ch09.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Plotting and Visualization"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "绘制 可视化"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "from IPython.core.interactiveshell import InteractiveShell\n",
    "InteractiveShell.ast_node_interactivity = \"all\" "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import pandas as pd\n",
    "PREVIOUS_MAX_ROWS = pd.options.display.max_rows\n",
    "pd.options.display.max_rows = 20\n",
    "np.random.seed(12345)#生成指定随机数\n",
    "import matplotlib.pyplot as plt\n",
    "import matplotlib\n",
    "plt.rc('figure', figsize=(10, 6))\n",
    "np.set_printoptions(precision=4, suppress=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "%matplotlib notebook"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## A Brief matplotlib API Primer"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([0, 1, 2, 3, 4, 5, 6, 7, 8, 9])"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x24657092070>]"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "import numpy as np\n",
    "data = np.arange(10)\n",
    "data\n",
    "plt.plot(data)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Figures and Subplots"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Figure size 720x432 with 0 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = plt.figure()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "ax1 = fig.add_subplot(2, 2, 1)#添加子图，前两个分布，后面为index"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "ax2 = fig.add_subplot(2, 2, 2)\n",
    "ax3 = fig.add_subplot(2, 2, 3)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "fig = plt.figure()\n",
    "ax1 = fig.add_subplot(2, 2, 1)\n",
    "ax2 = fig.add_subplot(2, 2, 2)\n",
    "ax3 = fig.add_subplot(2, 2, 3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x2465717dd90>]"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(np.random.randn(50).cumsum(), 'k--')#按照所给定的轴参数返回元素的梯形累计和，axis=0，\n",
    "##按照行累加。axis=1，按照列累加。axis不给定具体值，就把numpy数组当成一个一维数组，K线型"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.collections.PathCollection at 0x246571bfcd0>"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "_ = ax1.hist(np.random.randn(100), bins=20, color='k', alpha=0.3)#直方图hist\n",
    "ax2.scatter(np.arange(30), np.arange(30) + 3 * np.random.randn(30))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "plt.close('all')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[<AxesSubplot:>, <AxesSubplot:>, <AxesSubplot:>],\n",
       "       [<AxesSubplot:>, <AxesSubplot:>, <AxesSubplot:>]], dtype=object)"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 720x432 with 6 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, axes = plt.subplots(2, 3)\n",
    "axes"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Adjusting the spacing around subplots"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "subplots_adjust(left=None, bottom=None, right=None, top=None,\n",
    "                wspace=None, hspace=None)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "fig, axes = plt.subplots(2, 2, sharex=True, sharey=True)\n",
    "for i in range(2):\n",
    "    for j in range(2):\n",
    "        axes[i, j].hist(np.random.randn(500), bins=50, color='k', alpha=0.5)\n",
    "plt.subplots_adjust(wspace=0, hspace=0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(array([ 2.,  0.,  3.,  2.,  1.,  1.,  0.,  3.,  5.,  8.,  9.,  9., 10.,\n",
       "        18., 34., 13., 24., 30., 24., 24., 25., 20., 34., 20., 30., 30.,\n",
       "        19., 14., 14.,  8., 19., 14.,  7.,  3.,  7.,  2.,  7.,  2.,  2.,\n",
       "         0.,  1.,  0.,  0.,  0.,  1.,  0.,  0.,  0.,  0.,  1.]),\n",
       " array([-2.9493, -2.8118, -2.6743, -2.5367, -2.3992, -2.2617, -2.1241,\n",
       "        -1.9866, -1.849 , -1.7115, -1.574 , -1.4364, -1.2989, -1.1614,\n",
       "        -1.0238, -0.8863, -0.7487, -0.6112, -0.4737, -0.3361, -0.1986,\n",
       "        -0.0611,  0.0765,  0.214 ,  0.3516,  0.4891,  0.6266,  0.7642,\n",
       "         0.9017,  1.0392,  1.1768,  1.3143,  1.4519,  1.5894,  1.7269,\n",
       "         1.8645,  2.002 ,  2.1395,  2.2771,  2.4146,  2.5522,  2.6897,\n",
       "         2.8272,  2.9648,  3.1023,  3.2398,  3.3774,  3.5149,  3.6525,\n",
       "         3.79  ,  3.9275]),\n",
       " <BarContainer object of 50 artists>)"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "text/plain": [
       "(array([ 1.,  1.,  0.,  2.,  0.,  1.,  1.,  5.,  7.,  4.,  5.,  8., 12.,\n",
       "        12., 13., 15., 17., 13., 22., 30., 21., 24., 17., 20., 20., 20.,\n",
       "        18., 26., 16., 24., 19.,  8., 14., 15.,  7., 11.,  5.,  4.,  9.,\n",
       "         7.,  6.,  1.,  6.,  2.,  4.,  2.,  0.,  2.,  1.,  2.]),\n",
       " array([-2.595 , -2.4898, -2.3845, -2.2793, -2.1741, -2.0688, -1.9636,\n",
       "        -1.8584, -1.7531, -1.6479, -1.5427, -1.4374, -1.3322, -1.227 ,\n",
       "        -1.1217, -1.0165, -0.9112, -0.806 , -0.7008, -0.5955, -0.4903,\n",
       "        -0.3851, -0.2798, -0.1746, -0.0694,  0.0359,  0.1411,  0.2463,\n",
       "         0.3516,  0.4568,  0.562 ,  0.6673,  0.7725,  0.8777,  0.983 ,\n",
       "         1.0882,  1.1935,  1.2987,  1.4039,  1.5092,  1.6144,  1.7196,\n",
       "         1.8249,  1.9301,  2.0353,  2.1406,  2.2458,  2.351 ,  2.4563,\n",
       "         2.5615,  2.6667]),\n",
       " <BarContainer object of 50 artists>)"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "text/plain": [
       "(array([ 1.,  0.,  1.,  0.,  0.,  1.,  0.,  1.,  1.,  0.,  4.,  1.,  4.,\n",
       "         5., 11.,  8.,  6., 11., 13., 13., 17., 18., 20., 27., 32., 29.,\n",
       "        31., 22., 21., 31., 29., 19., 22., 18., 10., 18., 11., 12.,  9.,\n",
       "         6.,  2.,  3.,  3.,  3.,  2.,  1.,  1.,  1.,  0.,  1.]),\n",
       " array([-3.7454, -3.6052, -3.4651, -3.325 , -3.1849, -3.0448, -2.9047,\n",
       "        -2.7646, -2.6244, -2.4843, -2.3442, -2.2041, -2.064 , -1.9239,\n",
       "        -1.7837, -1.6436, -1.5035, -1.3634, -1.2233, -1.0832, -0.9431,\n",
       "        -0.8029, -0.6628, -0.5227, -0.3826, -0.2425, -0.1024,  0.0377,\n",
       "         0.1779,  0.318 ,  0.4581,  0.5982,  0.7383,  0.8784,  1.0185,\n",
       "         1.1587,  1.2988,  1.4389,  1.579 ,  1.7191,  1.8592,  1.9994,\n",
       "         2.1395,  2.2796,  2.4197,  2.5598,  2.6999,  2.84  ,  2.9802,\n",
       "         3.1203,  3.2604]),\n",
       " <BarContainer object of 50 artists>)"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "text/plain": [
       "(array([ 1.,  0.,  0.,  1.,  1.,  0.,  0.,  0.,  0.,  1.,  2.,  5.,  9.,\n",
       "         8.,  6.,  2., 11., 17., 10., 13., 10., 14., 12., 27., 17., 28.,\n",
       "        27., 25., 14., 24., 25., 38., 13., 24., 15., 10., 17., 14., 13.,\n",
       "         8.,  7., 10.,  3.,  7.,  2.,  5.,  2.,  0.,  1.,  1.]),\n",
       " array([-3.4283, -3.3066, -3.185 , -3.0633, -2.9417, -2.8201, -2.6984,\n",
       "        -2.5768, -2.4551, -2.3335, -2.2119, -2.0902, -1.9686, -1.847 ,\n",
       "        -1.7253, -1.6037, -1.482 , -1.3604, -1.2388, -1.1171, -0.9955,\n",
       "        -0.8739, -0.7522, -0.6306, -0.5089, -0.3873, -0.2657, -0.144 ,\n",
       "        -0.0224,  0.0993,  0.2209,  0.3425,  0.4642,  0.5858,  0.7074,\n",
       "         0.8291,  0.9507,  1.0724,  1.194 ,  1.3156,  1.4373,  1.5589,\n",
       "         1.6806,  1.8022,  1.9238,  2.0455,  2.1671,  2.2887,  2.4104,\n",
       "         2.532 ,  2.6537]),\n",
       " <BarContainer object of 50 artists>)"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x432 with 4 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, axes = plt.subplots(2, 2, sharex=True, sharey=True)\n",
    "for i in range(2):\n",
    "    for j in range(2):\n",
    "        axes[i, j].hist(np.random.randn(500), bins=50, color='k', alpha=0.2)#alpha灰度\n",
    "plt.subplots_adjust(wspace=0, hspace=0)#调整行列间距"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Colors, Markers, and Line Styles"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "ax.plot(x, y, 'g--')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "ax.plot(x, y, linestyle='--', color='g')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Figure size 720x432 with 0 Axes>"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "text/plain": [
       "<Figure size 720x432 with 0 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x2465793e3a0>]"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "text/plain": [
       "array([ 0.8231,  0.516 , -0.4457,  0.3856, -0.0688, -0.3098,  0.4175,\n",
       "       -1.009 , -0.5101, -0.6431,  0.3356, -0.172 ,  2.0784,  0.2183,\n",
       "        0.3703, -0.8464,  1.393 ,  0.237 ,  1.3752,  0.8676,  1.1658,\n",
       "        0.2581,  0.7133, -0.3699, -0.8255,  0.8401,  0.9895,  1.0324,\n",
       "       -0.4746, -0.8776])"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "from numpy.random import randn\n",
    "plt.plot(randn(30).cumsum(), 'ko--')\n",
    "randn(30)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "plot(randn(30).cumsum(), color='k', linestyle='dashed', marker='o')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [],
   "source": [
    "plt.close('all')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x24657814c10>]"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x24657822040>]"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x24657814a60>"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "data = np.random.randn(30).cumsum()\n",
    "plt.plot(data, 'k--', label='Default')\n",
    "plt.plot(data, 'k-', drawstyle='steps-post', label='steps-post')\n",
    "plt.legend(loc='best')#给图像加上图例"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Ticks, Labels, and Legends"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Setting the title, axis labels, ticks, and ticklabels"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x2465787ff10>]"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "text/plain": [
       "array([  0.5629,   0.6119,   1.2409,   1.2188,   1.4781,   0.9618,\n",
       "         0.3821,  -0.9692,  -1.1992,  -1.9991,  -2.6923,  -1.2979,\n",
       "        -1.1613,  -1.9889,  -2.8905,  -2.1884,  -0.9746,  -2.2169,\n",
       "        -3.9684,  -3.2357,  -2.9475,  -4.0127,  -4.9244,  -4.6354,\n",
       "        -4.6522,  -3.158 ,  -3.2588,  -2.0615,  -0.3368,   1.5677,\n",
       "         1.4826,   2.3167,   3.6102,   4.2763,   3.537 ,   2.0428,\n",
       "         1.8298,   3.0084,   2.0616,   2.0893,   1.4091,   1.6038,\n",
       "         2.2781,   0.9202,   0.3834,  -0.4691,  -2.1737,  -0.1332,\n",
       "        -0.2343,  -0.6132,   0.0255,  -0.6712,   0.2349,  -0.1922,\n",
       "        -1.3969,  -0.7669,  -0.5619,  -1.9651,  -3.1058,  -1.7201,\n",
       "        -1.006 ,  -0.7525,  -3.4287,  -1.6524,  -2.195 ,  -1.7991,\n",
       "        -2.7429,  -1.7939,  -1.4203,  -0.6322,  -2.298 ,  -2.342 ,\n",
       "        -3.316 ,  -4.0244,  -3.7928,  -5.5153,  -7.5947,  -8.9934,\n",
       "        -8.978 ,  -8.1504,  -7.1993,  -7.2284,  -8.5477, -10.982 ,\n",
       "        -9.4069,  -9.7928,  -7.4184,  -5.6938,  -6.1958,  -5.4103,\n",
       "        -5.0923,  -6.3367,  -4.794 ,  -4.6617,  -4.506 ,  -4.0923,\n",
       "        -2.8031,  -2.5405,  -2.5321,  -3.8866,  -4.0429,  -3.0157,\n",
       "        -3.0992,  -6.0085,  -5.2796,  -5.5991,  -6.0196,  -7.1364,\n",
       "        -6.8329,  -6.8373,  -7.2703,  -5.8885,  -6.2834,  -7.0875,\n",
       "        -8.1682,  -8.2055,  -8.2077,  -7.185 ,  -8.1043,  -7.3306,\n",
       "        -6.4894,  -7.1984,  -8.1873,  -7.2337,  -5.3436,  -5.6335,\n",
       "        -6.3722,  -6.9443,  -8.0653,  -7.399 ,  -8.0409,  -7.162 ,\n",
       "        -6.7042,  -6.7451,  -8.4139,  -7.8608,  -9.1986, -10.0333,\n",
       "        -8.9892,  -8.3495,  -8.3838,  -8.1975,  -9.1673,  -7.9001,\n",
       "        -8.3703,  -7.814 ,  -7.1834,  -7.395 ,  -8.2213,  -8.9679,\n",
       "        -9.4013,  -9.8885, -10.7669, -10.3194, -10.8326, -10.9494,\n",
       "        -9.4166,  -9.2326,  -7.7101,  -6.6119,  -5.4951,  -7.0867,\n",
       "        -5.7921,  -4.3815,  -5.4186,  -4.6074,  -3.9313,  -2.4835,\n",
       "        -4.9637,  -4.3415,  -3.5753,  -3.0299,  -3.6286,  -4.9849,\n",
       "        -5.0174,  -4.0941,  -4.4568,  -4.8949,  -5.8008,  -7.7296,\n",
       "        -7.8051,  -7.5485,  -7.3087,  -5.9165,  -6.1425,  -5.15  ,\n",
       "        -6.153 ,  -5.224 ,  -5.3876,  -5.2245,  -3.6728,  -4.3849,\n",
       "        -5.335 ,  -6.172 ,  -7.3586,  -7.3196,  -9.133 ,  -9.4567,\n",
       "        -9.5851, -11.7959, -10.8495, -10.7126, -10.539 ,  -9.5672,\n",
       "       -10.4548, -10.2174, -10.5648, -10.7874, -12.2021, -11.7125,\n",
       "       -12.6212, -12.3243, -12.3743, -13.6874, -13.1414, -12.4365,\n",
       "       -10.9089, -10.9928, -10.9261, -10.2239, -10.682 , -11.796 ,\n",
       "       -10.9665,  -9.0965,  -8.202 ,  -7.9098,  -8.3144,  -8.5936,\n",
       "        -8.3483,  -9.2295, -10.1095, -10.1635, -11.4588, -12.6961,\n",
       "       -13.4436, -13.3509, -13.5643, -11.6373, -11.9337, -10.2772,\n",
       "       -10.1955, -10.6751, -11.1035, -10.672 , -10.4738, -10.8345,\n",
       "       -11.1845, -10.9909,  -9.6997,  -7.4239,  -6.2776,  -6.121 ,\n",
       "        -5.6579,  -6.2515,  -5.22  ,  -5.7231,  -4.5588,  -3.9242,\n",
