'this is a message'[ 4:9 ]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>gdpPercap_1972</th>\n",
       "      <th>gdpPercap_1977</th>\n",
       "      <th>gdpPercap_1982</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>country</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Mexico</th>\n",
       "      <td>6809.406690</td>\n",
       "      <td>7674.929108</td>\n",
       "      <td>9611.147541</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Nicaragua</th>\n",
       "      <td>4688.593267</td>\n",
       "      <td>5486.371089</td>\n",
       "      <td>3470.338156</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Panama</th>\n",
       "      <td>5364.249663</td>\n",
       "      <td>5351.912144</td>\n",
       "      <td>7009.601598</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Paraguay</th>\n",
       "      <td>2523.337977</td>\n",
       "      <td>3248.373311</td>\n",
       "      <td>4258.503604</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Peru</th>\n",
       "      <td>5937.827283</td>\n",
       "      <td>6281.290855</td>\n",
       "      <td>6434.501797</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Puerto Rico</th>\n",
       "      <td>9123.041742</td>\n",
       "      <td>9770.524921</td>\n",
       "      <td>10330.989150</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Trinidad and Tobago</th>\n",
       "      <td>6619.551419</td>\n",
       "      <td>7899.554209</td>\n",
       "      <td>9119.528607</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>United States</th>\n",
       "      <td>21806.035940</td>\n",
       "      <td>24072.632130</td>\n",
       "      <td>25009.559140</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Uruguay</th>\n",
       "      <td>5703.408898</td>\n",
       "      <td>6504.339663</td>\n",
       "      <td>6920.223051</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                     gdpPercap_1972  gdpPercap_1977  gdpPercap_1982\n",
       "country                                                            \n",
       "Mexico                  6809.406690     7674.929108     9611.147541\n",
       "Nicaragua               4688.593267     5486.371089     3470.338156\n",
       "Panama                  5364.249663     5351.912144     7009.601598\n",
       "Paraguay                2523.337977     3248.373311     4258.503604\n",
       "Peru                    5937.827283     6281.290855     6434.501797\n",
       "Puerto Rico             9123.041742     9770.524921    10330.989150\n",
       "Trinidad and Tobago     6619.551419     7899.554209     9119.528607\n",
       "United States          21806.035940    24072.632130    25009.559140\n",
       "Uruguay                 5703.408898     6504.339663     6920.223051"
      ]
     },
     "execution_count": 38,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "americas.loc['Mexico':'Uruguay','gdpPercap_1972':'gdpPercap_1982']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'this is text'"
      ]
     },
     "execution_count": 39,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "\"this is text\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [],
   "source": [
    "subset = americas.loc['Mexico':'Uruguay','gdpPercap_1972':'gdpPercap_1982']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "gdpPercap_1972    21806.03594\n",
       "gdpPercap_1977    24072.63213\n",
       "gdpPercap_1982    25009.55914\n",
       "dtype: float64"
      ]
     },
     "execution_count": 41,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "subset.max()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "3548.3308460000003"
      ]
     },
     "execution_count": 45,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "americas.loc['Honduras','gdpPercap_1962':'gdpPercap_2007'].max()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>gdpPercap_1972</th>\n",
       "      <th>gdpPercap_1977</th>\n",
       "      <th>gdpPercap_1982</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>country</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Mexico</th>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Nicaragua</th>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Panama</th>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Paraguay</th>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Peru</th>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Puerto Rico</th>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Trinidad and Tobago</th>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>United States</th>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Uruguay</th>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                     gdpPercap_1972  gdpPercap_1977  gdpPercap_1982\n",
       "country                                                            \n",
       "Mexico                        False           False           False\n",
       "Nicaragua                     False           False           False\n",
       "Panama                        False           False           False\n",
       "Paraguay                      False           False           False\n",
       "Peru                          False           False           False\n",
       "Puerto Rico                   False           False            True\n",
       "Trinidad and Tobago           False           False           False\n",
       "United States                  True            True            True\n",
       "Uruguay                       False           False           False"
      ]
     },
     "execution_count": 48,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "subset > 10000"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
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       "\n",
       "    .dataframe tbody tr th {\n",
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       "    }\n",
       "\n",
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       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>gdpPercap_1972</th>\n",
       "      <th>gdpPercap_1977</th>\n",