       "        -4.8601,  -5.1814,  -6.5558,  -7.1581,  -7.4178,  -7.0259,\n",
       "        -9.0099,  -9.3585, -10.2798, -12.0589, -10.7535, -10.9094,\n",
       "        -9.7692, -10.9938, -11.3276, -10.8168, -11.3966, -10.6777,\n",
       "       -10.8922,  -9.2215,  -9.6645,  -7.2623,  -5.6793,  -5.0125,\n",
       "        -3.3837,  -3.918 ,  -2.2309,  -2.853 ,  -2.2538,  -2.2326,\n",
       "        -3.2338,  -2.8792,  -2.2688,  -3.6128,  -3.8163,  -4.9619,\n",
       "        -5.3141,  -4.7391,  -4.0583,  -5.9923,  -5.5045,  -5.9377,\n",
       "        -6.3071,  -7.4469,  -8.9576,  -9.3455, -10.1436,  -8.8861,\n",
       "        -7.4825,  -8.2081,  -8.9043,  -8.919 ,  -9.6322, -10.4786,\n",
       "       -10.6947, -11.0324, -12.3412, -12.2536, -12.8641, -12.838 ,\n",
       "       -11.5396, -12.5079, -12.1708, -12.915 , -13.8497, -14.752 ,\n",
       "       -12.8052, -13.8582, -13.8333, -14.4114, -14.2181, -12.8203,\n",
       "        -9.4536, -11.8259, -10.9748,  -9.642 ,  -9.1286,  -8.0404,\n",
       "        -6.6943,  -6.1668,  -7.096 ,  -8.1619,  -7.1039,  -8.7762,\n",
       "        -9.6441, -10.262 ,  -9.6581, -10.318 , -11.1513, -11.1743,\n",
       "       -11.5848, -10.878 , -10.2077, -10.8381, -11.0384, -11.5831,\n",
       "       -11.6704, -10.5749, -10.8485,  -9.6699, -11.806 , -10.6067,\n",
       "       -10.1631, -12.1029, -12.2894, -14.8189, -12.9578, -11.233 ,\n",
       "       -10.7824, -12.0767, -12.0588, -13.931 , -13.2313, -12.638 ,\n",
       "       -11.7797, -13.8291, -14.9751, -15.0142, -15.4584, -15.955 ,\n",
       "       -15.5481, -15.7305, -16.6795, -15.126 , -16.7912, -18.5203,\n",
       "       -16.7892, -16.7207, -15.6593, -15.4613, -15.6576, -17.1845,\n",
       "       -16.1747, -15.1126, -14.5664, -15.4676, -14.0069, -13.2707,\n",
       "       -13.504 , -12.9435, -13.0897, -13.201 , -14.0423, -12.9895,\n",
       "       -14.1733, -14.7827, -15.1528, -15.4577, -15.3766, -15.2978,\n",
       "       -14.2337, -14.3521, -14.482 , -15.259 , -15.7097, -16.1003,\n",
       "       -16.8308, -17.3367, -16.5109, -15.5832, -16.4406, -13.9751,\n",
       "       -12.9611, -13.3293, -15.3247, -15.2958, -15.2366, -15.0443,\n",
       "       -15.1263, -14.7203, -12.7063, -10.7823, -10.7897, -11.1318,\n",
       "       -11.876 , -10.6933, -10.9137, -10.6838, -11.2584, -11.6553,\n",
       "       -11.9893, -12.1307, -12.4286, -13.3771, -13.2246, -14.321 ,\n",
       "       -13.0966, -13.3416, -14.2164, -14.7901, -13.6875, -12.5085,\n",
       "       -14.2931, -14.9923, -16.9672, -16.3965, -16.7583, -16.9105,\n",
       "       -16.3641, -15.3238, -16.9258, -17.5376, -18.1562, -19.1265,\n",
       "       -18.2888, -18.9269, -19.2016, -17.9914, -18.3678, -17.5095,\n",
       "       -16.531 , -15.3547, -15.5423, -14.0328, -15.0683, -14.8676,\n",
       "       -17.837 , -17.6895, -18.4318, -17.9594, -17.4965, -17.0205,\n",
       "       -16.5756, -17.3677, -16.8759, -17.3819, -17.8144, -16.7884,\n",
       "       -18.1615, -16.9886, -15.9961, -16.7924, -16.4431, -14.1839,\n",
       "       -12.1201, -11.921 , -14.1974, -13.4809, -15.0307, -13.5987,\n",
       "       -14.6101, -13.2934, -12.6972, -12.799 , -13.8921, -15.0803,\n",
       "       -15.0957, -16.4075, -15.1069, -15.523 , -15.2048, -16.2697,\n",
       "       -16.6553, -17.0223, -16.0714, -16.3392, -15.3825, -16.3518,\n",
       "       -16.189 , -17.3939, -16.4412, -18.1204, -16.7319, -17.0756,\n",
       "       -17.3887, -17.9761, -18.0337, -18.7181, -19.3025, -16.9642,\n",
       "       -18.1895, -18.1111, -19.0953, -19.4309, -19.5923, -19.7199,\n",
       "       -21.4331, -20.7534, -21.2445, -22.411 , -20.0803, -20.2584,\n",
       "       -20.4152, -22.2011, -21.469 , -22.395 , -22.2964, -20.6427,\n",
       "       -22.7343, -22.445 , -21.3887, -22.4565, -21.684 , -21.5311,\n",
       "       -22.2691, -23.0479, -22.3264, -21.9711, -22.3197, -22.8322,\n",
       "       -24.596 , -24.5594, -25.635 , -25.0052, -24.8219, -23.4295,\n",
       "       -25.6706, -24.4249, -24.6368, -24.4275, -25.8873, -26.3601,\n",
       "       -25.7737, -28.5224, -30.4591, -31.7447, -32.0075, -32.4682,\n",
       "       -32.9951, -33.083 , -33.2851, -32.368 , -31.3864, -31.1058,\n",
       "       -31.6785, -32.1989, -32.9756, -33.964 , -33.4268, -33.2943,\n",
       "       -32.9328, -31.5843, -32.327 , -31.1964, -30.7137, -30.7656,\n",
       "       -30.0186, -29.3363, -30.0648, -30.6117, -30.5107, -30.3713,\n",
       "       -30.2747, -30.6048, -29.8765, -29.5484, -27.0173, -26.5796,\n",
       "       -27.5322, -26.74  , -26.6147, -27.639 , -26.4981, -26.3848,\n",
       "       -26.178 , -27.6381, -29.1617, -29.7522, -30.0763, -29.944 ,\n",
       "       -29.8462, -28.6017, -28.6502, -29.7421, -30.4804, -30.3645,\n",
       "       -30.3483, -31.5913, -33.5605, -34.7019, -34.2963, -34.8175,\n",
       "       -35.6307, -36.0922, -34.9325, -35.2402, -34.571 , -34.1737,\n",
       "       -33.5611, -32.18  , -32.2225, -31.0404, -30.8873, -30.8115,\n",
       "       -30.1959, -32.1882, -31.2251, -31.1227, -30.7633, -30.4075,\n",
       "       -31.2069, -30.086 , -30.3478, -30.8219, -30.934 , -31.2191,\n",
       "       -31.3556, -30.0699, -29.3164, -29.2629, -29.6183, -28.8276,\n",
       "       -27.5528, -27.3192, -28.6352, -27.2391, -26.9024, -26.2975,\n",
       "       -25.6222, -25.6825, -23.8806, -24.2157, -24.9698, -24.3191,\n",
       "       -23.9537, -22.5865, -22.6922, -22.694 , -22.3772, -22.8898,\n",
       "       -22.9425, -23.3997, -20.9469, -21.9978, -22.1699, -21.3169,\n",
       "       -21.6731, -22.0601, -21.1785, -20.1112, -19.0315, -17.3892,\n",
       "       -17.4929, -18.3758, -18.5732, -17.2365, -16.3097, -16.8369,\n",
       "       -16.2031, -16.0491, -16.5769, -15.7617, -16.4396, -17.9062,\n",
       "       -16.9491, -16.5717, -16.955 , -15.853 , -14.6319, -14.9584,\n",
       "       -14.2084, -13.6043, -12.5153, -12.264 , -13.716 , -12.0629,\n",
       "       -12.5414, -12.5521, -13.6129, -15.1158, -17.0621, -16.0485,\n",
       "       -16.0111, -15.8778, -17.171 , -17.4935, -18.2765, -18.5798,\n",
       "       -18.4898, -18.1975, -17.0198, -16.1371, -14.9863, -15.9835,\n",
       "       -15.937 , -16.5474, -16.9424, -15.7425, -16.1943, -16.3497,\n",
       "       -16.5032, -16.492 , -16.5426, -16.1224, -14.9314, -13.3699,\n",
       "       -14.5028, -14.4057, -15.4373, -15.4819, -15.7001, -14.9271,\n",
       "       -15.6558, -15.4403, -17.497 , -18.7457, -17.4788, -16.7567,\n",
       "       -17.7113, -16.768 , -15.5753, -14.5395, -13.5081, -13.3284,\n",
       "       -13.9536, -12.1995, -11.5344, -10.5383,  -9.2843,  -9.3558,\n",
       "        -8.2156,  -8.355 ,  -8.2249,  -7.5515,  -7.9906,  -8.4408,\n",
       "        -6.8972,  -7.0721,  -8.8391,  -7.4439,  -8.1567,  -7.5358,\n",
       "        -8.0263,  -9.4428,  -9.2102,  -7.0478,  -7.7516,  -8.4553,\n",
       "        -7.6437,  -6.9594,  -8.2978,  -6.4171,  -5.089 ,  -5.4377,\n",
       "        -5.9908,  -5.4884,  -3.9442,  -4.5185,  -3.628 ,  -4.6036,\n",
       "        -3.6668,  -3.6255,  -4.0913,  -4.5465,  -3.5464,  -4.2678,\n",
       "        -4.4891,  -2.2678,  -2.5931,  -3.3517,  -5.1867,  -6.2944,\n",
       "        -5.3321,  -5.6329,  -4.3312,  -3.2954,  -2.8173,  -3.0014,\n",
       "        -4.3759,  -4.0486,  -4.993 ,  -6.6633,  -6.3386,  -5.3061,\n",
       "        -4.252 ,  -5.5298,  -4.8852,  -4.0784,  -4.5828,  -5.8099,\n",
       "        -5.8337,  -6.7827,  -8.3703,  -7.3677,  -9.2387,  -8.1619,\n",
       "        -8.7501,  -9.0887,  -9.3249, -10.7526, -12.2481, -13.5388,\n",
       "       -13.9329, -14.8836, -14.264 , -14.4619, -15.9852, -16.7858,\n",
       "       -17.1855, -18.2378, -18.0122, -16.9573, -16.7417, -16.6358,\n",
       "       -17.4299, -17.1046, -16.756 , -16.2651, -16.3041, -15.5202,\n",
       "       -14.8288, -14.6475, -16.209 , -16.0731, -15.7325, -15.4071,\n",
       "       -14.3387, -11.7271, -11.194 , -11.5095, -12.5764, -11.0787,\n",
       "       -11.6053, -12.7982, -14.5063, -13.8507, -14.6442, -14.5574,\n",
       "       -14.6687, -13.7971, -15.036 , -14.2663, -15.74  , -16.4779,\n",
       "       -16.0926, -18.5836, -19.8082, -18.2851, -18.5547, -19.4343,\n",
       "       -18.7962, -19.591 , -20.1869, -20.0468, -20.441 , -20.911 ,\n",
       "       -20.288 , -19.8435, -18.8064, -19.6205, -21.4959, -21.2066,\n",
       "       -21.334 , -20.0302, -19.8319, -20.3504, -20.1174, -20.219 ,\n",
       "       -20.3039, -20.41  , -20.4682, -19.083 , -17.5541, -17.1332,\n",
       "       -17.2054, -16.6231, -17.2812, -17.4886, -13.9628, -13.6797,\n",
       "       -13.1351, -12.6729, -13.2419, -14.2404, -12.3229,  -9.7939,\n",
       "        -9.2382,  -9.4397,  -9.2159,  -9.6417,  -9.5635,  -9.8379,\n",
       "       -10.0987, -11.3665, -11.5012, -12.0185, -12.3589, -11.2696,\n",
       "       -11.1403, -10.1179, -10.5618, -11.2165, -10.8692, -12.0039,\n",
       "       -11.7664, -12.4343,  -9.7664,  -9.0296, -11.6955, -11.7935,\n",
       "       -10.597 , -10.7188, -10.3394,  -9.0201,  -7.4664,  -6.5179,\n",
       "        -5.6693,  -5.0268,  -6.0236,  -5.5957,  -4.9735,  -6.8774,\n",
       "        -6.04  ,  -5.1235,  -5.5996,  -5.0973,  -4.608 ,  -4.4128,\n",
       "        -3.9725,  -4.7223,  -4.4849,  -3.5442,  -4.995 ,  -4.2742,\n",
       "        -5.9962,  -4.6742,  -3.8149,  -4.1559,  -3.7691,  -4.1197,\n",
       "        -4.8714,  -5.1713,  -4.9353,  -5.666 ,  -6.0593,  -6.7311,\n",
       "        -7.156 ,  -8.2853,  -9.2513,  -8.3563,  -6.9685,  -7.6695,\n",
       "        -7.7938,  -8.    ,  -8.9784,  -9.3245, -11.2293, -10.5049,\n",
       "       -10.9556, -11.036 , -10.436 , -14.0819])"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = plt.figure()\n",
    "ax = fig.add_subplot(1, 1, 1)\n",
    "ax.plot(np.random.randn(1000).cumsum())\n",
    "np.random.randn(1000).cumsum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [],
   "source": [
    "ticks = ax.set_xticks([0, 250, 500, 750, 1000])#修改刻度\n",
    "labels = ax.set_xticklabels(['one', 'two', 'three', 'four', 'five'],\n",
    "                            rotation=30, fontsize='small')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5, 1.0, 'My first matplotlib plot')"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "text/plain": [
       "Text(0.5, 3.200000000000003, 'Stages')"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ax.set_title('My first matplotlib plot')\n",
    "ax.set_xlabel('Stages')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "props = {\n",
    "    'title': 'My first matplotlib plot',\n",
    "    'xlabel': 'Stages'\n",
    "}\n",
    "ax.set(**props)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Adding legends"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "添加图标"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x246599c8160>]"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x246599c87f0>]"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x246599c8be0>]"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "from numpy.random import randn\n",
    "fig = plt.figure(); ax = fig.add_subplot(1, 1, 1)\n",
    "ax.plot(randn(1000).cumsum(), 'k', label='one')\n",
    "ax.plot(randn(1000).cumsum(), 'k--', label='two')\n",
    "ax.plot(randn(1000).cumsum(), 'k.', label='three')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x24659e88340>"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ax.legend(loc='best')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Annotations and Drawing on a Subplot"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "ax.text(x, y, 'Hello world!',\n",
    "        family='monospace', fontsize=10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:xlabel='Date'>"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "text/plain": [
       "Text(2007-10-11 00:00:00, 1779.41, 'Peak of bull market')"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "text/plain": [
       "Text(2008-03-12 00:00:00, 1533.77, 'Bear Stearns Fails')"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "text/plain": [
       "Text(2008-09-15 00:00:00, 1417.7, 'Lehman Bankruptcy')"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "text/plain": [
       "(13514.0, 14975.0)"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "text/plain": [
       "(600.0, 1800.0)"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "text/plain": [
       "Text(0.5, 1.0, 'Important dates in the 2008-2009 financial crisis')"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "from datetime import datetime\n",
    "\n",
    "fig = plt.figure()\n",
    "ax = fig.add_subplot(1, 1, 1)\n",
    "\n",
    "data = pd.read_csv('examples/spx.csv', index_col=0, parse_dates=True)##important\n",
    "spx = data['SPX']\n",
    "\n",
    "spx.plot(ax=ax, style='k-')\n",
    "\n",
    "crisis_data = [\n",
    "    (datetime(2007, 10, 11), 'Peak of bull market'),\n",
    "    (datetime(2008, 3, 12), 'Bear Stearns Fails'),\n",
    "    (datetime(2008, 9, 15), 'Lehman Bankruptcy')\n",
    "]\n",
    "\n",
    "for date, label in crisis_data:\n",
    "    ax.annotate(label, xy=(date, spx.asof(date)+ 75 ),#标注点函数 spx.asof(date)+ 75是坐标来的\n",
    "                xytext=(date, spx.asof(date) + 225),#spx.asof(date) + 225 箭头的坐标\n",
    "                arrowprops=dict(facecolor='black', headwidth=4, width=2,\n",
    "                                headlength=4),\n",
    "                horizontalalignment='left', verticalalignment='top')#important\n",
    "\n",
    "# Zoom in on 2007-2010\n",
    "ax.set_xlim(['1/1/2007', '1/1/2011'])#设置刻度的初值值和末值，太小会显示不全\n",
    "ax.set_ylim([600, 1800])\n",
    "\n",
    "ax.set_title('Important dates in the 2008-2009 financial crisis')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5, 1.0, 'Important dates in the 2008–2009 financial crisis')"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ax.set_title('Important dates in the 2008–2009 financial crisis')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "fig = plt.figure()\n",
    "ax = fig.add_subplot(1, 1, 1)\n",
    "\n",
    "rect = plt.Rectangle((0.2, 0.75), 0.4, 0.15, color='k', alpha=0.3)\n",
    "circ = plt.Circle((0.7, 0.2), 0.15, color='b', alpha=0.3)\n",
    "pgon = plt.Polygon([[0.15, 0.15], [0.35, 0.4], [0.2, 0.6]],\n",
    "                   color='g', alpha=0.5)\n",
    "\n",
    "ax.add_patch(rect)\n",
    "ax.add_patch(circ)\n",
    "ax.add_patch(pgon)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.patches.Rectangle at 0x2465bb0fca0>"
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "text/plain": [
       "<matplotlib.patches.Circle at 0x2465bb367f0>"
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "text/plain": [
       "<matplotlib.patches.Polygon at 0x2465bb0f2e0>"
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = plt.figure(figsize=(12, 6)); ax = fig.add_subplot(1, 1, 1)\n",
    "rect = plt.Rectangle((0.2, 0.75), 0.4, 0.15, color='k', alpha=0.3)\n",
    "circ = plt.Circle((0.7, 0.2), 0.15, color='b', alpha=0.3)\n",
    "pgon = plt.Polygon([[0.15, 0.15], [0.35, 0.4], [0.2, 0.6]],\n",
    "                   color='g', alpha=0.5)\n",
    "ax.add_patch(rect)#important\n",
    "ax.add_patch(circ)\n",
    "ax.add_patch(pgon)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Saving Plots to File"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "plt.savefig('figpath.svg')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "plt.savefig('figpath.png', dpi=400, bbox_inches='tight')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "from io import BytesIO\n",
    "buffer = BytesIO()\n",
    "plt.savefig(buffer)\n",
    "plot_data = buffer.getvalue()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### matplotlib Configuration"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "plt.rc('figure', figsize=(10, 10))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "font_options = {'family' : 'monospace',\n",
    "                'weight' : 'bold',\n",
    "                'size'   : 'small'}\n",
    "plt.rc('font', **font_options)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Plotting with pandas and seaborn"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Line Plots"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [],
   "source": [
    "plt.close('all')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:>"
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "s = pd.Series(np.random.randn(10).cumsum(), index=np.arange(0, 100, 10))\n",
    "s.plot()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:>"
      ]
     },
     "execution_count": 50,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "df = pd.DataFrame(np.random.randn(10, 4).cumsum(0),#随机数据,4组数据，各10个\n",
    "                  columns=['A', 'B', 'C', 'D'],#列数，4组\n",
    "                  index=np.arange(0, 100, 10))#x轴间距，10个显示位\n",
    "df.plot()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Bar Plots"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:>"
      ]
     },
     "execution_count": 55,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:>"
      ]
     },
     "execution_count": 55,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 720x432 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, axes = plt.subplots(2, 1)#两行各一个表\n",
    "data = pd.Series(np.random.rand(16), index=list('abcdefghijklmnop'))#improtant\n",
    "data.plot.bar(ax=axes[0], color='k', alpha=0.1)#ax横纵显示，alpha亮度之类的\n",
    "data.plot.barh(ax=axes[1], color='k', alpha=0.7)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "metadata": {},
   "outputs": [],
   "source": [
    "np.random.seed(12348)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "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>Genus</th>\n",
       "      <th>A</th>\n",
       "      <th>B</th>\n",
       "      <th>C</th>\n",
       "      <th>D</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>one</th>\n",
       "      <td>0.876389</td>\n",
       "      <td>0.894607</td>\n",
       "      <td>0.085044</td>\n",
       "      <td>0.039055</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>two</th>\n",
       "      <td>0.169830</td>\n",
       "      <td>0.878143</td>\n",
       "      <td>0.098347</td>\n",
       "      <td>0.421108</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>three</th>\n",
       "      <td>0.957890</td>\n",
       "      <td>0.533165</td>\n",
       "      <td>0.691877</td>\n",
       "      <td>0.315516</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>four</th>\n",
       "      <td>0.686501</td>\n",
       "      <td>0.834626</td>\n",
       "      <td>0.018288</td>\n",
       "      <td>0.750144</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>five</th>\n",
       "      <td>0.988861</td>\n",
       "      <td>0.748166</td>\n",
       "      <td>0.280444</td>\n",
       "      <td>0.789279</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>six</th>\n",
       "      <td>0.103226</td>\n",
       "      <td>0.447894</td>\n",
       "      <td>0.908596</td>\n",
       "      <td>0.293614</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "Genus         A         B         C         D\n",
       "one    0.876389  0.894607  0.085044  0.039055\n",
       "two    0.169830  0.878143  0.098347  0.421108\n",
       "three  0.957890  0.533165  0.691877  0.315516\n",
       "four   0.686501  0.834626  0.018288  0.750144\n",
       "five   0.988861  0.748166  0.280444  0.789279\n",
       "six    0.103226  0.447894  0.908596  0.293614"
      ]
     },
     "execution_count": 60,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:>"
      ]
     },
     "execution_count": 60,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "df = pd.DataFrame(np.random.rand(6, 4),\n",
    "                  index=['one', 'two', 'three', 'four', 'five', 'six'],\n",
    "                  columns=pd.Index(['A', 'B', 'C', 'D'], name='Genus'))\n",
    "df\n",
    "df.plot.bar()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Figure size 720x432 with 0 Axes>"
      ]
     },
     "execution_count": 61,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "text/plain": [
       "<Figure size 720x432 with 0 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:>"
      ]
     },
     "execution_count": 64,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 720x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "df.plot.barh(stacked=True, alpha=0.5)#stacked堆在一起"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "metadata": {},
   "outputs": [],
   "source": [
    "plt.close('all')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 71,
   "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>size</th>\n",
       "      <th>1</th>\n",
       "      <th>2</th>\n",
       "      <th>3</th>\n",
       "      <th>4</th>\n",
       "      <th>5</th>\n",
       "      <th>6</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>day</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>Fri</th>\n",
       "      <td>1</td>\n",
       "      <td>16</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Sat</th>\n",
       "      <td>2</td>\n",
       "      <td>53</td>\n",
       "      <td>18</td>\n",
       "      <td>13</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Sun</th>\n",
       "      <td>0</td>\n",
       "      <td>39</td>\n",
       "      <td>15</td>\n",
       "      <td>18</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Thur</th>\n",
       "      <td>1</td>\n",
       "      <td>48</td>\n",
       "      <td>4</td>\n",
       "      <td>5</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "size  1   2   3   4  5  6\n",
       "day                      \n",
       "Fri   1  16   1   1  0  0\n",
       "Sat   2  53  18  13  1  0\n",
       "Sun   0  39  15  18  3  1\n",
       "Thur  1  48   4   5  1  3"
      ]
     },
     "execution_count": 71,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "tips = pd.read_csv('examples/tips.csv')\n",
    "party_counts = pd.crosstab(tips['day'], tips['size'])# Crosstab 交叉列表取值\n",
    "party_counts\n",
    "# Not many 1- and 6-person parties\n",
    "party_counts = party_counts.loc[:, 2:5]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 73,
   "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>size</th>\n",
       "      <th>2</th>\n",
       "      <th>3</th>\n",
       "      <th>4</th>\n",
       "      <th>5</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>day</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Fri</th>\n",
       "      <td>16</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Sat</th>\n",
       "      <td>53</td>\n",
       "      <td>18</td>\n",
       "      <td>13</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Sun</th>\n",
       "      <td>39</td>\n",
       "      <td>15</td>\n",
       "      <td>18</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Thur</th>\n",
       "      <td>48</td>\n",
       "      <td>4</td>\n",
       "      <td>5</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "size   2   3   4  5\n",
       "day                \n",
       "Fri   16   1   1  0\n",
       "Sat   53  18  13  1\n",
       "Sun   39  15  18  3\n",
       "Thur  48   4   5  1"
      ]
     },
     "execution_count": 73,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "party_counts = party_counts.loc[:, 2:5]\n",
    "party_counts"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 77,
   "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>size</th>\n",
       "      <th>2</th>\n",
       "      <th>3</th>\n",
       "      <th>4</th>\n",
       "      <th>5</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>day</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Fri</th>\n",
       "      <td>0.888889</td>\n",
       "      <td>0.055556</td>\n",
       "      <td>0.055556</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Sat</th>\n",
       "      <td>0.623529</td>\n",
       "      <td>0.211765</td>\n",
       "      <td>0.152941</td>\n",
       "      <td>0.011765</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Sun</th>\n",
       "      <td>0.520000</td>\n",
       "      <td>0.200000</td>\n",
       "      <td>0.240000</td>\n",
       "      <td>0.040000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Thur</th>\n",
       "      <td>0.827586</td>\n",
       "      <td>0.068966</td>\n",
       "      <td>0.086207</td>\n",
       "      <td>0.017241</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "size         2         3         4         5\n",
       "day                                         \n",
       "Fri   0.888889  0.055556  0.055556  0.000000\n",
       "Sat   0.623529  0.211765  0.152941  0.011765\n",
       "Sun   0.520000  0.200000  0.240000  0.040000\n",
       "Thur  0.827586  0.068966  0.086207  0.017241"
      ]
     },
     "execution_count": 77,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:xlabel='day'>"
      ]
     },
     "execution_count": 77,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Normalize to sum to 1\n",
    "party_pcts = party_counts.div(party_counts.sum(1), axis=0)#进行规格化，使得各行的和为 1，并生成图表\n",
    "party_pcts\n",
    "party_pcts.plot.bar()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 78,
   "metadata": {},
   "outputs": [],
   "source": [
    "plt.close('all')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 81,
   "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>total_bill</th>\n",
       "      <th>tip</th>\n",
       "      <th>smoker</th>\n",
       "      <th>day</th>\n",
       "      <th>time</th>\n",
       "      <th>size</th>\n",
       "      <th>tip_pct</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>16.99</td>\n",
       "      <td>1.01</td>\n",
       "      <td>No</td>\n",
       "      <td>Sun</td>\n",
       "      <td>Dinner</td>\n",
       "      <td>2</td>\n",
       "      <td>0.063204</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>10.34</td>\n",
       "      <td>1.66</td>\n",
       "      <td>No</td>\n",
       "      <td>Sun</td>\n",
       "      <td>Dinner</td>\n",
       "      <td>3</td>\n",
       "      <td>0.191244</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>21.01</td>\n",
       "      <td>3.50</td>\n",
       "      <td>No</td>\n",
       "      <td>Sun</td>\n",
       "      <td>Dinner</td>\n",
       "      <td>3</td>\n",
       "      <td>0.199886</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>23.68</td>\n",
       "      <td>3.31</td>\n",
       "      <td>No</td>\n",
       "      <td>Sun</td>\n",
       "      <td>Dinner</td>\n",
       "      <td>2</td>\n",
       "      <td>0.162494</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>24.59</td>\n",