       "      <th>gdpPercap_1982</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>country</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Mexico</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Nicaragua</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Panama</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Paraguay</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Peru</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Puerto Rico</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>10330.98915</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Trinidad and Tobago</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>United States</th>\n",
       "      <td>21806.03594</td>\n",
       "      <td>24072.63213</td>\n",
       "      <td>25009.55914</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Uruguay</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                     gdpPercap_1972  gdpPercap_1977  gdpPercap_1982\n",
       "country                                                            \n",
       "Mexico                          NaN             NaN             NaN\n",
       "Nicaragua                       NaN             NaN             NaN\n",
       "Panama                          NaN             NaN             NaN\n",
       "Paraguay                        NaN             NaN             NaN\n",
       "Peru                            NaN             NaN             NaN\n",
       "Puerto Rico                     NaN             NaN     10330.98915\n",
       "Trinidad and Tobago             NaN             NaN             NaN\n",
       "United States           21806.03594     24072.63213     25009.55914\n",
       "Uruguay                         NaN             NaN             NaN"
      ]
     },
     "execution_count": 49,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "subset[subset > 10000]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
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       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>gdpPercap_1972</th>\n",
       "      <th>gdpPercap_1977</th>\n",
       "      <th>gdpPercap_1982</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>9.000000</td>\n",
       "      <td>9.000000</td>\n",
       "      <td>9.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>7619.494764</td>\n",
       "      <td>8476.658603</td>\n",
       "      <td>9129.376960</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>5604.922524</td>\n",
       "      <td>6130.199920</td>\n",
       "      <td>6385.946934</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>2523.337977</td>\n",
       "      <td>3248.373311</td>\n",
       "      <td>3470.338156</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>5364.249663</td>\n",
       "      <td>5486.371089</td>\n",
       "      <td>6434.501797</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>5937.827283</td>\n",
       "      <td>6504.339663</td>\n",
       "      <td>7009.601598</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>6809.406690</td>\n",
       "      <td>7899.554209</td>\n",
       "      <td>9611.147541</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>21806.035940</td>\n",
       "      <td>24072.632130</td>\n",
       "      <td>25009.559140</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       gdpPercap_1972  gdpPercap_1977  gdpPercap_1982\n",
       "count        9.000000        9.000000        9.000000\n",
       "mean      7619.494764     8476.658603     9129.376960\n",
       "std       5604.922524     6130.199920     6385.946934\n",
       "min       2523.337977     3248.373311     3470.338156\n",
       "25%       5364.249663     5486.371089     6434.501797\n",
       "50%       5937.827283     6504.339663     7009.601598\n",
       "75%       6809.406690     7899.554209     9611.147541\n",
       "max      21806.035940    24072.632130    25009.559140"
      ]
     },
     "execution_count": 51,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "subset[subset > 1000].describe()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "1. Load the European data set as `europe`.\n",
    "2. Find the per-capita GDP of Serbia in 2007."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Assume Pandas has been imported and the Gapminder GDP data for Europe has been loaded. Write an expression to select each of the following:\n",
    "\n",
    "1. GDP per capita for all countries in 1982.\n",
    "2. GDP per capita for Denmark for all years.\n",
    "3. GDP per capita for all countries for years after 1985.\n",
    "4. GDP per capita for each country in 2007 as a multiple of GDP per capita for that country in 1952."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "country\n",
       "Argentina              2.161851\n",
       "Bolivia                1.427595\n",
       "Brazil                 4.298739\n",
       "Canada                 3.195102\n",
       "Chile                  3.343074\n",
       "Colombia               3.267819\n",
       "Costa Rica             3.671499\n",
       "Cuba                   1.601726\n",
       "Dominican Republic     4.310868\n",
       "Ecuador                1.951461\n",
       "El Salvador            1.879194\n",
       "Guatemala              2.135726\n",
       "Haiti                  0.652933\n",
       "Honduras               1.616606\n",
       "Jamaica                2.525721\n",
       "Mexico                 3.443687\n",
       "Nicaragua              0.883355\n",
       "Panama                 3.954710\n",
       "Paraguay               2.137387\n",
       "Peru                   1.971228\n",
       "Puerto Rico            6.271564\n",
       "Trinidad and Tobago    5.956629\n",
       "United States          3.070062\n",
       "Uruguay                1.856200\n",
       "Venezuela              1.484539\n",
       "dtype: float64"
      ]
     },
     "execution_count": 54,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "americas['gdpPercap_2007']/americas['gdpPercap_1952']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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