       "      <td>3.61</td>\n",
       "      <td>No</td>\n",
       "      <td>Sun</td>\n",
       "      <td>Dinner</td>\n",
       "      <td>4</td>\n",
       "      <td>0.172069</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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>239</th>\n",
       "      <td>29.03</td>\n",
       "      <td>5.92</td>\n",
       "      <td>No</td>\n",
       "      <td>Sat</td>\n",
       "      <td>Dinner</td>\n",
       "      <td>3</td>\n",
       "      <td>0.256166</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>240</th>\n",
       "      <td>27.18</td>\n",
       "      <td>2.00</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Sat</td>\n",
       "      <td>Dinner</td>\n",
       "      <td>2</td>\n",
       "      <td>0.079428</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>241</th>\n",
       "      <td>22.67</td>\n",
       "      <td>2.00</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Sat</td>\n",
       "      <td>Dinner</td>\n",
       "      <td>2</td>\n",
       "      <td>0.096759</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>242</th>\n",
       "      <td>17.82</td>\n",
       "      <td>1.75</td>\n",
       "      <td>No</td>\n",
       "      <td>Sat</td>\n",
       "      <td>Dinner</td>\n",
       "      <td>2</td>\n",
       "      <td>0.108899</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>243</th>\n",
       "      <td>18.78</td>\n",
       "      <td>3.00</td>\n",
       "      <td>No</td>\n",
       "      <td>Thur</td>\n",
       "      <td>Dinner</td>\n",
       "      <td>2</td>\n",
       "      <td>0.190114</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>244 rows × 7 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     total_bill   tip smoker   day    time  size   tip_pct\n",
       "0         16.99  1.01     No   Sun  Dinner     2  0.063204\n",
       "1         10.34  1.66     No   Sun  Dinner     3  0.191244\n",
       "2         21.01  3.50     No   Sun  Dinner     3  0.199886\n",
       "3         23.68  3.31     No   Sun  Dinner     2  0.162494\n",
       "4         24.59  3.61     No   Sun  Dinner     4  0.172069\n",
       "..          ...   ...    ...   ...     ...   ...       ...\n",
       "239       29.03  5.92     No   Sat  Dinner     3  0.256166\n",
       "240       27.18  2.00    Yes   Sat  Dinner     2  0.079428\n",
       "241       22.67  2.00    Yes   Sat  Dinner     2  0.096759\n",
       "242       17.82  1.75     No   Sat  Dinner     2  0.108899\n",
       "243       18.78  3.00     No  Thur  Dinner     2  0.190114\n",
       "\n",
       "[244 rows x 7 columns]"
      ]
     },
     "execution_count": 81,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "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>total_bill</th>\n",
       "      <th>tip</th>\n",
       "      <th>smoker</th>\n",
       "      <th>day</th>\n",
       "      <th>time</th>\n",
       "      <th>size</th>\n",
       "      <th>tip_pct</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>16.99</td>\n",
       "      <td>1.01</td>\n",
       "      <td>No</td>\n",
       "      <td>Sun</td>\n",
       "      <td>Dinner</td>\n",
       "      <td>2</td>\n",
       "      <td>0.063204</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>10.34</td>\n",
       "      <td>1.66</td>\n",
       "      <td>No</td>\n",
       "      <td>Sun</td>\n",
       "      <td>Dinner</td>\n",
       "      <td>3</td>\n",
       "      <td>0.191244</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>21.01</td>\n",
       "      <td>3.50</td>\n",
       "      <td>No</td>\n",
       "      <td>Sun</td>\n",
       "      <td>Dinner</td>\n",
       "      <td>3</td>\n",
       "      <td>0.199886</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>23.68</td>\n",
       "      <td>3.31</td>\n",
       "      <td>No</td>\n",
       "      <td>Sun</td>\n",
       "      <td>Dinner</td>\n",
       "      <td>2</td>\n",
       "      <td>0.162494</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>24.59</td>\n",
       "      <td>3.61</td>\n",
       "      <td>No</td>\n",
       "      <td>Sun</td>\n",
       "      <td>Dinner</td>\n",
       "      <td>4</td>\n",
       "      <td>0.172069</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   total_bill   tip smoker  day    time  size   tip_pct\n",
       "0       16.99  1.01     No  Sun  Dinner     2  0.063204\n",
       "1       10.34  1.66     No  Sun  Dinner     3  0.191244\n",
       "2       21.01  3.50     No  Sun  Dinner     3  0.199886\n",
       "3       23.68  3.31     No  Sun  Dinner     2  0.162494\n",
       "4       24.59  3.61     No  Sun  Dinner     4  0.172069"
      ]
     },
     "execution_count": 81,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:xlabel='tip_pct', ylabel='day'>"
      ]
     },
     "execution_count": 81,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 720x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "import seaborn as sns\n",
    "tips\n",
    "tips['tip_pct'] = tips['tip'] / (tips['total_bill'] - tips['tip'])\n",
    "tips.head()\n",
    "sns.barplot(x='tip_pct', y='day', data=tips, orient='h')#画条形图"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [],
   "source": [
    "plt.close('all')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 82,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:xlabel='tip_pct', ylabel='day'>"
      ]
     },
     "execution_count": 82,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.barplot(x='tip_pct', y='day', hue='time', data=tips, orient='h')#x,y,hue:数据字段变量名"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 83,
   "metadata": {},
   "outputs": [],
   "source": [
    "plt.close('all')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 84,
   "metadata": {},
   "outputs": [],
   "source": [
    "sns.set(style=\"whitegrid\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Histograms and Density Plots"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 85,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Figure size 720x432 with 0 Axes>"
      ]
     },
     "execution_count": 85,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "text/plain": [
       "<Figure size 720x432 with 0 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 86,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:ylabel='Frequency'>"
      ]
     },
     "execution_count": 86,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAmAAAAFoCAYAAADw0EcgAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjMuMiwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy8vihELAAAACXBIWXMAAAsTAAALEwEAmpwYAAAdWUlEQVR4nO3df3AU5R3H8c+Ru5z8slSbgwxNY0uhVVPRpqOebXPS0RASbmIpIjBjpmodtE4QastgxFrxV+qPyWiRTmsdUMQqtlBCije2UtPa4KinFa+1wlgSQWi4liJCzSVctn843jQKyebH89zm8n7NdCZ7z97u9/jOEz99drPncxzHEQAAAKwZle0CAAAARhoCGAAAgGUEMAAAAMsIYAAAAJYRwAAAACzzZ7sAt7q7u3X06FEFAgH5fL5slwMAAHBCjuOoq6tLY8eO1ahRH1/vGjYB7OjRo9q5c2e2ywAAAHBt2rRpGj9+/MdeHzYBLBAISPrgg+Tn5w/qWIlEQiUlJUNRFgyhR95Hj7yPHnkfPfK+gfaos7NTO3fuzOSXjxo2AezDy475+fkKBoODPt5QHANm0SPvo0feR4+8jx5532B6dKLbprgJHwAAwDICGAAAgGUEMAAAAMsIYAAAAJYRwAAAACwjgAEAAFhGAAMAALCMAAYAAGAZAQwAAMAyAhgAAIBlBDAAAADLCGAAAACWEcAAAAAsI4BZ0NmVHtL9AADA8ObPdgEjQX4gT9EbNve535b7qi1UAwAAso0VMAAAAMsIYAAAAJYRwAAAACwjgAEAAFhGAAMAALCMAAYAAGAZAQwAAMAyAhgAAIBlBDAAAADLCGAAAACWEcAAAAAsI4ABAABYRgADAACwjAAGAABgGQEMAADAMgIYAACAZQQwAAAAywhgAAAAlvlNHfipp57SY489ltneu3evqqurddFFF+muu+5SKpXSrFmztHTpUlMlAAAAeJKxAHbppZfq0ksvlSTt2rVL1113na6++motWLBA69atU2FhoRYtWqTm5mZFIhFTZQAAAHiOlUuQP/rRj7R06VLt2bNHxcXFKioqkt/vVzQaVSwWs1ECAACAZxgPYC0tLero6NCsWbN04MABFRQUZMZCoZDa29tNlwAAAOApxi5BfuiJJ57QFVdcIUnq7u6Wz+fLjDmO02PbjUQiMSR1xePxITmOG6Wlpa73tVmX1/Fv4X30yPvokffRI+8z0SOjAayzs1MvvfSS6uvrJUmTJk1SMpnMjCeTSYVCoX4ds6SkRMFgcFB1xePxfoUim7xal21e7hE+QI+8jx55Hz3yvoH2KJVK9bpoZPQS5JtvvqnTTjtNY8aMkSRNnz5du3fvVltbm9LptJqamlRWVmayBAAAAM8xugK2Z88eTZo0KbMdDAZVX1+v2tpapVIpRSIRVVRUmCwBAADAc4wGsMrKSlVWVvZ4LRwOq7Gx0eRpAQAAPI0n4QMAAFhGAAMAALCMAAYAAGAZAQwAAMAyAhgAAIBlBDAAAADLCGAAAACWEcAAAAAsI4ABAABYRgADAACwjAAGAABgGQEMAADAMgIYAACAZQQwAAAAywhgAAAAlhHAAAAALCOAAQAAWEYAAwAAsIwABgAAYBkBDAAAwDICGAAAgGUEMAAAAMsIYAAAAJYRwAAAACwjgAEAAFhGAAMAALCMAAYAAGAZAQwAAMAyAhgAAIBlBDAAAADLCGAAAACWEcAAAAAsMxrAtm3bpjlz5mjWrFm6/fbbJUktLS2KRqMqLy9XQ0ODydMDAAB4krEAtmfPHt1yyy1avXq1Ghsb9be//U3Nzc2qq6vT6tWrtXXrViUSCTU3N5sqAQAAwJOMBbDf/e53qqys1KRJkxQIBNTQ0KDRo0eruLhYRUVF8vv9ikajisVipkoAAADwJL+pA7e1tSkQCOiaa67R/v37deGFF2rq1KkqKCjI7BMKhdTe3m6qBAAAAE8yFsDS6bRefvllrVu3TmPGjNG1116rk046ST6fL7OP4zg9tt1IJBJDUl88Hh+S47hRWlrqel+bdXkd/xbeR4+8jx55Hz3yPhM9MhbAPvWpTykcDuuUU06RJF100UWKxWLKy8vL7JNMJhUKhfp13JKSEgWDwUHVFo/H+xWKbPJqXbZ5uUf4AD3yPnrkffTI+wbao1Qq1euikbF7wGbMmKHnn39ehw8fVjqd1p/+9CdVVFRo9+7damtrUzqdVlNTk8rKykyVAAAA4EnGVsCmT5+u73znO1q4cKG6urr01a9+VQsWLNDnPvc51dbWKpVKKRKJqKKiwlQJAAAAnmQsgEnS3LlzNXfu3B6vhcNhNTY2mjwtAACAp/EkfAAAAMsIYAAAAJYRwAAAACwjgAEAAFhGAAMAALCMAAYAAGAZAQwAAMAyApiHdHalh3Q/AADgTUYfxIr+yQ/kKXrD5j7323JftYVqAACAKayAAQAAWEYAAwAAsIwABgAAYBkBDAAAwDICGAAAgGUEMAAAAMsIYAAAAJYRwAAAACwjgAEAAFhGAAMAALCMAAYAAGAZAQwAAMAyAhgAAIBlBDAAAADLCGAAAACWEcAAAAAsI4ABAABYRgADAACwjAAGAABgGQEMAADAMgIYAACAZQQwAAAAywhgAAAAlvlNHvzyyy/XwYMH5fd/cJqVK1fq6NGjuuuuu5RKpTRr1iwtXbrUZAkAAACeYyyAOY6j1tZW/eEPf8gEsI6ODlVUVGjdunUqLCzUokWL1NzcrEgkYqoMAAAAzzEWwP7xj39Ikq688kodOnRI8+bN07Rp01RcXKyioiJJUjQaVSwWI4ABAIARxdg9YIcPH1Y4HNaDDz6otWvX6oknntC+fftUUFCQ2ScUCqm9vd1UCQAAAJ5kbAXsnHPO0TnnnJPZnjt3rh544AGVlpZmXnMcRz6fr1/HTSQSQ1JfPB4fkuO48f+feajYrD9bRsJnHO7okffRI++jR95nokfGAtjLL7+srq4uhcNhSR+ErcmTJyuZTGb2SSaTCoVC/TpuSUmJgsHgoGqLx+NGQpFNw73+vuRCj3IdPfI+euR99Mj7BtqjVCrV66KRsUuQ7733nu6++26lUikdOXJEmzZt0ve+9z3t3r1bbW1tSqfTampqUllZmakSAAAAPMnYCtiMGTP02muv6ZJLLlF3d7cWLlyoc845R/X19aqtrVUqlVIkElFFRYWpEgAAADzJ6HPAlixZoiVLlvR4LRwOq7Gx0eRpAQAAPI0n4QMAAFhGAAMAALCMAAYAAGAZAQwAAMAyAhgAAIBlBDAAAADLCGAAAACWEcAAAAAsI4ABAABYRgADAACwzFUAW7dunY4cOWK6FgAAgBHBVQB78803NXPmTN100016/fXXTdcEAACQ01x9Gfftt9+uI0eOaMuWLbr11lvlOI4WLFigaDSqYDBoukYAAICc4voesHHjxqmiokKzZ8/WoUOH9Pjjj6uiokLbtm0zWR8AAEDOcbUCtn37dj355JPavn27Zs6cqQcffFBf/OIX9fbbb2vhwoX6xje+YbpOAACAnOEqgN16661auHChbrvtNo0fPz7z+mc+8xnNmzfPWHEAAAC5yNUlyMbGRk2YMEHjx49XMpnU2rVr1d3dLUlavHix0QIBAAByjasAdtttt+m555774A2jRikej+vOO+80WRcAAEDOcnUJ8tVXX1VTU5Mk6dRTT9X999+v6upqo4UBAADkKlcrYF1dXers7MxsHzt2zFhBAAAAuc7VCtiFF16oq666StXV1fL5fGpqalIkEjFdGwAAQE5yFcCWLVum9evX69lnn5Xf79fFF1+s+fPnm64NAAAgJ7kKYHl5eaqpqVFNTY3pegAAAHKeqwD2+9//XnfeeafeffddOY6Tef2VV14xVhgAAECuchXA7rnnHi1fvlxnnHGGfD6f6ZoAAABymqsAdvLJJ6u8vNx0LQAAACOCq8dQTJ8+Xc3NzaZrAQAAGBFcrYA1NzfrscceUyAQUCAQkOM48vl83AMGAAAwAK4C2Nq1aw2XAQAAMHK4ugQ5efJkvf7669qwYYNOOeUUvfrqq5o8ebLp2gAAAHKSqwD285//XL/85S8Vi8XU0dGhVatW6cEHHzRdGwAAQE5yFcB++9vf6qGHHtLo0aP1yU9+Uhs2bMh8OTcAAAD6x1UA8/v9ys/Pz2yffPLJ8vtd3T6mH//4x1q+fLkkqaWlRdFoVOXl5WpoaBhAuZCkzq70kO4HAADscpWiCgsL9dxzz8nn86mzs1MPP/ywq3vAtm/frk2bNunCCy9UR0eH6urqtG7dOhUWFmrRokVqbm7mS70HID+Qp+gNm/vcb8t91RaqAQAA/eVqBezmm2/WmjVr9Oabb+rss8/WH//4R9188829vufQoUNqaGjQNddcI0nasWOHiouLVVRUJL/fr2g0qlgsNvhPAAAAMMy4WgGbOHGiHnnkEb3//vtKp9MaN25cn+/54Q9/qKVLl2r//v2SpAMHDqigoCAzHgqF1N7ePsCyAQAAhi9XAWzNmjXHff2KK6447utPPfWUCgsLFQ6HtXHjRklSd3d3j++R/PBhrv2VSCT6/Z7jicfjQ3IcN0pLS62d66Nsfs6hNpxrHynokffRI++jR95nokeuAtjOnTszP3d2duqll15SOBw+4f5bt25VMplUdXW13n33Xf33v//VO++8o7y8vMw+yWRSoVCo3wWXlJQoGAz2+33/Lx6PZzUU2TRcP+dI6tFwRY+8jx55Hz3yvoH2KJVK9bpo5CqA3XXXXT2229vbddNNN51w//9fMdu4caNefPFF3XrrrSovL1dbW5s+/elPq6mpSd/61rfcnB4AACCnuHuWxEdMnDhR77zzTr/eEwwGVV9fr9raWqVSKUUiEVVUVAzk9AAAAMNav+8BcxxHiURCp556qqsTzJkzR3PmzJEkhcNhNTY2DqBMAACA3NHve8CkD54LtmzZMiMFAQAA5LoB3QMGAACAgXMVwC6//PJeHxnx6KOPDllBAAAAuc5VACspKdFbb72lefPmKRAIaPPmzTp27JiqqqpM1wcAAJBzXAWwV155RY8//njmOV5f//rXNW/ePM2cOdNocQAAALnI1XdBHjx4UKlUKrN99OhRdXR0GCsKAAAgl7laAZs9e7Yuu+wyXXzxxXIcR08//bRqampM1wYAAJCTXAWw66+/XmeccYZeeOEFBYNBrVy5Uueee67p2gAAAHKSq0uQ0gdPv586daqWLFmiQCBgsiYAAICc5iqA/frXv9aNN96oX/ziF3rvvff03e9+Vxs2bDBdGwAAQE5yFcAee+wxPfnkkxo3bpxOPfVUbdy4UY888ojp2gAAAHKSqwA2atQojRs3LrNdWFiYeSQFAAAA+sdVAJswYYLeeOONzNPwGxsb9YlPfMJoYQAAALnK1V9B1tXV6frrr9fbb7+tr33tawoGg1q9erXp2gAAAHKSqwDW0dGhzZs3q7W1Vel0Wp/97Gf5S0gAAIABcnUJ8vvf/77y8vI0ZcoUTZs2jfAFAAAwCK4C2Be+8AVt2bJF+/bt06FDhzL/AwAAQP+5ugT57LPPKhaL9XjN5/PpjTfeMFIUAABALnMVwF5//XXTdQAAAIwYvV6CvPnmmzM/Hzx40HgxAAAAI0GvASyRSGR+vuqqq4wXAwAAMBL0GsAcxznuzwAAABg4V38FKSnzFHwAAAAMTq834Xd3d+vdd9+V4zhKp9OZnz80YcIE0/V5VmdXWvkBvg8TAAD0X68BbOfOnTr//PMzoeu8887LjI30x1DkB/IUvWGzq3233FdtuBoAADCc9BrA/v73v9uqAwAAYMRwfQ8YAAAAhgYBDAAAwDICGAAAgGUEMAAAAMsIYAAAAJYRwAAAACwzGsDuv/9+VVZWqqqqSmvWrJEktbS0KBqNqry8XA0NDSZPDwAA4Em9PgdsMF588UW98MILamxs1LFjx1RZWalwOKy6ujqtW7dOhYWFWrRokZqbmxWJREyVAQAA4DnGVsDOPfdcPfroo/L7/fr3v/+tdDqtw4cPq7i4WEVFRfL7/YpGo4rFYqZKAAAA8CSjlyADgYAeeOABVVVVKRwO68CBAyooKMiMh0Ihtbe3mywBAADAc4xdgvzQ4sWLdfXVV+uaa65Ra2urfD5fZsxxnB7bbiQSiSGpKx6PD+r9paWlQ1KHaYP9nNk0nGsfKeiR99Ej76NH3meiR8YC2FtvvaXOzk6dfvrpGj16tMrLyxWLxZSXl5fZJ5lMKhQK9eu4JSUlCgaDg6otHo8PmwA1WMP1c46kHg1X9Mj76JH30SPvG2iPUqlUr4tGxi5B7t27VytWrFBnZ6c6Ozv17LPPav78+dq9e7fa2tqUTqfV1NSksrIyUyUAAAB4krEVsEgkoh07duiSSy5RXl6eysvLVVVVpVNOOUW1tbVKpVKKRCKqqKgwVQIAAIAnGb0HrLa2VrW1tT1eC4fDamxsNHlaAAAAT+NJ+AAAAJYRwAAAACwjgAEAAFhGAAMAALCMAAYAAGAZAQwAAMAyAhgAAIBlBDAAAADLCGAAAACWEcAAAAAsI4ABAABYRgADAACwjAAGAABgGQEMAADAMgIYAACAZQQwAAAAywhgAAAAlhHAAAAALCOAAQAAWEYAAwAAsIwABgAAYBkBDAAAwDICGAAAgGUEMAAAAMsIYAAAAJYRwAAAACwjgAEAAFhGAAMAALCMAAYAAGAZAQwAAMAyAhgAAIBlBDAAAADLjAawVatWqaqqSlVVVbr77rslSS0tLYpGoyovL1dDQ4PJ0wMAAHiSsQDW0tKi559/Xps2bdJvfvMb/fWvf1VTU5Pq6uq0evVqbd26VYlEQs3NzaZKAAAA8CRjAaygoEDLly9Xfn6+AoGApkyZotbWVhUXF6uoqEh+v1/RaFSxWMxUCQAAAJ5kLIBNnTpVZ599tiSptbVVTz/9tHw+nwoKCjL7hEIhtbe3myoBAADAk/ymT7Br1y4tWrRIy5YtU15enlpbWzNjjuPI5/P163iJRGJI6orH44N6f2lp6ZDUYdpgP2c2DefaRwp65H30yPvokfeZ6JHRABaPx7V48WLV1dWpqqpKL774opLJZGY8mUwqFAr165glJSUKBoODrmu4BKjBGq6fcyT1aLiiR95Hj7yPHnnfQHuUSqV6XTQydgly//79uu6663TvvfeqqqpKkjR9+nTt3r1bbW1tSqfTampqUllZmakSAAAAPMnYCtjDDz+sVCql+vr6zGvz589XfX29amtrlUqlFIlEVFFRYaoEAAAATzIWwFasWKEVK1Ycd6yxsdHUaQEAADyPJ+EDAABYRgADAACwjAAGAABgGQEMAADAMgIYAACAZQQwAAAAywhgAAAAlhHAAAAALCOAAQAAWEYAAwAAsIwABgAAYBkBDAAAwDICGAAAgGUEMAAAAMsIYAAAAJYRwHJYZ1d6SPcDAABDw5/tAmBOfiBP0Rs297nflvuqLVQDAAA+xAoYAACAZQQwAAAAywhgAAAAlhHAAAAALCOAAQAAWEYAAwAAsIwABgAAYBkBDAAAwDICGAAAgGUEMAAAAMsIYB/B9yICAADT+C7Ij+D7EwEAgGmsgAEAAFhGAAMAALDMaAA7cuSIZs+erb1790qSWlpaFI1GVV5eroaGBpOnBgAA8CxjAey1117TggUL1NraKknq6OhQXV2dVq9era1btyqRSKi5udnU6QEAADzLWADbsGGDbrnlFoVCIUnSjh07VFxcrKKiIvn9fkWjUcViMVOnBwAA8CxjfwV5xx139Ng+cOCACgoKMtuhUEjt7e2mTg8AAOBZ1h5D0d3dLZ/Pl9l2HKfHtluJRGJI6onH48d9vbS0dEiOP9yc6N8jm7xYE3qiR95Hj7yPHnmfiR5ZC2CTJk1SMpnMbCeTyczlyf4oKSlRMBgcVC3xeHzEBq0T8dq/Bz3yPnrkffTI++iR9w20R6lUqtdFI2uPoZg+fbp2796ttrY2pdNpNTU1qayszNbpAQAAPMPaClgwGFR9fb1qa2uVSqUUiURUUVFh6/QAAACeYTyAbdu2LfNzOBxWY2Oj6VMCAAB4Gk/CBwAAsIwABgAAYBkBDAAAwDICGAAAgGUEMAAAAMsIYAAAAJYRwAAAACwjgAEAAFhGAAMAALCMAAYAAGAZAQwAAMAyAhgAAIBlBDAAAADLCGAAAACWEcAAAAAsI4ABAABYRgADAACwjAAGAABgGQEMAADAMgIYAACAZQQwqLMrPaT7AQCA3vmzXQCyLz+Qp+gNm/vcb8t91RaqAQAg97ECBgAAYBkBDAAAwDICGFzjXjEAAIYG94DBNe4VAwBgaLACBgAAYBkBDAAAwDICGAAAgGUEMAAAAMsIYAAAAJYRwAAAACzLSgDbsmWLKisrVV5ervXr12ejBHjEiZ4ZVlpa6mo/r+AZaQCQff35HZvt38fWnwPW3t6uhoYGbdy4Ufn5+Zo/f77OO+88ff7zn7ddCjwgV54tliufAwCGM7e/i6Xs/z62vgLW0tKi888/XxMmTNCYMWM0c+ZMxWIx22UAAABkjfUVsAMHDqigoCCzHQqFtGPHjj7f5ziOJKmzs3NI6kilUiccmzA2z9X73ezXn31zab/+MHHMbMiVz9EfufZ5chE98j56NLT6899mtwbSow/zyof55aN8zolGDPnpT3+qVCqlJUuWSJI2bNigRCKhlStX9vq+9957Tzt37rRQIQAAwNCYNm2axo8f/7HXra+ATZo0SS+//HJmO5lMKhQK9fm+sWPHatq0aQoEAvL5fCZLBAAAGBTHcdTV1aWxY8ced9x6ALvgggv0k5/8RAcPHtTo0aP1zDPP6LbbbuvzfaNGjTpuggQAAPCik0466YRj1gPYxIkTtXTpUtXU1Kirq0tz587VWWedZbsMAACArLF+DxgAAMBIx5PwAQAALCOAAQAAWEYAAwAAsIwABgAAYBkBDAAAwLKcDWBbtmxRZWWlysvLtX79+o+Nv/HGG5ozZ45mzpypm266SceOHctClSNbXz1atWqVZsyYoerqalVXVx93H5h35MgRzZ49W3v37v3YGPPIG3rrEfMo+1atWqWqqipVVVXp7rvv/tg48yj7+uqRkXnk5KB//vOfzowZM5z//Oc/ztGjR51oNOrs2rWrxz5VVVXOq6++6jiO49x4443O+vXrs1DpyOWmR4sWLXJeeeWVLFUIx3Gcv/zlL87s2bOdM88809mzZ8/HxplH2ddXj5hH2fXnP//Zueyyy5xUKuV0dnY6NTU1zjPPPNNjH+ZRdrnpkYl5lJMrYC0tLTr//PM1YcIEjRkzRjNnzlQsFsuMv/POO+ro6NDZZ58tSZozZ06PcZjXV48kKZFI6Gc/+5mi0ahWrlzJF9ZmwYYNG3TLLbcc9+vCmEfe0FuPJOZRthUUFGj58uXKz89XIBDQlClTtG/fvsw48yj7+uqRZGYe5WQAO3DggAoKCjLboVBI7e3tJxwvKCjoMQ7z+urR0aNHdfrpp+sHP/iBNm3apMOHD2v16tXZKHVEu+OOO/SVr3zluGPMI2/orUfMo+ybOnVqJly1trbq6aefViQSyYwzj7Kvrx6Zmkc5GcC6u7t7fGG34zg9tvsah3l99WDs2LF66KGHNGXKFPn9fl155ZVqbm7ORqk4AeaR9zGPvGPXrl268sortWzZMp122mmZ15lH3nGiHpmaRzkZwCZNmqRkMpnZTiaTPZbnPzr+r3/964TL9zCjrx7t27dPv/rVrzLbjuPI77f+1aXoBfPI+5hH3hCPx/Xtb39bN9xwg775zW/2GGMeeUNvPTI1j3IygF1wwQXavn27Dh48qPfff1/PPPOMysrKMuOTJ09WMBhUPB6XJG3evLnHOMzrq0cnnXSS7rnnHu3Zs0eO42j9+vW6+OKLs1gxPop55H3Mo+zbv3+/rrvuOt17772qqqr62DjzKPv66pGpeZST/1do4sSJWrp0qWpqatTV1aW5c+fqrLPO0tVXX63FixfrS1/6ku69916tWLFCR44c0Zlnnqmamppslz2iuOnRypUrde2116qrq0tf/vKXdcUVV2S7bEjMo2GAeeQdDz/8sFKplOrr6zOvzZ8/X9u2bWMeeYSbHpmYRz7HcZxBHwUAAACu5eQlSAAAAC8jgAEAAFhGAAMAALCMAAYAAGAZAQwAAMAyAhgAAIBlBDAAAADLCGAAAACW/Q/VZzwncLSm5gAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 720x432 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "tips['tip_pct'].plot.hist(bins=50)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 87,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Figure size 720x432 with 0 Axes>"
      ]
     },
     "execution_count": 87,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "text/plain": [
       "<Figure size 720x432 with 0 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 89,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:ylabel='Density'>"
      ]
     },
     "execution_count": 89,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x432 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "tips['tip_pct'].plot.density()#密度图"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 90,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Figure size 720x432 with 0 Axes>"
      ]
     },
     "execution_count": 90,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "text/plain": [
       "<Figure size 720x432 with 0 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 91,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\ProgramData\\Anaconda3\\lib\\site-packages\\seaborn\\distributions.py:2551: FutureWarning: `distplot` is a deprecated function and will be removed in a future version. Please adapt your code to use either `displot` (a figure-level function with similar flexibility) or `histplot` (an axes-level function for histograms).\n",
      "  warnings.warn(msg, FutureWarning)\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:ylabel='Density'>"
      ]
     },
     "execution_count": 91,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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z5k2VhyMiIiLSVdWWNB8fH1y+fBmXLl2Ch4eH8nZ9fX107NhR1dmIiIiIdFa1Ja19+/Zo3749evbsCRsbG3VlIiIiItJ51Za0GTNmYO3atQgMDHzu+pSUFJWEIiIiItJ11Za0oKAgAMAnn3yiljBERERE9Fi1n+50cnICAHTr1g12dnbo1q0bCgsLceLECTg6OqolIBEREZEuqtEUHJ9++ikiIyPx999/Y8GCBcjKysK8efNUnY2IiIhIZ9WopGVmZmLRokX45Zdf8O6772LZsmW4deuWqrMRERER6awalTSFQgE9PT0cPXoUrq6uAIDi4mKVBiMiIiLSZTUqaS1atEBQUBCysrLQrVs3fPzxx2jTpo2qsxERERHprBpdu3PZsmX45Zdf0LlzZxgaGqJLly4YNmyYiqMRERER6a4alTQzMzN06dIFeXl5OHfuHJydnXH16lW0a9dO1fmIdIZUKoVMJgMAWFhYwNLSUthApLU41og0Q41K2tq1a/Htt9+icePGytskEgn+97//qSwYka6RyWRIS0sDALi5ufE/TlIZjjUizVCjkpacnIzU1FReGoqIiIhITWr0wQE7OzsWNCIiIiI1qtGZtO7du2PFihXo378/TExMlLfzPWlEREREqlGjkpaQkAAA2Lt3r/I2vieNiIiISHVqVNIOHDig6hxEREREVEGN3pNWUFCAJUuWICAgAFKpFJ9++ikKCgpUnY2IiIhIZ9WopH322WeoV68eHjx4AGNjY8hkMnz66aeqzkZERESks2pU0i5cuIDQ0FAYGBjA1NQUK1euxIULF1SdjYiIiEhn1aik6elV3qy8vPyZ24iIiIio7tTogwNdu3bFl19+ieLiYhw+fBgxMTF46623VJ2NiIiISGfV6HTYzJkzYWZmhnr16mHNmjVo27YtZs+erepsRERERDrrhWfSfvnlF2zZsgWXLl2CiYkJ2rRpAxcXFxgbG6sjHxEREZFOqrak/fzzzwgPD0dISAjatm0LiUSCs2fP4vPPP0dJSQnc3d3VlZOIiIhIp1Rb0rZt24aoqCg0bdpUeVvLli3RoUMHzJs3jyWNiIiISEWqLWkFBQWVCtoTr7/+OkpKSlQWioiI1E8qlUIulyMrKwsAYGFhAUtLS2FDEemwakuavr5+lesUCkWdhyEiIuHIZDKkpqbCwcEBAODm5saSRiQgTnZGREREJELVnkm7dOkSXFxcnrldoVDg0aNHKgtFREREpOuqLWm//PKLunIQERERUQXVlrRmzZqpKwcRERERVcD3pBERERGJEEsaERERkQixpBERERGJEEsaERERkQixpBERERGJEEsaERERkQixpBERERGJEEsaERERkQhVO5ktET3r0aNHOH/+PJKTk3Hnzh0UFxejQYMGsLKyQsuWLeHk5CR0RCIi0gIsaUQ1VFxcjJ9++gnHjx9HSUkJGjVqBEtLSzRs2BD6+vpIT0/H4cOHsXfvXvTt2xfOzs7Q0+PJaiIiejksaUQ1cO3aNXz11Ve4desWOnbsiG7dusHDwwNXrlwBALi4uOC3337DlStXcPjwYXz33Xc4cuQI/Pz8BE5ORESaiiWNtJZUKoVMJlMuW1hYwNLSstb7OX78OJKSkmBjY4OgoCC0atUKAJ45S2ZoaAhHR0eMHj0aW7ZsQXJyMr7++ms0bdr0lZ4HUcWx/DLj+OmfheLiYrVletXsRLqMJY20lkwmQ1pamnLZzc2t1v9BbN++HYmJiXB0dMTy5ctx4cKFF95HT08PnTt3hr29PaKiovDxxx9j9OjRaNeuXS2fAdFjFcfyy4zjp38WXFxc1JbpVbMT6TK+YYaoCmvWrMHXX38NZ2dnjBs3DqamprW6v42NDaZNm4aWLVtix44d+Pvvv1WUlIiItBFLGtFzJCcn48svv8SgQYMwevRo6Ovrv9R+zM3N8fnnn6Nx48aIjo7G1atX6zgpERFpK5Y0oqdcuHABH330Ebp164b58+e/8ic069evjwkTJsDY2Bjz5s1Dfn5+HSUlIiJtptKSlpKSAk9PT7i7u2PHjh1Vbjd79mwkJCQol2/fvg0/Pz8MHDgQU6ZMQUFBgSpjEinJZDLMnj0bjRo1QmRkJAwNDetkvw0bNsSECROQn5+PuLg4yOXyOtkvERFpL5WVtOzsbISHhyM2NhZJSUmIi4tTTldQcZvg4GDs27ev0u2LFy/GmDFjsHfvXjg5OSEiIkJVMYmUFAoFdu/eDalUiq1bt6JJkyZ1un87OztMnToVly9fxq+//lqn+yYiIu2jspKWnp4OV1dXWFpawszMDB4eHti7d2+lbVJSUtC/f38MGjRIeVtpaSlOnDgBDw8PAMDw4cOfuR+RKpw6dQrnz5/HlClTVHbVAE9PT7Rv3x779u3DP//8o5LHICIi7aCykpaTkwMrKyvlsrW1NbKzsyttExgYiPfee6/SbQ8fPoSFhQUMDB7PDmJlZfXM/YjqmlQqRXJyMl5//XWMGjVKZY8jkUgwYsQINGjQAPHx8Xj06JHKHouIiDSbyuZJk8vlkEgkymWFQlFpuSrP264m96soMzOzVttrm4yMDKEjiIJcLseNGzeUy3fu3Hlu4S8vL0dMTAzKy8vRo0cP5OTk4P79+8/so3Xr1pX2V3G5qq+fty4nJwc9e/bEDz/8gIiICIwePfqZx6oqqy7T5XFd07FR1XZP/yxUHJNPbwfglR7rZbfTVbo8rtVNE4+1ykqara0tTp48qVy+d+8erK2tX3i/Ro0aIT8/H+Xl5dDX16/x/SpycnKCsbFxrTNrg4yMDHTu3FnoGKKQlZUFBwcH5bKdnR3s7e2f2W7btm24efMmhg4dCmdn50rbVdyHhYVFpf0BeO66p7d73joHBwfcvHkTu3btwpQpU9CyZctKj1VVVl2l6+O6pmOjqu2e/lmoOCaf3g7AKz3Wy26ni3R9XKuTWI91SUlJtSeWVPZyZ48ePXDs2DHk5uaiqKgIqamp6N279wvvZ2hoiC5duuCnn34CACQlJdXofkQvo6ioCGvXroWtrS1cXV3V+theXl4wMTHBnDlzoFAo1PrYREQkfioraTY2NggNDYW/vz+GDRuGIUOGwNnZGUFBQTh79my19124cCHi4+Ph6emJkydP4sMPP1RVTNJxERERuHv3Lry9vV96wtqXVa9ePUydOhXp6enYs2ePWh+biIjET6XX7vTy8oKXl1el2yIjI5/ZLiwsrNJys2bNsH37dlVGI8LNmzcRERGBd955B2+88YYgGby9vZGSkoJly5YhNjZWkAxERCROvOIA6azly5cDAEJCQgTLoK+vj08++QQ3b97E999/L1gOIiISH5Y00knnz59HUlISJk6cCBsbG0Gz9O7dG/369cPWrVt5dQ0iIlJS6cudRGK1fPly5XvCZDJZpXVlZWXKT7kVFxerJc/8+fMxYMAA/O9//8PQoUPV8pgkXlKptNK4VOU4rG68V1xnYWEBS0vLF+6juu2IqHZY0kjnnDhxAvv378d///tfWFpaPlPSCgsLcerUKQCAi4uLWjK1bdsWQ4YMwY8//shPMxNkMhnS0tKUy6och9WN94rr3NzcqixfNd2OiGqHL3eSTlEoFFi+fDmsrKwQGBgodJxK3n//fSgUChw8eFDoKEREJAIsaaRTjh8/jmPHjmH69OkwMzMTOk4lTZs2RdeuXXHixAncvXtX6DhERCQwljTSKWvXroWVlRXGjBkjdJTn6tu3LwBg69atAichIiKhsaSRzjh79iwOHz6M4OBgmJqaCh3nuRo2bIhu3bohJSUFN2/eFDoOEREJiCWNdEZUVBQaNmyIcePGCR2lWm5ubtDT00NERITQUYiISEAsaaQTbt26hSNHjiAoKAjm5uZCx6mWpaUlPD09ERcXh5ycHKHjEBGRQFjSSCf8+uuvMDc3x/jx44WOUiNjx45FaWkpNm/eLHQUIiISCEsaaT2pVIo///wT3t7eaNCggdBxaqRFixYYPHgwoqOjkZeXJ3QcIiISAEsaab309HQAwMiRIwVOUjvTpk2DTCZDdHS00FGIiEgALGmk1UpKSvDbb7/ByckJdnZ2QsepFScnJ/Tt2xdbtmxR2+WpiIhIPFjSSKudPHkSxcXFePvtt4WO8lImT56M+/fvIykpSegoRESkZixppLXKy8tx5MgRODg4oEWLFkLHeSm9evWCo6MjNm/eDIVCIXQcIiJSI5Y00lqHDx9Gbm6uxp5FAwCJRIKgoCBcuHABhw8fFjoOERGpEUsaaa3Y2Fg0bNgQ7dq1EzrKKxk2bBisrKwQGRkpdBQiIlIjA6EDEKnCH3/8gTNnzmDIkCHQ03v2dxGpVAqZTAYAon9TvrGxMQICArBy5UpcuXIFrVq1EjoSqYAmjcm6UPH5AoC+vj7Ky8sBABYWFrC0tBQoGZF48EwaaaXIyEiYm5uja9euz10vk8mQlpaGtLQ0PHr0SM3pam/cuHEwNjbm5LZaTNPG5Kuq+HzT0tLw8OFD5dcVyxuRLuOZNNI6t27dQkpKCkaNGgUTExOh49SJJk2aYPjw4fj+++8xe/ZsNGrUSOhIpMEKCgpw4cIFZGdnY//+/bh+/TpKS0thaGiIoqIiNGnSBA0bNkRRURFKS0tRv359oSMT6SSWNNI6UVFRUCgUGDlyJC5duiR0nDoTGBiI7777DjExMQgJCRE6DmmYoqIinDp1CpmZmbhx44bypcUmTZrAzMwMRkZGsLS0xL///ot//vkHf/75Jw4ePAgAsLOzw9WrVzFu3Di8/vrrQj4NIp3CkkZapaioCLGxsRg4cCDs7Oy0qqS1bdsWffr0QVRUFIKDg2FkZCR0JNIA165dw5dffomffvoJpaWlsLW1xXvvvYf69eujadOm6NmzJ06dOgUAcHFxQWJiIhwcHFBaWop69eph3759OHfuHDZu3IiNGzeif//+mDRpEhwcHAR+ZkTajyWNtMqePXsglUo15kLqtRUUFISxY8ciJSUFI0aMEDoOidiDBw+wfv16xMbGQl9fHx07doSrqyvs7e3h4uKiLGZVMTQ0xH/+8x8UFxejT58+cHR0xK+//oqoqCiMGjUKzs7O6NWrF8sakQrxgwOkVaKjo9G6dWv06NFD6Cgq4ebmhjfffBORkZGc3JaeSy6X4/jx4/Dx8UFsbCz8/PyQkJAAHx8f2Nvbv/R+bWxsEBoait9++w3Lli1DVlYWIiIisGPHDuTm5tbhMyCiJ1jSSGucPn0aZ86cQUBAACQSidBxVEIikSAwMBBnz57FiRMnhI5DInPr1i1s2rQJiYmJaNeuHQ4ePIgvvvgCTZo0qbPHMDExgb+/P3bt2oX+/fvj/PnzCAwMxKlTp/iLA1EdY0kjrREVFQVzc3Otfxlw+PDhsLS0xJYtW4SOQiLy888/w9/fH3fu3IGPjw/WrVuHN954Q2WPZ25uDnd3d8yYMQPNmzdHXFwctm/fjvz8fJU9JpGuYUkjrZCbm6t8n1a9evWEjqNSZmZmGD16NH7++WfcunVL6DgksLKyMixatAiBgYFo0aIFZsyYga5du6rtbLK1tTVWr14NT09PXLhwAf7+/jhz5oxaHptI27GkkVb47rvvUFJSorUfGHhaQEAAFAoFtm3bJnQUEpBMJsP777+PyMhIvP/++9i0aZMgc+jp6+ujT58+CA4ORnl5Oby9vREXF6f2HETahiWNNF55eTm2bduG7t27o02bNkLHUYvmzZvDw8MDO3bsQFFRkdBxSAC3b9/GsGHDcOjQISxfvhyfffYZDA0NBc3k4OCA7du3o1u3bvjoo4+wbNkyyOVyQTMRaTKWNNJ4Bw4cQFZWFgICAoSOolYTJkzAw4cPkZycLHQUUrNr165h2LBhyMrKwvbt2zF27FihIyk1aNAAO3bsgJ+fH77++mvMmzcPpaWlQsci0kgsaaTxoqOjYWtri4EDBwodRa26d+8OR0dHbNmyhZ+q0yF///03hg8fjqKiIuzatQt9+vQROtIzDA0NsXz5cnz66ac4ePAgtm7dipKSEqFjEWkcljTSaNeuXcPBgwfh5+cn+Es96iaRSDBhwgScP38ev/32m9BxSA1u376N4OBg6OnpISEhAU5OTkJHqpJEIsHkyZOxcOFCXLt2DRs3boRUKhU6FpFGYUkjjbZt2zYYGBhgzJgxQkcRxLvvvsvpOHTE3bt3sXnzZpiYmCAhIQFvvvmm0JFqxNPTE/7+/sjOzsa0adPw8OFDoSMRaQyWNNJYRUVFiIuLw8CBA2Frayt0HEGYmppi7Nix2Lt3L7KysoSOQypy8+ZNREZGQk9PDxERERp3KSZHR0cEBATgxo0bGD16NM+oEdUQSxpprKSkJOTl5VWadkMqlSIrKwtZWVkoLi6utH1ZWVmV64RSF5n8/f0hkUgQHR1dx+lIDKRSKf773/8CACZNmgQ7OzvlmBFj2ak4piuO69atWyMsLAyXLl2Cn58fZDJZjfbx9HOs+DMuxudPVJdY0kgjKRQKREVFoU2bNnB1dVXeLpPJkJaWhrS0NDx69KjSfQoLC6tcJ5S6yNSsWTMMHDgQsbGxnI5DyxQWFmLLli0oKCjAxIkTYW1tXWnMVFd0hFIx39PjumfPnti4cSPOnTuHGTNmVPmLSXXPseLPuBifP1FdYkkjjXTq1ClkZmZq9XU6a2PixImQSqVISEgQOgrVkUePHmHr1q148OABFi9ejKZNmwodqU64u7tjw4YNuHDhAj/1SfQCLGmkkaKiomBhYaH11+msqW7duqFdu3b49ttvOR2HFpDL5YiPj8fNmzcxevRodOzYUehIdWrQoEFYunQp/vnnH2zfvh1lZWVCRyISJZY00jj379/HDz/8AB8fH1hYWAgdRxQkEgkmTpyIixcvIj09Xeg49Iqio6Nx9uxZDBo0CO3btxc6jkr0798fw4cPx+XLl7F7927+ckH0HCxppHF27tyJR48e6dwVBl7E29sbjRo1wrfffit0FHoFGRkZiI2NRdeuXdG7d2+h46hU165d4e7ujlOnTnEaGaLnYEkjjVJeXo7t27ejR48eaN26tdBxRMXExAR+fn5ITU3FP//8I3QcegnXrl3D7t270bFjRwwbNkwn3m/Zr18/uLq6Ii4uDkePHhU6DpGosKSRRvnf//6HrKysStNu0P/H6Tg0V1ZWFrZt24aGDRvi008/hYGBgdCR1EIikcDb2xs9e/ZESkoK/vzzT6EjEYkGSxpplKioKNja2sLDw0PoKKLUtGlTeHp64rvvvkNhYaHQcaiG8vLy8PHHHwMA3n//fdSrV0/gROqlp6eHuXPnwsHBATt37sSZM2eEjkQkCixppDGuXr2KQ4cOYezYsTpzluFlTJw4EXl5edi9e7fQUagG5HI5QkJCcPPmTYwbNw5NmjQROpIgjI2NERAQgMaNG2Px4sW4f/++0JGIBMeSRhrjyXU6/fz8hI4ial26dEH79u05HYeGWLt2Lfbv34/Q0FC88cYbQscRlJmZGcaPHw+JRIKoqCieDSadx5JGGqGoqAjx8fHw9PSEtbW10HFE7cl0HH/99RcOHz4sdByqxv79+7Fq1Sr4+PjAx8dH6Dii0LhxYyxatAi5ubnYsWMH51AjncaSRhohMTHxmet0UtWGDh2KJk2acDoOEbt27RpCQkLwn//8B2FhYTrxSc6aat++PUaMGIErV65g5cqVPCNMOosljUTvyXU6HR0d0a1bN6HjaARjY2OMHTsW+/fvx9WrV4WOQ08pLCxEUFAQJBIJNm/eDFNTU6EjiU7nzp3Rt29fJCYmcg410lksaSR6GRkZOHfuHK/TWUsBAQEwNDTEpk2bhI5CFSgUCsyaNQsXL15EREQEWrRoIXQk0XJ3d4ebmxsWL16M/fv3Cx2HSO1Y0kj0oqOjUa9ePQwfPlzoKBrF2toa7733HuLj43Hv3j2h49D/2bx5M5KSkvDf//4Xffr0ETqOqOnp6WHRokVo164dpk6digsXLggdiUitOI8BidqT63SOGzcO5ubmQsdRm7KyMmRlZSmX9fX1UV5eDgCwsLCApaUlAEAqlUImkym3q7gOACZNmoTY2Fhs3boVs2fPVkt2qtqxY8ewdOlSDBo0CNOmTXvl/T09ToqLi5+7ruLtqnisl9lHTe9vamqKrVu3YsiQIRg/fnylM8NPZ3p6/NfWi36earsd0atSaUlLSUnBhg0bUFZWhoCAgGemTrhw4QLmz5+PgoICdOnSBYsXL4aBgQESExOxatUqNG7cGADg5uaG0NBQVUYlkYqJicGjR4/g7+8vdBS1KiwsxKlTp5TLLi4uymU3NzflfwgymQxpaWnK7SquA4BWrVph4MCBiI6OxgcffKBTRVdsbt++jeDgYLz22msIDw+vk5funzdOnreu4u2qeKyX2Udt7m9nZ4etW7fi3XffxezZs+Hr6wtDQ8NnMj09/mvrRT9Ptd2O6FWp7OXO7OxshIeHIzY2FklJSYiLi8OVK1cqbTNr1ix8+umn2LdvHxQKBeLj4wEAmZmZmDNnDpKTk5GcnMyCpqNKSkoQFRWFfv36oVWrVkLH0VhTp06FVCpFbGys0FF0VklJCSZNmoSioiJs2bJF564oUBecnZ2xbt06ZGZmYvfu3fzEJ+kElZW09PR0uLq6wtLSEmZmZvDw8MDevXuV62/duoXi4mJ07NgRADB8+HDl+rNnzyIxMRFeXl6YOXMm8vLyVBWTRCwpKQn37t1DUFCQ0FE0mouLC1xdXbFp0yaUlpYKHUcnffrppzh9+jTWrFmDN998U+g4GsvT0xNTpkzB6dOnK53JItJWKitpOTk5sLKyUi5bW1sjOzu7yvVWVlbK9VZWVpg6dSr27NkDOzs7LFmyRFUxSaQUCgUiIyPh6OiIt99+W+g4Gm/KlCm4ffs29uzZI3QUnfPdd98hJiYG06ZNg6enp9BxNF5AQAA6deqEvXv34siRI0LHIVIplb0nTS6XV3rPhUKhqLRc3fr169crbw8MDMSAAQNq9diZmZkvG1srZGRkCB3hlf3xxx+4cOECZsyYUek9Jy8il8tx48YNAEDr1q2VXz+9XNXX6tzuZfdx584d5S80FZ/v0+sqsrS0hIODA1atWgUHBweNnMpEE8f15cuXMXfuXHTo0AH9+/ev9jmIZewCENXPydNjWi6Xo2vXrrh9+zbCwsIwdOhQ5S/8VY3/mqrpz1NNt6sJTRzXmkoTj7XKSpqtrS1OnjypXL53716ly/nY2tpWmhbg/v37sLa2Rn5+Pnbv3q2cWV6hUEBfX79Wj+3k5ARjY+NXewIaKiMjA507dxY6xitbs2YNrKysMGPGjFp9L7OysuDg4ADg8Seunnz99HJVX9dmOwCvtL+XzWRnZwd7e/tnnu/T654WGhqKDz/8EP/++y/69ev3/AMoUpo4rh88eIDg4GDY2NggJiYGjRo1qnZ7dY7d6rYDXm1c1/V2T4/prKwstGzZEkFBQdi4cSNSU1Mxffp01KtXr9rxXxM1/Xmqzc9ddTRxXGsqsR7rkpKSak8sqezlzh49euDYsWPIzc1FUVERUlNT0bt3b+X6Zs2awdjYWNlsk5OT0bt3b5iZmWHz5s04c+YMgMef7qvtmTTSbJcvX8aBAwcQEBCgs2VbFby9vWFnZ4eIiAiho2i9srIyTJkyBbm5udi8efMLCxrVXr169bBkyRIUFhYiOjqa77ckraSykmZjY4PQ0FD4+/tj2LBhGDJkCJydnREUFISzZ88CAFauXIlly5Zh4MCBKCwshL+/P/T19bFmzRosWrQIgwYNwrlz5zBr1ixVxSQRioyMhImJic5Nu6FqRkZGCAoKwrFjxzTytL8mCQsLw9GjR7Fs2TK0b99e6Dhaq1WrVvD19cXNmzf5iU/SSiqdJ83LywteXl6VbouMjFR+3bZtW+zateuZ+3Xp0gWJiYmqjEYi9eDBA+zevRsjRoxQzpNHdWfs2LFYt24d1qxZg+3btwsdRyslJydjw4YNCAgIwMiRI4WOo/WcnJzg4eGBffv2ITo6GgsWLBA6ElGd4WWhSFS2bduG4uJiTruhIubm5ggODsaBAwdw+vRpoeNonczMTHz00Ufo1q0bFi1aJHQcndG3b1906tQJGzZswE8//SR0HKI6w5JGolFcXKycvJZzSanO+PHj0bBhQ6xevVroKFrlwYMHmDBhAho2bIhNmzbByMhI6Eg6QyKRYMSIEWjXrh1CQkJ0/hP+pD1Y0kg0kpKScP/+fUyaNEnoKFrNwsICkydPxoEDB/DHH38IHUcrlJaWYvLkyXjw4AG2bNlSaQ5IUg9DQ0N8+eWXaNiwIcaPH4+cnByhIxG9MpY0EoXy8nJERESgXbt26NWrl9BxtN77778PS0tLrFq1SugoWmHp0qU4duwYli9fjg4dOggdR2c1btwYW7duhVQqxYQJE1BUVCR0JKJXwpJGovDzzz/j77//xvTp0zVyolVNY2FhgalTp+LAgQP4/fffhY6j0eLi4rBlyxYEBQXBx8dH6Dg6z8nJCevWrcPp06cRGhoKuVwudCSil8aSRoJTKBRYt24d3njjDV42R40mTJgAGxsbfPHFF5y64CWdOHECc+bMwdtvv81PFYrIoEGD8MknnyAlJQVhYWFCxyF6aSqdgoOoJg4dOoTMzEysWrWq1leXkEqlkMlkyuXi4uK6jqdRysrKkJWVBeDx2TJLS8sqtzU1NUVoaCjmzJmD/fv3a92k0RXHxtPHorp1NXX27FmMHz8eNjY2CAsLg4GBwTP7rm7/HLuqNWrUKJw/fx7r169HkyZN+F5X0kgsaSS4devWwc7ODsOHD6/1fWUyGdLS0pTLLi4udZhM8xQWFiqvderm5vbC8uHr64tvvvkGYWFh6NevX61LsphVHBtPH4vq1tVEXl4egoOD8ejRI/j6+ioL2tP7rm7/HLuqVVBQgM6dO+PcuXP47LPP0KpVK427HBoRX+4kQaWnp+P48eMIDg7mlAUCMDQ0xOzZs3Hx4sXnTixNzyotLcWkSZOQlZWFcePGoUmTJkJHoiro6+tjzJgxaNWqFYKDgzk1B2kcljQSjEKhwKpVq2BjYwM/Pz+h4+gsLy8vdOrUCcuXL0dBQYHQcURNoVBg3rx5OHLkCObNm4c33nhD6Ej0AsbGxli1ahXq16+PgIAA3Lp1S+hIRDXGkkaCOXr0KI4fP44PPvgApqamQsfRWXp6eli8eDGys7Px9ddfCx1H1L755hvExsYiJCQEgwcPFjoO1ZCVlRW2b9+OgoIC+Pn5ITc3V+hIRDXCkkaCeHIWzdbWlmfRRKBz584YPnw4Nm7ciJs3bwodR5SSk5Px+eefw8vLC7NmzRI6DtWSo6Mjvv32W9y4cQMBAQEoLCwUOhLRC7GkkSAOHz6M33//HdOmTYOJiYnQcQjAnDlzIJFIsHTpUqGjiM7BgwcREhKCt956C+Hh4dDT4z+dmqhHjx5Yv349/vjjD0yePBmlpaVCRyKqFv+lIbVTKBRYsWIF7OzsMHr0aKHj0P9p1qwZpk2bhh9//BEHDx4UOo5onDhxAkFBQWjTpg22bt3Kl+Y1nKenJ8LCwnDgwAF89NFHnOyWRI0ljdTup59+wunTpzFz5kyeRROZqVOnomXLlpg3bx4vqQPgwoULCAgIgI2NDXbs2IH69esLHYnqgJ+fH2bPno2EhAQsWbKEkzmTaLGkkVqVlZUhLCwMrVu35iV0RMjY2BjLly/HP//8gzVr1ggdR1A3btyAn58fTE1NsXPnTl40XcuEhIRg4sSJiIyMxFdffSV0HKLn4mS2pFY7d+7E1atXsXXr1koTgJJ4dO/eXTnJrbe3N/7zn/8IHUntsrOzMWbMGJSUlCAhIQHNmzcXOhLVMYlEgkWLFuHhw4dYsWIFjI2NMWTIEKFjEVXC/yVJbQoLC7F69Wp07dpV6y5BpG3mz5+P/fv3Y8aMGfjxxx91aqLh27dvY+TIkcjJycHOnTvRpk0boSORiujp6SE8PBylpaVYunQpCgoKYGNjI3QsIiW+3Elqs379emRnZ2P+/PmQSCRCx6FqNGrUCF9++SXOnz+PVatWCR1HbW7evIkRI0bg/v37iI2NRefOnYWORCpmYGCAdevWYdCgQVi9ejWOHz8udCQiJZY0UoubN2/im2++wbBhw9C1a1eh41ANuLu7w9fXFxEREThx4oTQcVTu+vXrGDFiBPLy8rBz506OUx1iaGiIiIgI9OrVC4mJiTox3kkzsKSRWjyZe2vevHkCJ6HaWLx4Mezt7TFjxgzk5eUJHUdlrly5ghEjRqCwsBDx8fHo2LGj0JFIzYyMjPDFF1+gdevW2L17NzIyMoSORMSSRqqXnp6OH3/8EdOmTUOzZs2EjkO1YGFhga+++gq3bt1CaGioVk5VcOXKFfj4+KCsrAzff/89nJychI5EAjE2Noa/vz9atmyJ+Ph4JCQkCB2JdBxLGqnUo0ePsGDBAjRr1gzBwcFCx6GX0LVrVyxYsAD79u3Dhg0bhI5Tp65cuYJJkyZBX18fu3btgqOjo9CRSGCGhoYYP348HB0dsXz5cq0b86RZ+OlOUqkNGzbg0qVLrzxTu1QqhUwmAwDo6+ujvLwcAFBcXFwnOTVJWVkZsrKyANT8+Vc8fsDjM2SWlpY1fszAwEBkZGRg2bJlcHZ2Rq9evWqVuSa5apvpVZ0+fRrff/89WrRogbi4OOVZ3qoyPX0Ma3rsK36/dH3sisWLxp2hoSHGjRuHAwcO4LPPPoNMJsPMmTOr/MBTxe+xuscxaTeWNFKZq1evYu3atRg8eDDc3d1faV8ymQxpaWkAABcXF5w6dUr5ta4pLCys9fOvePwAwM3NrVb/kUgkEqxcuRKXLl1CUFAQkpKS6mRqioq5apvpZcnlcnzzzTfYuXMn3njjDWzcuLHSy/BVZXr6GNb02D/9/dLlsSsWNRl3+vr6WLJkCZo0aYI1a9agoKAACxcufG5Rq/g9Vtc4Jt3AlztJJRQKBebMmQMjIyMsWbJE6DhUBywsLLB9+3aYmJhg7NixuHv3rtCRaq2goABBQUHYunUrunTpgokTJ/JST1QlfX19fPnll8orE3z88ce8KDupFUsaqcR3332Ho0ePYu7cubC1tRU6DtURe3t7bN++HXl5eRg3bhwePnwodKQau3TpEjw9PZGamoqPPvoIPj4+vOoFvZCenh4WL16Mjz76CHFxcfD396/0sjeRKrGkUZ37559/sGjRIvTs2RPjxo0TOg7VMScnJ0RGRuLKlSvw9fVFbm6u0JGqpVAo8OOPP8LT01M5B9qoUaM4oTLVmEQiwccff4zVq1cjPT0dkydPhlQqFToW6QCWNKpT5eXl+PDDD5WXW9HT4xDTRn369MG3336Ly5cvY+TIkXjw4IHQkZ6roKAAO3bswJIlS9CpUyekpqaiZ8+eQsciDTVq1Chs374dd+7cwddff41bt24JHYm0HP8HpToVGRmJ3377DUuXLuWcaFqub9++iIqKwrVr1zB06FBcuXJF6EiVHD58GOHh4Th//jymTJmCuLg4WFtbCx2LNFzv3r0RGRkJPT09fPPNN7hw4YLQkUiLsaRRnXkyRYOnpyd8fHyEjkNq0Lt3b+zcuRP5+fnw8vLCoUOHhI6E27dvIzAwEDNnzoS5uTmmTZuG8ePHQ19fX+hopCVatmyJadOmwcrKCtHR0YiJiYFcLhc6FmkhljSqE7m5uZgyZQqaNm2KL7/8ku/30SFdu3bFjz/+iGbNmmHs2LFYsWKFIJ+AKywsRHh4ONzc3HDw4EF88MEHmD59Opo2bar2LKT96tevj+DgYHTs2BHR0dGIjo5GYWGh0LFIy7Ck0SuTy+WYMWMG7t27h2+++YZzBOmg5s2bIykpCSNGjMDatWvh5eWltpeBiouLsW3bNvTq1QsrV65Enz59cPDgQfj7+/PTm6RSRkZGGDVqFKZNm4a//voL69atw19//SV0LNIiLGn0ylavXo0DBw5g4cKF6NChg9BxSCAWFhZYs2YNtmzZgtu3b8Pd3R2zZ89Gdna2Sh5PKpXim2++QY8ePTB37lzY29sjKSkJkZGRaNGihUoek+hpEokE3t7emDx5MsrKyhAYGIjvv/9e6FikJVjS6JUkJCQgPDwco0aNQkBAgNBxSAQGDhyItLQ0vP/++4iPj0fPnj0xd+5cXLx48ZX3XVZWhqNHjyIkJASdO3fG0qVL8eabbyIuLg7Jycno2rVrHTwDotp77bXXEBISgnbt2uHDDz/E1KlTOU0HvTK+FkAv7eTJk5g5cyZcXV0RFhbG96GRUqNGjbBkyRJMmDABa9euRVxcHLZt24ZOnTphwIAB6N+/P9q2bfvC/SgUCty4cQMHDhxATEwMfvnlFzx8+BD16tXDyJEj4efnBycnJzU8I6IXq1evHtatW4ekpCSEh4fj999/R3h4ON5++22ho5GGYkmjl3L58mW8//77sLOzQ2RkJIyMjISORCL02muvITw8HJ988gni4uKQkpKCFStWYMWKFTA2NsZrr70GY2NjmJmZ4dy5czAzM0NRURGkUilu3LiB69evK89GNGjQAP3798fAgQPRt29fmJmZCfvkiJ7DwMAAH374Ifr27Yvp06fD19cXQUFBmDNnDkxMTISORxqGJY1q7Z9//oGvry8MDAwQExODRo0aCR2JRK5Ro0aYMmUKpkyZgpycHPz66684f/48/vjjD/z9998oKirCyZMnYWBgAFNTU9SvXx8tWrTAkCFD0K5dO5ibm2PYsGGcRoM0RocOHbBv3z589tlniIyMxKFDh7B8+XJ069ZN6GikQVjSqFbu3LmDUaNGobi4GLt378brr78udCTSMNbW1sp59LKyspCWlgYAcHNzg729/XPvk5GRwYJGGsfU1BSff/453nnnHcyePRvvvvsufH19MX/+fP5ySzXCkkY1dv36dfj6+uLhw4eIi4ur0XuKakMqlSovXGxhYcGpPF5RWVkZsrKyADyepkKTGRoaKp+Lvr4+ysvLAdR8nFQ8FkDNj0dNj6E2HWuxqc33rqrvQ118/yuOu9p+j/v27Yu0tDSEh4cjMjIS+/btw4IFC9CyZcta7edp/DdT+7GkUY1cvHgRo0ePxqNHjxAfH6+SqTZkMlmlsyr8B+fVFBYW4tSpUwAAFxcXgdO8mpKSEuXYcHFxUT6vmo6TisfiyT5qoqbHUJuOtdjU5ntX1fehrr7/r/I9Njc3x4IFCzBixAjMnTsXH3/8MRwdHbF8+XJ07ty51vsD+G+mLuAUHPRChw8fxogRIyCRSJCQkMC50IiIXpKjoyMSEhKwatUq3L59G0OHDkVgYCAuX74sdDQSIZY0qpJCoUBUVBT8/PxgY2ODpKQktGnTRuhYREQaTU9PD76+vti4cSNmzpyJw4cPo1+/fpg5cyZu3boldDwSEZY0ei6ZTIbQ0FDMnz8f/fr1Q3JyMmdxJyKqQ2ZmZggNDUV6ejomTJiA3bt34+2338bs2bPx999/Cx2PRIAljZ5x5swZeHh4YPfu3QgNDcWWLVtQr149oWMREWmlxo0bY/HixTh8+DB8fHywa9cu9OnTBxMnTsSJEyeEjkcCYkkjpaKiInzxxRcYOnQoSkpK8P3332PmzJmc+oCISA3s7e2xYsUK/PbbbwgJCcHx48cxbNgweHt7IyEhAUVFRUJHJDVjSSMoFAqkpqaiX79+WL9+PXx8fPDLL7/A1dVV6GhERDrHysoKs2fPxokTJ7B06VLcu3cP06dPh4uLC+bOnYszZ85AoVAIHZPUgFNw6LgTJ07giy++wO+//45WrVph165d6N69u9CxiIh0npmZGSZMmIDx48fj2LFj2LlzJ+Lj47Ft2zY4OjrCzc0N5ubmsLKyEjoqqQhLmg5SKBRIS0tDREQE0tPTYW1tjbCwMPj6+sLQ0FDoeEREVIGenh569uyJnj174rPPPkNycjLi4+OxYcMGAI+v4nHx4kWMGjUKTk5OkEgkAiemusKSpkMePHiA77//Ht999x2uXLkCW1tbfPLJJ/D39+fFqomINECDBg3g7+8Pf39/ZGRkYMuWLcjMzER0dDS2bt0KKysrZaHr2bMnWrRowdKmwVjStFxubi5SU1Px448/4tdff0VZWRk6d+6MNWvWwNvbG0ZGRkJHJCKil2BjY4MePXqgR48e6NixI86dO4cjR47gyJEjSEpKAvD4wwjdunVDhw4d0KFDBzg5OcHU1FTY4FRjKi1pKSkp2LBhA8rKyhAQEAA/P79K6y9cuID58+ejoKAAXbp0weLFi2FgYIDbt29j1qxZePDgAV5//XWsXLkS5ubmqoyqNf79918cPHgQJ06cwKFDh5RvMG3evDkCAwMxcuRITkhLRKRlLC0tMWrUKIwaNQoKhQJXrlzB0aNHcfToUaSnpyMhIQHA42uQtm3bFu3atUPr1q3x5ptv4s0330Tz5s2hp8fPEoqNykpadnY2wsPDkZCQACMjI/j6+uKtt95Cq1atlNvMmjULn332GTp27Ih58+YhPj4eY8aMweLFizFmzBgMHjwY69evR0REBGbNmqWqqBqptLQUWVlZuHHjBi5duoQzZ87gjz/+wI0bNwA8fg+Di4sLPvroI/Tv3x/Ozs485U1EpAMkEomyfI0fPx4AcPfuXZw5cwanT5/GmTNnkJaWhvj4eOV9TExM8Prrr8Pe3h4tWrSAvb09mjdvjqZNm6JJkyZo0qQJjI2NBXpGuktlJS09PR2urq7KC756eHhg7969mDZtGgDg1q1bKC4uRseOHQEAw4cPx1dffYX33nsPJ06cwPr165W3jx07VidKmkKhQFFREf7991/8+++/kEqlyMnJwb1795R/bt++jevXryMrKwtlZWXK+zZr1gwdO3aEm5sbhgwZAmdnZ1hYWAj4bIiISCxsbW1ha2sLDw8P5W1SqRSXL1/G5cuX8ddff+HGjRu4efMm0tPTUVBQ8Mw+GjRogCZNmsDKykr5t6WlJSwsLFC/fn3Uq1ev0t8WFhYwMTGBsbExTExMeKLgJaispOXk5FT6WLC1tTX+/PPPKtdbWVkhOzsbDx8+hIWFBQwMDCrdXhNP5o159OhRXTyF55LL5UhJSUF2djbKy8shl8shl8tf+HV5eTkePXqER48eoaSkBCUlJZW+Lioqgkwmg1wuf+7j6unpoWHDhmjSpAm6d++O5s2bK3/TadGiBRo2bAgAyMzMhJOTEwCgpKREZcdBFcrLy5WfLi0vL6+Uv+I6uVz+3K9fdt3LbgdAdJlqut3Tx1co1X3Pn/a851LdfaoaMy/ax6uOtbreTp2PJZfLYWpqKqrnr+rjVPH7X/F7Xxf7q4lX+Tmszc/P85iamsLZ2RnOzs6VblcoFPj3339x9+5dZGdnIzc3Fw8ePMDDhw/x4MEDSKVS3L17FxcuXEB+fn6NH8/Y2BhGRkbP/dvAwAB6enrKv/X19WFgYACJRPLMbU++rrg9AGUJrPj3kz85OTlIT09XLlfc7ultK/7p378/mjZtWqvjWhtP+kpV895JFCqaEW/Dhg0oKSnBhx9+CACIj49HZmYmlixZAgDIyMjAqlWrEBsbCwC4fv06goODER0djZEjR+LQoUMAgLKyMnTq1Alnz5594WPm5+fjr7/+UsXTISIiIlKJ1q1bP/fyiyo7k2Zra4uTJ08ql+/duwdra+tK6+/du6dcvn//PqytrdGoUSPk5+ejvLwc+vr6z9yvOubm5mjdujUMDQ15WpWIiIhETaFQoLS0tMoPR6qspPXo0QPr1q1Dbm4uTE1NkZqaiqVLlyrXN2vWDMbGxsjIyEDnzp2RnJyM3r17w9DQEF26dMFPP/0ELy8vJCUloXfv3jV6TD09PV4InIiIiDSGiYlJletU9nIn8HgKjo0bN6K0tBQ+Pj4ICgpCUFAQQkJC0L59e1y8eBELFiyATCZDu3btsGzZMhgZGeHWrVuYM2cOHjx4ADs7O6xevRoNGjRQVUwiIiIi0VFpSSMiIiKil8OZ64iIiIhEiCWNiIiISIRY0oiIiIhEiCWNiIiISIRY0oiIiIhEiCVNCyUmJqJXr17w9vaGt7c3wsPDhY6kdVJSUuDp6Ql3d3fs2LFD6Dhabdy4cRg8eLByPJ85c0boSFpFJpNhyJAhyMrKAvD4usteXl5wd3fnvx117OljPXfuXLi7uyvH9i+//CJwQu3w9ddfY/DgwRg8eDBWrFgBQHPHtcomsyXhZGZmYs6cORgyZIjQUbRSdnY2wsPDkZCQACMjI/j6+uKtt95Cq1athI6mdRQKBa5fv46DBw8qr+dLdefMmTNYsGABrl+/DgAoLi7GvHnzsH37dtjZ2WHy5Mk4dOgQ+vTpI2xQLfD0sQYe/1sdExNT46vq0Iulp6fjyJEjSExMhEQiQWBgIH744QesXLlSI8c1z6RpobNnzyIxMRFeXl6YOXMm8vLyhI6kVdLT0+Hq6gpLS0uYmZnBw8MDe/fuFTqWVrp69SoAYMKECRg6dChiYmIETqRd4uPjsXDhQmVJ+PPPP+Hg4IDmzZvDwMAAXl5eHNt15OljXVRUhNu3b2PevHnw8vLCV199BblcLnBKzWdlZYU5c+bAyMgIhoaGaNmyJa5fv66x45olTQtZWVlh6tSp2LNnD+zs7JQXtae6kZOTAysrK+WytbU1srOzBUykvf799190794d69evR1RUFHbu3ImjR48KHUtrfP755+jSpYtymWNbdZ4+1vfv34erqyu++OILxMfH4+TJk9i1a5eACbXDm2++iY4dOwIArl+/jp9//hkSiURjxzVfP9BgP//8M5YtW1bptjfeeANRUVHK5cDAQAwYMEDNybSbXC6HRCJRLisUikrLVHc6deqETp06KZd9fHxw6NAh9OzZU8BU2otjW32aN2+O9evXK5fHjRuHpKQkjBw5UsBU2uPy5cuYPHkyZs+eDX19/UovM2vSuGZJ02CDBg3CoEGDKt2Wn5+PqKgojB8/HsDjwaivry9AOu1la2uLkydPKpfv3bvH95SoyMmTJ1FaWoru3bsDeDye+d401bG1tcW9e/eUyxzbqnPp0iVcv34dHh4eADi261JGRgZCQkIwb948DB48GL///rvGjmu+3KllzMzMsHnzZuUn4GJiYngmrY716NEDx44dQ25uLoqKipCamorevXsLHUsr5efnY8WKFSgpKYFMJkNiYiLHswp16NAB165dw40bN1BeXo4ffviBY1tFFAoFvvjiC+Tl5aG0tBRxcXEc23Xgzp07+OCDD7By5UoMHjwYgGaPa9Z2LaOvr481a9Zg0aJFKC4uxmuvvab8CDLVDRsbG4SGhsLf3x+lpaXw8fGBs7Oz0LG0Ut++fXHmzBkMGzYMcrkcY8aMqfTyJ9UtY2NjhIWFYfr06SgpKUGfPn0wcOBAoWNppbZt22LSpEkYPXo0ysrK4O7uzk/k14EtW7agpKQEYWFhytt8fX01dlxLFAqFQugQRERERFQZX+4kIiIiEiGWNCIiIiIRYkkjIiIiEiGWNCIiIiIRYkkjIiIiEiGWNCIiIiIRYkkjIiIiEiGWNCIiIiIR+n+kYrvMsmjljQAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 720x432 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "comp1 = np.random.normal(0, 1, size=200)\n",
    "comp2 = np.random.normal(10, 2, size=200)\n",
    "values = pd.Series(np.concatenate([comp1, comp2]))\n",
    "sns.distplot(values, bins=100, color='k')#100个区间bins"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Scatter or Point Plots"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 105,
   "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>cpi</th>\n",
       "      <th>m1</th>\n",
       "      <th>tbilrate</th>\n",
       "      <th>unemp</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>198</th>\n",
       "      <td>216.889</td>\n",
       "      <td>1474.7</td>\n",
       "      <td>1.17</td>\n",
       "      <td>6.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>199</th>\n",
       "      <td>212.174</td>\n",
       "      <td>1576.5</td>\n",
       "      <td>0.12</td>\n",
       "      <td>6.9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>200</th>\n",
       "      <td>212.671</td>\n",
       "      <td>1592.8</td>\n",
       "      <td>0.22</td>\n",
       "      <td>8.1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>201</th>\n",
       "      <td>214.469</td>\n",
       "      <td>1653.6</td>\n",
       "      <td>0.18</td>\n",
       "      <td>9.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>202</th>\n",
       "      <td>216.385</td>\n",
       "      <td>1673.9</td>\n",
       "      <td>0.12</td>\n",
       "      <td>9.6</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "         cpi      m1  tbilrate  unemp\n",
       "198  216.889  1474.7      1.17    6.0\n",
       "199  212.174  1576.5      0.12    6.9\n",
       "200  212.671  1592.8      0.22    8.1\n",
       "201  214.469  1653.6      0.18    9.2\n",
       "202  216.385  1673.9      0.12    9.6"
      ]
     },
     "execution_count": 105,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>cpi</th>\n",
       "      <th>m1</th>\n",
       "      <th>tbilrate</th>\n",
       "      <th>unemp</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>198</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>199</th>\n",
       "      <td>-4.715</td>\n",
       "      <td>101.8</td>\n",
       "      <td>-1.05</td>\n",
       "      <td>0.9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>200</th>\n",
       "      <td>0.497</td>\n",
       "      <td>16.3</td>\n",
       "      <td>0.10</td>\n",
       "      <td>1.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>201</th>\n",
       "      <td>1.798</td>\n",
       "      <td>60.8</td>\n",
       "      <td>-0.04</td>\n",
       "      <td>1.1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>202</th>\n",
       "      <td>1.916</td>\n",
       "      <td>20.3</td>\n",
       "      <td>-0.06</td>\n",
       "      <td>0.4</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       cpi     m1  tbilrate  unemp\n",
       "198    NaN    NaN       NaN    NaN\n",
       "199 -4.715  101.8     -1.05    0.9\n",
       "200  0.497   16.3      0.10    1.2\n",
       "201  1.798   60.8     -0.04    1.1\n",
       "202  1.916   20.3     -0.06    0.4"
      ]
     },
     "execution_count": 105,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>cpi</th>\n",
       "      <th>m1</th>\n",
       "      <th>tbilrate</th>\n",
       "      <th>unemp</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>198</th>\n",
       "      <td>-0.007904</td>\n",
       "      <td>0.045361</td>\n",
       "      <td>-0.396881</td>\n",
       "      <td>0.105361</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>199</th>\n",
       "      <td>-0.021979</td>\n",
       "      <td>0.066753</td>\n",
       "      <td>-2.277267</td>\n",
       "      <td>0.139762</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>200</th>\n",
       "      <td>0.002340</td>\n",
       "      <td>0.010286</td>\n",
       "      <td>0.606136</td>\n",
       "      <td>0.160343</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>201</th>\n",
       "      <td>0.008419</td>\n",
       "      <td>0.037461</td>\n",
       "      <td>-0.200671</td>\n",
       "      <td>0.127339</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>202</th>\n",
       "      <td>0.008894</td>\n",
       "      <td>0.012202</td>\n",
       "      <td>-0.405465</td>\n",
       "      <td>0.042560</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          cpi        m1  tbilrate     unemp\n",
       "198 -0.007904  0.045361 -0.396881  0.105361\n",
       "199 -0.021979  0.066753 -2.277267  0.139762\n",
       "200  0.002340  0.010286  0.606136  0.160343\n",
       "201  0.008419  0.037461 -0.200671  0.127339\n",
       "202  0.008894  0.012202 -0.405465  0.042560"
      ]
     },
     "execution_count": 105,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "macro = pd.read_csv('examples/macrodata.csv')\n",
    "data = macro[['cpi', 'm1', 'tbilrate', 'unemp']]\n",
    "data[-5:]\n",
    "data[-5:].diff()\n",
    "trans_data = np.log(data).diff().dropna()#%log 返回自然对数 diff()是将原来的数据减去移动后的数据,这里是上下相减，dropna删去nan行\n",
    "trans_data[-5:]#最后五个"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 106,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Figure size 720x432 with 0 Axes>"
      ]
     },
     "execution_count": 106,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "text/plain": [
       "<Figure size 720x432 with 0 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 108,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\ProgramData\\Anaconda3\\lib\\site-packages\\seaborn\\_decorators.py:36: FutureWarning: Pass the following variables as keyword args: x, y. From version 0.12, the only valid positional argument will be `data`, and passing other arguments without an explicit keyword will result in an error or misinterpretation.\n",
      "  warnings.warn(\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:xlabel='m1', ylabel='unemp'>"
      ]
     },
     "execution_count": 108,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "text/plain": [
       "Text(0.5, 1.0, 'Changes in log m1 versus log unemp')"
      ]
     },
     "execution_count": 108,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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gzjvvxNKlS7Fx40ZMnz4dTzzxRKabT0RERJRVGQ/etm7dirlz56KkpAROpxOLFi3Cxo0bw/cHAgHcfvvtqKgIFg+dOnUqDh48iEAggG3btmHRokUAgKqqqqjnEREREeWDjAdvDQ0NKCsrC98uLy+Hy+UK3x45ciS++93vAgC8Xi/++Mc/4pxzzkFLSwsKCwuhqsFFIcrKyqKeR0RERJQPMr48lmEYkCQpfFsIEXU7pKOjAz/72c9w3HHH4eKLL4bL5erzuFjPG0hdXV3yjU5CbW1tWvdPuYPXOn/wWucPXuv8YeZrnfHgbcyYMaipqQnfbmxsRHl5edRjGhoa8OMf/xhz587F8uXLAQClpaXo6OiArutQFCXm8xIxffp02Gy2oZ1EHLW1tZg1a1Za9k25hdc6f/Ba5w9e6/xhhmvt8/niJpwy3m06b948vP/++2hubobH48GmTZswf/788P26ruMnP/kJFi9ejFtuuSWcXbNYLJg9ezY2bNgAAFi7dm3U84iIiIjyQcYzbxUVFbjxxhtxxRVXIBAI4JJLLsHMmTNx1VVX4brrrsOhQ4fw6aefQtd1vPXWWwCC2bJ7770Xt99+O26++WasWrUKY8eOxcqVKzPdfCIiIqKsynjwBgCVlZWorKyM2vbkk08CAGbMmIHPPvss5vPGjx+PZ599Nu3tIyIiIspVXGGBiIiIyEQYvBERERGZCIM3IiIiIhNh8EZERERkIgzeiIiIiEyEwRsRERGRiTB4IyIiIjIRBm9EREREJsLgjYiIiMhEGLwRERERmQiDNyIiIiITYfBGREREZCIM3oiIiIhMhMEbERERkYkweCMiIiIyEQZvRERERCbC4I2IiIjIRBi8EREREZkIgzciIiIiE2HwRkRERGQiDN6IiIiITITBGxEREZGJqNluABENXk29C9Wb98DV7EZFqRNVCyZj9rSKbDeLiIjSiJk3IpOqqXdhdfUOtLR7UORQ0dLuwerqHaipd2W7aURElEYM3ohMqnrzHqiqBLtVhSQFf6qqhOrNe7LdNCIiSiMGb0Qm5Wp2w2ZRorbZLAoamt1ZahEREWUCx7wRmVRFqRMt7R7YrT2/xr6AjvJSZ1qOx/F1RES5gZk3IpOqWjAZmibg9WsQIvhT0wSqFkxO+bE4vo6IKHcweCMyqdnTKnBN1UyMLHag06NhZLED11TNTEs2jOPriIhyB7tNiUxs9rSKjHRduprdKHJE/7ng+Doiouxg5o2IBlRR6oQvoEdtS+f4OiIiio+ZN6IMMfOA/6oFk7G6ege80GCzKPAF9LSNryMiov4x80aUAWYf8J/J8XVERNQ/Zt6IMiBywD8A2K0qvNBQvXmPaQKgTI2vIyKi/mUl87Z+/Xqcd955WLhwIZ577rm4j/vVr36F6urq8O3XXnsNp59+Oi666CJcdNFFePjhhzPRXKIhY0FdIiJKlYxn3lwuFx5++GFUV1fDarViyZIlmDNnDiZPnhz1mNtvvx3vv/8+5s6dG95eV1eHm2++GRdccEGmm000JJkuqEtERMNXxjNvW7duxdy5c1FSUgKn04lFixZh48aNUY9Zv349vvOd72Dx4sVR23fu3InXXnsNlZWV+OUvf4m2trZMNp1o0DJZUJeIiIa3jGfeGhoaUFZWFr5dXl6OHTt2RD3myiuvBADU1tZGbS8rK8O//du/4eSTT8bKlStx11134Xe/+11Sx6+rqxtkyxPTu800fCVzrSUAZ890YGt9Jw63elFSqGL+zEJI7q9RW/t1+hpJKZFLv9efH/Bga30nWjs1lBSqmDetEFPGObLdrGEjl641pZeZr3XGgzfDMCBJUvi2ECLqdn8ef/zx8L+vvPJKfPe73036+NOnT4fNZkv6eYmora3FrFmz0rJvyi2DudazZgE/rExTgyhtcun3uqbehXd37ICqqhhVYoMvoOPdHR4cO/lYTiZJgVy61pReZrjWPp8vbsIp492mY8aMQWNjY/h2Y2MjysvLB3xeR0cHnn766fBtIQQURYn/BCKiYYbLlBERkIXgbd68eXj//ffR3NwMj8eDTZs2Yf78+QM+z+l04k9/+hP+93//FwDwl7/8ZVCZNyIis+KsZSICstBtWlFRgRtvvBFXXHEFAoEALrnkEsycORNXXXUVrrvuOsyYMSPm8xRFwe9//3vccccd8Hq9OOqoo/DQQw9luPVERNnDWctEBGSpSG9lZSUqK6MH/zz55JN9HvfAAw9E3Z49ezZee+21tLaNiChXcZkyIgK4PBYRkWlwmTKi/FBT78L//Uv82bBcHouIyES4TBnR8BZaC7ukUAEQuzoGM29EREREOSI0q7z35KRIzLwRESWppt6F6s174Gp2o6LUiaoFk5kNI6KUcDW7UeToPzxj5o2IKAmhLo2Wdg+KHCpa2j1YXb0DNfWubDeNiIaBilInfAG938cweCMiSgIL5RJROoXWwu4vgGO3KdEwwG68zInVpcFCuUSUKrOnVQBVM7Fx6964j2Hmjcjk2I2XWbG6NFgol4hSafa0Ctz0L/HXXmXwRmRy7MbLrFCXhtevQYjgTxbKJaJMYvBGZHJc7zKzWCiXiLKNY96ITI7rXWYeC+USUTYxeCMyOa53SfmOE3Yo37DblMjk2I1H+YwTdigfMfNGNAywG4/yVeSEHQCwW1V4oaF68x7+TtCwxcwbERGZFifsUD5i8EZERKbFunuUjxi8ERGRabHuHuUjBm9ERGRanLBD+YgTFoiIyNQ4YYfyDYM3ohRjzSkiIkondpsSpRBrThERUboxeCNKIS4ST0RE6cbgjSiFWHOKiIjSjcEbUQqx5hQREaUbgzeiFGLNKSIiSjcGb0QpxJpTRESUbiwVQpRirDkVxJIpRETpwcwbEaUcS6YQEaUPgzciSjmWTCEiSh8Gb0SUciyZQkSUPhzzRkQpV1HqREu7B3Zrz58Ylkwhio9jRCkZzLwRUcqxZApR4jhGlJLFzBsRpdzsaRVA1UxUb96DhmY3yplJyCvMIiUncowoANitKrzQUL15D183iikrwdv69euxatUqaJqGZcuW4fLLL4/5uF/96leYO3cuqqqqAAAHDhzATTfdhMOHD+Poo4/GihUrUFBQkMmmE1GCWDIlP4WySKoqRWWRwHqHcbma3ShyRH8cc4wo9Sfj3aYulwsPP/wwnn/+eaxduxYvvfQS9uzZ0+cxP/nJT/DWW29Fbb/zzjuxdOlSbNy4EdOnT8cTTzyRyaYTEdEAONM4eVxWj5KV8eBt69atmDt3LkpKSuB0OrFo0SJs3Lgx6jHr16/Hd77zHSxevDi8LRAIYNu2bVi0aBEAoKqqqs/ziIgouzjTOHkcI0rJynjw1tDQgLKysvDt8vJyuFzRgzKvvPJKXHrppVHbWlpaUFhYCFUNppbLysr6PI+IiLKLWaTkcVk9SlbGx7wZhgFJksK3hRBRt+OJ9bhEntdbXV1d0s9JRm1tbVr3T7mD19pcPj/gwdb6TrR2aigpVDFvWiGmjHMk9Fxe68TNOELgzW1eeLyARZEQ0AUMHZh/vN0Ur2O22igB+P6pdgD24Ab316it/TorbckXZng/xpPx4G3MmDGoqakJ325sbER5efmAzystLUVHRwd0XYeiKAk/r7fp06fDZrMl/bxE1NbWYtasWWnZN+UWXmtzqal34d0dO6CqKkaV2OAL6Hh3hwfHTj52wOwGr3VyZs0Cjp3sCs80HlduntmmvNb5wwzX2ufzxU04ZTx4mzdvHh599FE0NzfD4XBg06ZNuPvuuwd8nsViwezZs7FhwwZUVlZi7dq1mD9/fgZaTERmx1IMmcWZxkTplfExbxUVFbjxxhtxxRVX4Hvf+x4uuOACzJw5E1dddRV27tzZ73Nvv/12rFmzBueddx5qampwww03ZKbRRGRqHERPRMNJVuq8VVZWorKyMmrbk08+2edxDzzwQNTt8ePH49lnn01r24ho+OFyXUQ0nHB5LCIa9liKgYiGEwZvRDTssRQDEQ0nXNuUiPICB9ET0XDBzBsRERGRiTDzRkSUJjX1wXpnrmY3KkrNU++MiHIbM29ERGlQU+/C6uodaGn3oMihoqXdg9XVO1BTz2X9iGhoGLwREaVBZGFgSQr+VFUJ1Zv3ZLtpRGRyDN6IiNKAhYGJKF045o2IKA0yVRiY4+qI8g8zb0REadC7MHBLhw+uZg++OtSO5au2pGTsG8fVEeUnBm9ERGkQWRj4cJsPHV1+FBdYMHqEPWVBFsfVEeUndpsSUd5LV9djqDDw8lVborpQ7VYVXmio3rxnSMdxNbtR5FDR5QmgtdOHgGZAVWR0uANDbjsR5S5m3ogor2Wi6zFdkxcqSp1o7fShsdUDTROQJQkB3YDbq7HrlGgYY/BGNEzV1LuwfNUW/Pjev6ZsjNVwlImux4pSJ3wBPWpbKiYvVC2YjI6uAAQAWQYEAAkSigus7DolGsYYvBENQxzInrhMlPToPXnB69egaQJVCyYPab+zp1XAabfAosjQDUBVZJSNdKCk0MqSJETDGMe8EZlAsmOyIrNJQOrGWA21Xbl4rEyU9Jg9rQKomonqzXvQ0OxGeQrbP2FMUZ/2e/1aykuSEFHuYPBGlONCWTRVlaKyaKiaGffDPzSQPVKqs0nx2rX7lAnYufdwSoOswbwGiapaMBmrq3fACw02iwJfQE9JVqy30OSFVMtU+4kod7DblCjHDWZMVrrGWA3UroCu4+V3dqe8uzad49IiS3p0ejSMLHbgmhQEhZli9vYTUfKYeSPKcYPJoqUyGxOvuzJWu7o8GgxDpK0kRqRUZhLTlRXLFLO3n4iSw8wbUY4bTBYtVdmY/iY+xGpXQDNgUaP/rKSqJEa6M4lERGbBzBtRjhtsFi3ZbEysDFt/Ex9itUuRJRQ4LFH7TVVJDI7rIiIKYuaNKMdlYkxTvAzbV4fa45bRiNWuS75zLCyKnJaSGBzXRUT5RDdE3PuYeSNTyWRpilRIVXvTPaYpXoZN8wj4AnrcMhqx2nXshJFpKYnBcV1ENBzphkBA06EbArpmIKAJaLoOf8Af9zkM3sg00lkuIh3M1N54EwIsihwsLptEdyWDLCKivnTdQEA3oOsGNF1A0wxougFdCCD4X5T4eTd2m5KJZGIZo1QyU3vjTQiYMKaI3ZVEREnQdANen4Yujx9tHT40tXpw6HAnXC1uHG7zorXTj05PAN6ADs0QEDECt4Ew80amkYnCs6lkpvb2NyGAmTQiomhCCGi6CGbRDAOaFsqk6TAAiGSjsSQxeCPTyMQyRqlkpvamc/mmELONVyQiCgZp3d2bejBgC2gG9AwFafEkHLzpuo5du3ZBlmVMnToVkiSls11EfZitXITZ2pvODJuZxv8RUf6JDNI0LeLfugGB7AVp8SQUvNXU1ODGG2+EoigwDAMWiwVPPPEEpk6dmu72EYVlIjuUSmZrbzr1Vy8uH18PIsoOwwgGZkK2oKPLD003ENCCXZ+xJg3kqoSCt3vuuQf33nsv5s+fDwB49913cfvtt+PFF19Ma+OIejPb+Kt0t9csXZFmGv9HROandwdpesTszsggrbnNg3Z3/FIcuS7h2aahwA0Azj77bHg8nrQ0iIgS09/SVbmGy1sRUTroRrAYeJc3gPZOH5rbvGho7oKruQuHWz1o6fCh3R2A26choBvhmZ0i1/pBk5RQ5m3mzJnYsGEDzjvvPADAP/7xD0yZMiWtDSMaCrNkpIbCTF2RZhv/R0S5JTgWzYBuJFYjbbhLKHj7xz/+gTVr1uDOO++Eqqo4fPgwbDYb3n77bUiShI8//jjd7SRKWL4MjjdTVyTH/1E65cOXtXwQa2ZnJstvmElCwduzzz6b7nYQpYyZMlJDkc5SJOn4MDTbeEUyh3z5sjacDDQejTHawBIK3saPH4//+Z//QVtbW9T2M888c1AHXb9+PVatWgVN07Bs2TJcfvnlUffX19fjlltuQVdXF2bPnh3O+L322mv43e9+h1GjRgEAFixYgBtvvHFQbaDhy0wZqaFIV1ckPwwp1/T3ZSJfvqyZUd+uzuCanfna1ZlKCQVvN954I2pqalBeXh7eJknSoII3l8uFhx9+GNXV1bBarViyZAnmzJmDyZN7PnBuuukm3HPPPTjxxBOxfPlyrFmzBkuXLkVdXR1uvvlmXHDBBUkfl/KHmYrjDkW6uiL5YUi5ZKAvE/nyZS1XZXulgXyVUPBWV1eHd955B1ardcgH3Lp1K+bOnYuSkhIAwKJFi7Bx40b8/Oc/BwB888038Hq9OPHEEwEAVVVVeOSRR7B06VLs3LkTX375JVavXo2pU6fitttuw4gRI4bcJhpe8mlwfDq6IvlhSLFka1zZQF8m8uXLWraZrYjtcJdQqZBjjjkGmqal5IANDQ0oKysL3y4vL4fL5Yp7f1lZWfj+srIyXHvttfiv//ovjB07FnfddVdK2kTDy+xpFVxMfQhY1oN6y2ZZGlezGzaLErUt8stE1YLJ0LRguQghgj+H65e1TAloBjy+ADq6/Ghp96Kh2Y2Dh7vQ2OJBc7sP7W4/3D4Nfs2AIRi4ZUNCmbcf/OAHuPDCC3HSSSdBVXuecv/99yd9QMMwopbWEkJE3e7v/scffzy8/corr8R3v/vdpI9fV1eX9HOSUVtbm9b9U2IkAN8/1Q7AHtzg/hq1tV+n9BjD9VrPOELgzW1eeLyARZEQ0AUMHZh/vH3YnvNAEjnvzw94sLW+E62dGkoKVcybVogp4xwZaF36PfNOIwKaBgky3N3f4wOagWfWb4fkLuv/yUPktOho7fDBqvbkGvyagSKHitraWkgAzp7pwNb6Thxu9aKkUMX8mYWQBvk7nw/vcUmSIMsyhAAMSBCQoHdPGgh0TyIwDMP0tdAGku54YKisFgXFjtg5toSCt0cffRSnn346Jk6cOOTGjBkzBjU1NeHbjY2NUWPpxowZg8bGxvDtpqYmlJeXo6OjA6+++ip+9KMfAQgGdYoS/W0sEdOnT4fNZhv8CfSjtrYWs2bNSsu+KbcM52s9axZw7GRXeCzduPL8Lr2QyLWuqXfh3R07oKoqRpXY4AvoeHeHB8dOPnZYvG5PbPwrSopsUV+snUKg06Ol/fdAOINZP0WVwsMgLBBYVjkTs7pf21mzgB9WDv1Yw/X3Wte7gzJDQNcMBDhxAHV1dZg+fXq2m9EvXQ+g8ZsvYt6XUPAmyzLuuOOOlDRm3rx5ePTRR9Hc3AyHw4FNmzbh7rvvDt8/fvx42Gy28C/RunXrMH/+fDidTvzpT3/CSSedhG9961v4y1/+MqjMGxENjGU9kjPcJ3lkc1wZawQmTu9epzOykG1AN2AIwa7NYSah4O2EE07A5s2bsWDBgiEfsKKiAjfeeCOuuOIKBAIBXHLJJZg5cyauuuoqXHfddZgxYwZWrFiBW2+9FZ2dnTjhhBNwxRVXQFEU/P73v8cdd9wBr9eLo446Cg899NCQ20M03LBgaeYN90ke2Z4ExC8T0cKZtMgaabrO8Wd5JKHgbevWrVizZg0sFgssFkt4HNpgV1aorKxEZWV0jvvJJ58M//u4447DK6+80ud5s2fPxmuvvTaoYxLlg1yq0ZZPQeRwn/HI7Ff2hAIzrbu7M6AFuzsZpOW3hIK3Z555Jt3tIKIUyJXuu1wKIjMh25mpTMhm9isfvggYhkAgXIoj2P2paayVRrElVCpk/Pjx2LlzJ9asWYPS0lJs374d48ePT3fbiChJA5VVyJTIIFKSgj9VVUL15j0ZbUemsDxN+mSzTEk6GIaAP6D3KcVxqLkLh1s9aO3wodMTgC+gQ2c3KMWRUObtj3/8I7Zs2YJDhw7hRz/6ER577DHs27cPP/vZz9LdPjKxfPi2nGtypftuuI8Bi4XjstIjV7LJyTKMyEXWuX4npVZCmbc33ngDTz75JBwOB0aOHIk1a9bg9ddfT3fbyMSG27dls8iVgqUs9EupkivZ5Hh0Q8AX0OH2BtDe6UNzmxcNzV041NyFplYPWjp8aHcH4PZpCOgGBAM3SoGEgjdVVaOWxiouLo4q1kvUW751m+WKXOm+y5UgkswvV74I6EbwfdzVHaQdbvXCdbgLru7uzpYOHzo8AXj8GgK6YJBGaZVQBDZ27Fhs3rwZkiTB7/fjqaee4pg36lemu81iddECyMtu21zovuPsREqVTE4GURQlZq00TTfyuqAtZYYhBNyeANrdfnR0+WHoAYyME6UlFLzddttt+NWvfoVdu3bhxBNPxLe+9S2sWLEilW2mYSaTY69izWx85KXtEEKg0GnJi9mOqZaK8Yq5EESS+aXri0BoVqdmGNC14EzPli4drhY3JwlQyvgDOjrcfnS4gxNUOtx+tHf/7HAHgv/uvt3pDsCIePOVFCi44aKxMfebUPBWUVGBZ555Bh6PB7quo7CwMDVnRcNWJr8txxrQ3NjiBSAwusQR3maGQc65IN/KfFDuG8oXgWQK2vr9AQZu1C9DCLi9Gjq6IoMwf0RgFoi67fXrA+80jiKnJe59CQVvTU1NePHFF9Ha2hq1/dZbbx10o2h4y2S3WawuWk03ELEMI4DcGuScy8w6u4/ymx4xu1PTDGgR63cyIKP+BDQjHIT1ZMJiZcqC2w1jcG8oiyqjyGlFUYEVxU5L+N9FTiuKnJbu7cFthU4LIPShrW160003wW634/jjj49amJioP5nqNovVRasqMnqPTuFsx8TkY5kPMg8hIoO04L8Dmg7N4Jg0ChJCwO0LZsc6uvzBMWQRwVhHlx+HGluxZstWdLgD8Pi0QR+rwK72BGARwVeR04LiAlv3z+D9NquSVAyl6/GzdgkFb4cOHcKbb76Z8AGJMilWF63TroZnOQ7HivfprKGXK7XizIC1DNMrclyapoUWWtc5kzMPBTQDnZHZMXdP92TkGLLQNj2h7FigzxZVkXplxKzdwVd3ZqygZ1uhwwJFSahoR8olFLyNGzcObrcbTif/eFPuidVF++MLe2abDrfZjukek5YPSz2lAscGpkZoTJphiPC4tFBh28iloer2NmHTh1+hqc2D0SMcWDhnIqZPGp3Vtg/FcDufZAkh4PFp4YxYZNdk+N8R48fcQ8iOOW2R2bFgJszT2YpJRx3RE5x1Z83stuSyY9mSUPBWXl6O733vezj11FNht9vD2znmjXJFvC7a4fghmu4xaZkYr2imjNXnBzx49aMtfdrKsYGJi+zq1A0Rnt0ZmjgwUHdn3d4mvLhpFxRFQoFNQVunFy9u2oUlC2HKgGe4nU+Irhs92a+I8WPtvQKx0P2aPrj8qSJL4WAsMitW5IzstgwGakVOa/cwmmh1dXWYPv2IoZ5y1iQUvI0fP5513cgUzBQUDFYmxqSlc7xiohmrXLiWNfUuvLmtFQUF9j5t5djAvsIzOw0BXevJog11SahNH34FRZHCKy3YLAp80LHpw69MGeyY5XyCQ0/0iExYz892d6DPti7v4LNjDpvaZ9B+UdT4sZ5gzWFTTZEdS6eEgre33nor5vaf//znKW0M0VDkSzeW2cekJZKxypVrWb15D2QFMdtq9uswFAGtu/RGRI00TTdgpGlmZ1ObBwW26CWyrKqMw22e1B8sA7J5PrphoDPUVRkOvgK9uit7smWabgzqOLIsBYMxZ884sT4zKyPGlVnU7IwdM6uEi/SGBAIBvPHGG5gwYULaGkU0GPnSjWX2MWmJZKxy5Vq6mt2wKNHf8ENt/UnVTFNfh0REBmmhCQOarkeNRcuE0SMcaOv0Rq1x6tcMjBrhyFwjUiiV5yOEgM/fUwi2d5asd0HYLk/fQfqJstuUXoP4Y3Rbdv902FXIeZ4dS6eEgrdTTz016va8efOwZMkS/PSnP01Lo4gGY7h1Y8XrNszG0lOp7MJMJGOVK9eyotSJAw2+qG2htg6XJcCC49FCkwUil4TKfJAWz8I5E/Hipl3wQYdVleHXDOi6wMI5E7PdtEEZ6Hx0w0CXJxAeJ9ZnMH9XICJr5kdAG2R2TJKCq9CEylz06qKMDMYKnRZYLcrAO6WMGNTq8i0tLWhoaEh1W4iGJBXdWLkwzirUjlC3oQyBz/c14+4/f4iJFUVYdv7xGV16KtVdmIlkDnOlS7JqwWQ88sK2uCVnzLQEWLxZnZpuQCA3grR4pk8ajSULg2PFDrd5MMqEszND2bH27jIWMyaPxo49TWjr9MKiyigusKH6b3vw9OufossTGPT4QJtVic6Ixem2LC6wwumwMDtmUgkFb5WVlVG3Dxw4gB/84AdpaRDRYA21OzFXxlkBPd2Gui7Q1OaFBAmyBBxs6hpSmwYTnKa6CzORjFWudA3PnlaBxaeUYOfXkimya3posoARzOSEs2hGYrM6c9n0SaNzKlgzDIEub/TalL3rj0VmzfyB+Nkxr19Hhzt2d6YkIZwFi9U9WdQrSGN2LD8kPeZNkiSUlpZi0qRJaWsU0WAMtRsrV8ZZAT3dhgfauoKBmxz8dqwbAqoqDapNgw1O++vCrKl34Zk3PsU3jZ0AgHFlBfjR+ScM2LaBMla51CU5ZZwDP6yclfHjxhNaBkqPWK8zsi6amQO0bNN0gaZWT0Tw1Xcgf3DsmA+dnsGvg2qzKFGBWPTg/ehuzAK7Jfz7TxQyqDFvRLlqKN1YqRhnlapu11C3YUAzwt0ahgiujZdMmyLb0+UJwG5VUOi0AUg8OI3XhemwqXjkpe1o7/JDdM8y3HewA/f+x4e47Jwp+OHC45I+70hD7ZIc6Foke60y2aUeqoum6yI4o1MXUWt1MkBLjCEE3J5A1KzKPmUvImZe+vw6gOSHBElAz9ixyGxYrxmVkcskEQ3FoMa8EQ1HQx1nlcpu11C3oSJLMAwRHpNUUmRLuE2923O41QOvT4PVoqDAHjzHRALBqgWT8chL29HY4oWmG1AVGU67iuJCGW6vBgGByJVoNF3g5Xd249gJI7PWvTjQtUj2WqWrS90IZdGMyHU6u+uiIbfHoWVLQNP7DNiP7LKM7MbsdAdgDPJFDI5Ds0YEZLHGjwXHjhU4LFBklrqgzGHwRtRtqOOsUtntGuo2fPqNT/C1qxOqLGHkCBsUGQm3qXd7rJbgrLbWDl84eEs0EBQiOGAqmAQUEEKgrcMfHOze/dkoSQhnhAxDZLVEy0DXItlrNZRrGzmbUzeM7n+npnjtcCCEgNurRXVP9gRggaiZlh1dfnj98RfrHkiBwxI1o7LQ0bM0UpHTikbXfpw4YxqKHJakFxEnyiQGb0TdhjrOKtXlLULdhqHuuoZmN0YWOxJuU+/2lBTa0NjqgT+gB2tDJRicVm/eg0KnBaNLempQef0aWjr8UBUZvkD0h6kkBbMW2SzRMtC1iLy/y6uhtcMHf0CHq9mDmnpXn9c31v4cNhWt7V4AwWA1PEmg+2coQNON3J/NmWoBzYgKuGIN5I+s0m8ktIh4X6oiB9eqDI0Ri1WZv/vfhc6Bs2N1fhfKSsxZO47yC4M3oghDGWeVrvIWg21T7/YUOCzwazq8fgOdHi3h4DReIKQqEqyq2hO8dWeQFElCgcOS1rIeA40/G+hahO7XDaCxxQNJAuTu/3t3h0qShAnlhWhsccOv6YAA7DYVVouMsWUFcB3uGvbj0IQQcPu0vrMqYxaEDcAzlEXE7Wqf0haRZS8i17A0yyLiRKnG4I0oRXKlvEV/7bEoCn5++UlJBYPxAqGJY4pRtWAyVr36v2ho8UAAsKgSigtssChy2s47kfFnA12L0P0tHT4AAqosQ5ZlVJQ6YbVI2PThPpxwTCl0XcCvy5gysQR79rdCMwwIw0BjmwfCAM47rRTaILNG2abp3dmxiAXD23sN5I8c3K8POjsmRdQXizN+rPvfhU5LzEXEiSgagzeiFMml8hapbE9/gdDsaRV46taFUV276T7vRMaf9T73MaOcuHjBZMw6Lnj/SVPK8JPvz8CTa+vCWTeHVYXFosAf0PHlwXY0twdXVmjr9KL2s3ZIEronFQioigKHQ8HnX7Wm5RwHQwgBj0+LzohFlbmILnvhHsIi4k6bGtE9GR2IRWbNmB0jSg8Gb0QplGsV91PRnkSCwEyed2Q3roTuBbAdFnR0+QGExp8FK9ifcExpsGht9xi0xhZ3uB7a2FGFKCqwoaXdA5tFgcevw+PX4QvoGFFojzpmU5snPMg9RAiR9oXEdd1ApyfQ/0D+iEBN0weXHQsuIt63Kn9h98/e3ZbMjhFlF4M3IhpQrgSluiFwzPgR6HT74LCqkABohoDHF8DoEjsONXUiXMc+gTFo55wyIaE1M1O1kHhoEfHoumO+2MFYlx9dQ8iO2W0KimMtjdRrIH9RgRVOm8rsGJGJMHgjoqwyDAFDiOBPQwTrxhkChtGTRdON4KxNQwBzjq/AS3/9HJAELEpPwPWdU45EsomnRNfM7G8hcd0w0BmaSdmrzlj0OLLAkBcRj5xZGWtppMixZRaV2TGi4YrBGxGllBDBgCsUjBki+L/oDsjC94ngIunJZMoAYNrRo3DJd45N2SLlvdfMFELA69fCAdcXh7wYOdqHSUeUYNe+FrR0+KDIMhw2ZciLiNu7FxHvmVUZXaU/chyZw65yEXEiAsDgjYgSIERPIKbrweyYbgQDMt0AdD0YjIWyY8Enpa90RrKLlBuGQKcn9kD+YKYsejB/3+xYW+89xiyHIUtSzzJJvceKRWXHgtu4iDgRDQaDN6I8pEdkxUTop+juqhTRWTPdCN4ngJyqZebz6wPOqAx1XXa6B58dsygSRhTaotep7F1/rHtmpdNhYXaMiNKOwRuRSQgRXENUhAItAYjuMWIitB2AMBBeKF6EnhcOyoxgoBbeae4EY4Yh0OUNRFTkjzOrsrs7s/fKDomSJKDQYekVgPWUvSjuFZx9vqse06dPT/HZEhENXlaCt/Xr12PVqlXQNA3Lli3D5ZdfHnV/fX09brnlFnR1dWH27Nm48847oaoqDhw4gJtuugmHDx/G0UcfjRUrVqCgoCAbp0B5bqCZeaHgChEBlxGuwh8RbInIoKxnWygTJiKDtagDRP3IWf6AHnMgf3uvQCyUJRvsElKhRcRjLSTeezB/ocMCWWZ2jIgyo89fmwT//PT3sIwHby6XCw8//DCqq6thtVqxZMkSzJkzB5Mn91Rjv+mmm3DPPffgxBNPxPLly7FmzRosXboUd955J5YuXYrzzz8fjz/+OJ544gncdNNNmT6FvDLQMkRD3ccLmz7Dur9/AY9Pg8Om4qL5x+CHC49Lup21n7mw7u970dDiQUWpExedMQknH1cevn/7rgas/8cXaGz1oHykExecdhRmTi6DIYAdexrx1gf70NzuxagSB6ZMKMHu/S1obvdh9Ag7zpo1AccdOTKcvfr0y8N4fWsb/vO9zRhZZMeCWeMx7cjScLAWXMK9FwF88sVh/HXbV2hq9WBUsR3nnBocZF+3twmbPvwKTW0ejB7hwJSJJdi+qwGu7nU4y0udOKKsADv3NsPj0yBJgE2VMXHsiCEN1O993Mh9Rd5ntyqQAHj8OkYV2zH/pPE4oryoT9dk72WT2t1++Aa5iLiE4HJePetVRi+NVOS0oqnVjb//zzc43OqBEAJ2q4LzTzu639ejbm9TuF4dEFw94uIFk2Oed+g1Seb1fK37fQ4gXA8vVnv6e+3723+yz0mlRN8v2WhbPKlqV66e33AQN0BJ4vuV1Otn6B9S9z+C37V7/i1BQoHDCpsl+LdNkiREfh+P/HIeqxmS1LNPSQo+SOq+Q4o4RlRbIu6Lbkt4Y895dP/D5/Oh4Zs45yxEZpdLfu2117Bt2zbcd999AIDHH38cQgj8/Oc/BwB88803WLZsGd5++20AQE1NDR555BE89dRTmDNnDj766COoqoqDBw/iX/7lX/DOO+8kdFyfz4e6ujpMnz4dNpstLedWW1uLWbNmpWXf2bB9VwOefv2T4BqW3ZXnNV3gRxecgJOmlsd8TuTbSQjgf3c34D/fqIeqBtfDDJVYWHruNHx5sA1v/OOfkCRAkSUYIvjmXTzvKJz77aO7x1gF9xceAx8xNdHojpLqvzyMV/+2G4osQVXlYDs1ge8tmIzjjixF/ZeHUf23PVBkCRY1uJB6QDNQddZkCAAvv70bihxc5DpUd6vIaUGhwxpcTUAXWLJwajjQenHTLmiaH0UFjvD5hO6PJ/Q8RZGiSk3MnTEWH+w8GN7e4fajrTMAAJBldNcxi71Pp12B02YZ8NgDtceiSPD6dQQ0gTNOGg+PT8P7Ow8CCBaJ9QWCDZAl9ExGSAGrKkNRJMw6rgJTJo6MCtQKHP0vIl63twnPvBGc6SlLoe5hoNBpwRXnHR83YOrvOQBiX6Opdlxwdv+/13V7m/CfGz5FpzsQ/oNsiGAAuuz86PbEey/0dx0H85xU6u/4QOzXLVNtG0yb477O3Z8RsfYT/DsY3I+hAz/47hSckMD5pTLr0hOcSJAjggepO3oIFa0OPiQikAg9Vo7ex4ASDQ967at3ENKzXerzIClO4BIZ4IRvxXnsYGoUbt++HSeddFLSz8uk/uKWjGfeGhoaUFZWFr5dXl6OHTt2xL2/rKwMLpcLLS0tKCwshKqqUdtzhRACsqIE1/8LZV8iBhaJXt1cUTFzr98PEaczLOZTev1yiYg7I48fCnRCY6AAdNfUCm3v6aILWfv3vZBlQFVlGEJAVWToQsdrm/dg7ChnrKb3uf3q3/ZCFwYUocDjC2ZhvAEdr767B/sbOuDza5BlOdxFqBs6Xn5nD+ZMHxfzNYjl5Xf3oK3TF1VA1RfQse7vX2DS0hL813//E13eQHhpp9D9G7buAwDohgG1+9p1uAPQDIFOj4YCR3A2oICOTR9+hemTRmPTh19BUSRIkCFJUnCfEffHE3peqI2h572zbT+KCyzh7R6fHn4N5VDwYsSO3jxeHUVOa59jCyHg9mp9uifbI7ooP/uyGQGte/xbxEV7/R//jHsOsQK3ArsaVXOsZ7yYBcUFNhQ5LXj5nd3o8vrR1uGDYQCSLEEIAUmSUFxgRUOLB/+yeFrc48ay6cOv4PVrkCUJkhz8SAguDxX/Wgz0HAAxr9H2vV244OyB2+Px6ZBlKfxBIhvBkiO92xPvvdDfe2gwz0ml/o4vAcHlyiwqIAFORYZf0/FuzX5MnzS6TzYknsF0ZIcCl1DmJDLb8eEnh1A20g5r92cGJMAf0LCt3oVTpo2J+uAPJUNKih0odlrD+waA/93diCPKC2EJ/X0RAr6Aju2fN+KMk8b3Ooc+0UrM4KTnmFL8QIcTX9LKiPN31SwyHrwZhhH1pgz9ER/o/t6PAwb35v6fHfUApJgBUu8PJxE5RgndwVBkoBN8UPeHX/Axm7fURAwC7xttid4boo43UOujs1rptntfE2wWqc/1aDjcif/dWZfQPr74+nDMfbS0udHhMSBLgCz1dK0ZAvAHAqirS2z/AHCwsQ02iwSPHn2Mg43Bby393Q8g6r6Apnf/NODxeuPuS5KkmPcn20aPT0eBTUQcv+cPihjgj4sA0N7pxeE2D+576r/h9hnw+Ax4/MaQMmSSBChS8Bu8XxPhDzYIoNgpQ5KAgC5wxdllUPqMHQt0/w/AD3j8wOHWTtgsEjS9e1/dXxoCmg5d8w/42sVysLENmi4gd+8PweZB1wUONrbF3N9AzwEQ8xq5A2LA9h1sbIOmGZBl9GSLBaDr6NOeWO8FCIFDTT588kkdIsOYUMakubUTVosEQ+95T1hkgZa2TtTXf9pPy3oCk54foa4eKfhaRHQZRWZz0B0MyRKga36MKlLDQa8kARAyfJoGQwCji9TgXycpeN52qwyv14dDX+8NvXUiurZEz+3onqVBi9WB9NWBFtisEtwR2wwh0NTShS/3Rr9moeerAD7/bGfUfTt3u2C39v0b9tVBgU/rdoDMq7a2NttNGLSMB29jxoxBTU1N+HZjYyPKy8uj7m9sbAzfbmpqQnl5OUpLS9HR0QFd16EoSp/nJXz8I46EqlqGdhJxxEq5m9nYHR/3WRLIF9AxtsSe8Hn2tw/N1QFfQIMU2T1mGHBY1aRex4Ha2d/9AKLus7g9COg6LIoMh90ed1+GHoh5f6JtDBaC1WGzALpQoEgydENAkrRwjK4bA09I8PiDj/iq0R/3MU672mfB8Lq9TfAHdNgsChRZgixL0AwDJYV2SJIUbqur2Q1dD/ZnK7KMEUUO+AI6ygvt+NbMGQO0LvrcLaoPui4gycFPeFWRoajWpN5Pkfv854FWiO5MHoDgPlUJY8tGxNzfQM8Bet4LcndAE9ANFDl1zJjRd39S6H9Jwvt7dmD/oQ4IiO7nBr9wKoqEiWOLMWf2ieHnbP9qBzo8PthVJRy1+AI6ipw2nD73xIhuop7IZts/P0Z7pzeqLpzXr+GIIjvOnDe7e0usd0t391pUF1ryodIbH29Fc5sHNqsc/nLq9WsYWRxcHqyl3QO7tefjJHTfrJO+lfSxUqX8gy0x2zWmzIGTTz455nNiDX2Z8FHs/UwY5RhWw2TyjRmGOYW6TWPJePA2b948PProo2hubobD4cCmTZtw9913h+8fP348bDZb+IVdt24d5s+fD4vFgtmzZ2PDhg2orKzE2rVrMX/+/Ew3P6/0tyRQKvbx5cF2bNjyT+iGAUVCcGkjAXznlAkpbedA90fe57ApCHTpcNgUCCHi7kvTDNh73a/pRlStscilkSQJaG73RXQP93zQxit5MVDgJknBcXrHjB+BiWOKggFarzIXhU5LzEXE6/aO6jMeSBjAorlHRr0mRU4Lmtt9gABKiizwBfRBvwccNgUd7gAMI/jpX+hQkt5X5D6feaMTXZ4AVNEdEHYvH7X420dGdUHJCAYsF84/Bi//dRc8Pi2YMZQAAQmFDgsuPXsyJEnC2vf2QlUkqIoMX0BDQDMwd0oRykqcUd1dvYOgi+ZPwqrq/0V7VyAYcong+7nQoeLcuUehpKhnvMo5p07EH1/bEe6G9IXGaJ55LJz22F8sF845Equrd0BVo59z2TnHZWQZrIvmT8Lq6h0whIg6ftWC4ESz1dU74IUW875sqVowOSXtStV+iFIp4xMWgGCpkNWrVyMQCOCSSy7BVVddhauuugrXXXcdZsyYgc8++wy33norOjs7ccIJJ+D++++H1WrFN998g5tvvhmHDx/G2LFjsXLlSowYMSKhY4Yi2NHjjmHmLQmhWVZDWYaov328/o8v8M62/fD6NditKr5zygRccPoxKW9nf/f3vm/KxBJ8/lUrmlrdGFnswLenj8GY0QXhGZV7vm7FJ3saEdABRZFhswYnc7iHsIi43D3K3WZRMKLQio4uP9w+DRKAEUU2jBnpwBcHOsKBnt2SutmmA70mtu7Zpl6/PuT3wIGmTui6gKpIGDu6MOa+IrvTgGDwFRxLJge72WUJsiThs6+asWHrP9Fw2A1DAOUjnfjemZMw89jR3WOgglmnyCDr489ceHZjPb5p6AIgMG50If518TTM6p79HJoZ3dDsDs8WldxfJ/QNvabehWfe+BTfNHYCAMaVFeBH558Qc3Z2rOMMNIt7MM9Jpf6On+22xZNsu+JlY3L1/GjwzJR5izVhISvBWzYweCMAPYuIx1gwvL1PDbIANH2Qi4jLUncmrFcx2HCpC0tUN2as7JiZxQrAJEkKD+hXugMwWQ52YYa6KYMBlxR+bO/gKxvM8EeeUoPXOn+Y4Vrn1GxTolQSQsDn18OBWGRl/j4FYd0BuIeyiLhNCdcYg+7F+DGj+yyPFArOnHY160FHKkUGY0o4sAqW+ghlw6SIYEuOCNRyIQAjIhpOGLxRzglnx2JU5g8HZBHBWd9FxBMTuYh45ILhkVX6e7JjFljUnsHiwW9DyRcTziWRAVlw1q8cnrwgy1LPv6Xo2wzEiIiyi8EbZURkdqzv8kjRC4p3DSU7ZlV6LRzetzJ/KFBz2tVhu4h4T+kHCYosQ1V6gjBZkcLZMwZkRETmw+CNBsUwBDo9gdhLI8UI0vyBwWXHJAk9a1X2Hj/m7JstiyylMNxJUnAsmaLIULv/V5RQUNaTRetPKpY/IyKizGLwRmH+gB5dkb9XRixyHctO9+CzYzaLEhWIRQdk0d2YBfb8XkQ8tNSSIsuwqDI+39+C9z7+Gg0tHowstmHxt4/CyVMHF2zV1LvC5SeKHCpa2j1YXb0DqJrJAC6DzBRAp6OtZjp/olzB4G0YM4SA2xOIGrDfd7mknsH98eqNDUSSgEJHjKxYZEAWsc1mzZ/s2EBC485CAVpofVZV6c6eKcF/S5KE2s9ceGpdXbg+2NeuDqx6ZQeuGWSwVb15T3BZo+7io3arCi80VG/eww/PDDFTAJ2Otprp/IlyCYM3k/EH9NgD+WNs63QHYAyyEoxFlfsGYQWWPsFZUYEVhY78zo71JxScyZIEVQ52a6oRXZuhcWdKAqVCXv3bHihK8sFWvMyGq9mNIkf0nwCbRUFDszvOnijVzBRAp6OtZjp/olzC4C3LjNAi4l19uyajxpF1d2P6/IPMjgEoCGfHooOwDrcfu/a1oMMTwKgRdiycMxEnTSnnIPYYQsVmDza2YdzOj7FozpE4YdKocOYsNO5MUYJBmarIkLszagMZqPuov2Ar3nP7y2xUlDr7LPvjC+goL3UOqZ2JGmg/2epO633cGUcIpKscVKIBdC50LaYj2OcXCKLBYfCWBgHNCAdh0WUuYowfCy0XNAgWVQ5nv4qdvWZVhgbyh7JjTgsUOdYySU3hZZJKCizweAOofncPrKoy6Mr9sY6x6cOv0NTmwegBKvQn89hUGeiYoezZri9b8NbWL2G1yjiyogCKRcYbW77Au7VfocujwWqRYRhAhzuAspGOpD5gE+k+ihds2W1K3Oc+88anaOnwQTcELKqMkiIbVFVC9eY9g1r2J7KdsgR8vq8Fd//5Q0yoKIy7mkC8/fzhxY/h8WnQDYG2Di/+8OLHuH7JyQMGnekMWmId981tXhw72ZWW4yYSQOdK1+Jgg/1M75MoHzB4S4AQAm5fMDsWHsgfUWcstK2ppRP+v74Hj2/wyyQV2FVYLQo63H4oigyLIkEgGEDMP+kInHDMqHBBWJtVGXJ2bNOHX4XHUAHBb70+6Nj04VcpCZoig8MCm4K2Ti9e3LQLSxaiz/6TeWyqfPJFE6rf3Q2LRUb5CDsMGPjrh/swosCKGZNH47MvW/DWh/vganaj0+2HRZWgqDa0d3ohJAMNzW6oioSRRTZ8dcgLACgb6Uj6Azay+6jLE0Brpw/+gIEVz9Xil5fPwuxpFXGDLVWRENB1tHUF1+K0qDKcdhXPvPEpvnJ1QJYARZag6QYaWzwocqpwNXuwqnoHHDYFEiR0erSElv0JtVM3gKZWLyQJUCTgUFNXUuf79BufoMMdCJYvkaRw0Pv0G59g9rSKjHWn9c5odXT5+xzX40XauvESCaBzpWsxHWt8ct1QosHJ2+AtoBnodPfqmuydKeseQ9bp9kctJJ4MVZFi1xkLlbeIHD/mtEBRZKx8/mNYLXI4oAKC30b3fN2GC+dPStVLAABoavOgwBY9gcCqyjjc5knJ/pMJDtMZSAaDDAmqooTHnMky8PGuBpSOsMGiBhdJ14WA2xvA61v+CVVVohYDP9wWDFYMA4AAWjt9kKTgIvNtXf7w+qRtnX6MLytI6gM21H3U5QmgsdUDCRIUGfD6tOigqGpm1BqLMyaNwot/3RVsE4LvN00TaOv0o6XDB4sid98XzJRpwkBLhx82i4wihxr+sPxJgkFXqJ0HmtzBUiVS8MuFbohwRi+R/Rxo7AqvzBC6PjAEDjR2RR0nUqq702JltA40uVE+0hH1OIsipa0bL9Y1Taa7PJMSaWsu7JMoH+Rd8Pb7Fz7GgSYv3EPIjjntasSA/Z7xYx2tTTju2KMiujKtsNuSz46lO6CKNHqEA22d3qhA0a8ZGDXC0c+zEpfMuQz1vKWoWZsyVDU4OSCYwZRjTgrYvb8NRQ4VXn9PHTpZknDosLtPxsNqUeDXdLR2+lBSICOgGZAAqGrw36H1OQOagS5PAC0dPhxocmP5qi0DfiCFuo9aO32QEAwuDQFYLXJUUBT6H+gJPkJzUiQAmi5gUSUIAQgBjCyyoanNC8MIvj66HnxwabEdkiQlncUJtdPn1yAQPEbwNZCSDih6fx0KZZgjj5PO7rRYGS2LIqGl3YdCR8/6xwFdYFx5+rrxIq9pLLnUtThQW3Nln0TDXd4Fb02tHrh90YP+FVnqtTZlRNmLqHFkwUAt3iLidXVuTJ9aPuQ2pjugirRwzkS8uGkXfNBhVWX4NQO6LrBwzsSU7D+ZcxnosVEzN0NFaWUpXJg2dDuZYLm/D8beGY+SIhsamt3wBwwIIXV3RQqUFNrQ2umDpolgACIBja0eCASDz/66UEPddl8dakeXJwCtO7iSjOB5lpTY4gZFoeBDliToEbOKNd0Ir6agqjLKShxo7fSFlxGzKBIKIoKTZIKuqgWT8YcXP0ZkIlogmI1s7fRhXFlRQvsZX1aI/a4OGEJAlgCjO9g8orwwfJx0d6fFymiNLLKhsdULr7/nuIaOrHbjsWuRiHrLu+Ct8oxjYLfboir0O225tYh4ugOqSNMnjcaShcEuy8NtHoxK8SSBeOcyZWIJVj7/cdQkgUVzJuKVd3dDkgCHXYUQwSznpedMQWmxLVz3LJGZm4nq74OxevOeqMCuwK6ipMgGr1+H129g7OgCtHZ4oSgSRhRY0djqBUTwy4ABQIKEkcX2uNmtyG47h01Fe6c/ZhvjZVlCwYfVIsMfMIJlYQQAAZQU21DktMLr06CqEsaNLoAvoKOh2YOiAmtC+4/H22vGs9o9LrOjK4CqSxMLKJadfzweeWk73F4Nmm5AVWQUFliw7PzjAaSuO62/WZqxAndVlXFERSGKC2zh484/3p7VzBC7Fomot7wL3uZMHwtVtQz8wCxKd0AV63hD3XfvGZtTJpbg869a0dTmgd2qQALg9ukoG+nEcUeWoLa+AVaLjHGjnBBCYHPNfnz/7GNxTdVMbHz/y+4VBOyoPP1ozDoufR9S8T4YAaCjy48DTW5YuickqGqw+/Xnl58Iyf01Zs2aFQ4OGprdOKKiEBIkfOXqgFWVMbLYjgJ78FcsVnYrstvum8YuqKoMXTdgCECVZQgINLd5MbLIFjPLEgo+SgptaGz1QJWCz1HkYDtDgVDkuc0/6Qi8u21/VGYp0SxOKNgMaAasqgRdAIYuIERw5rPdqiYcUMyeVoHrfnBSvwHJULvTBpqlGS9w//GF0bNma2trB92GVGHXIhFFyrvgzSxSEVBlSu9Zoo0tXdh3sA0ji20oH2nvHhcl4d8unILpx4zCH17ajkKnCouiQDcEdAPo8vpQ/d5e3PfT09IarMXS+4Mx8kO/fKQDLe0+NLZ6cURFYfiDvbb265jPBYDlq7YkNEYpstsuoBlQZEBSguPndEPAEAK6oePsUybE/OAOBR+qKmH0CDtaOnwI6MARowuw7Pzjw8/p/dxjJ4wcVBYnFGxaLXJwlqsswZAEVEXGqBE2jCxOrls/3QHJQLM0zZrRyoWab0SUXQzeaMje2/4NRhRaUeCwwKLKUNq84QXird0BWpfXj7Xv7cWpx4/Bnq+DkwQCWs/AKauaO4U5e3/oFzos8Po1FBfYEvqQTHSMUmS3nUWVoelGeEUMRZGgiOBszHe37cexE0b2OXbv4GPKkaUJfZAPNmgKBZuhTF9wEoSAPwfGYMUKaBKZpZnqADLdgVWu1HzLNAasRNEYvFFCeiYLoLvcRnDNTVWR4fEF4LSr0HQBrz+Arxu6IEsChgAKHcHxVYoshz80c2n2XCxDLc2QaEYnMsgbUWhFY4sHuhEcwI/u4WulxXYoSvwSHEMJPpL9QAxdt9Bkh2AtOgG7TR30+qqpEC+gcdqCpVASeZ+lIjhINrAazDFTWfMtE4FmqlbiyMeANV0YCA8PDN4oSihIU7uXerKowVIbiiJDjbMGp8NmiQrGLKoMvxacoBAS+aGZ67PnUhFcJhJU9Q7yJlQU4StXe3A2rSqhpNCOAocFQoiUZyUH84EYed2cdhVKd025bAZuQDCgiVWk2AYFmiZivs8iP8CcNhWtHV4UOi1DCg6SCawGG5CkquZbugOiVO4/V4oUDwcMhIePgVfDpmFJ6s6iWVUZTpuKYqcVpcU2jC5xYExpAcpLnSgdYUdRgQ1OuwU2ixJ38fSqBZODH5J+DUIIOO0q0D1TVIjg9sjgbPa0ClxTNRMjix3o9GgYWezIegAQqff59G5/Ks2eVoH7fnoa/nTLd/HoL8/CCceMxphRTowvKwxnuNKRlYz8QAzVewvVk+uvrbl43b461I62Tj80TUCWeooUt3b4YrYXAFZX70BLuwdFDhUHm7rQ4Q5A10XCr0UsrmZ3VJkbIH5gNZjXHwh+sfAFomf7Dub9MdjjZ2P/ybyu1L90X3fKHGbehrnQygLhQrWqBLW75IaqJFcTLZ7eGaRxZYVYNPdI7Nx7OG0zCdMp3koG1Zv3YFX1jrQuVp6prORgMzi5eN00PVhfT4lYrUEzBDRdxJ1QEpnJCXVVt3b6wgHzYIKDZDK2g339U/X+SPeqDancf64PszCTXFmtg4aOwdswIUnBNKqqKrAowar8/a0skGqxPiR/mPajpk+slQwysVh5pmZADqcPRIsiwysQVfAXIrg9lt4fYBZVRkDTw0WMgcG9FokGVjX1LnR5Ajjc6oHVIqOk0IYChyWhY6bq/ZHu65/K/ef6MAszGU6/9/mOwZvJRI5Js6jB/9XuAM2ishc8HWKNuUnnYuWZyG6Z9QMx1mDrCWOKcKCxE25vxJi3AhXjygpj7qP3B1ho5QxVkSCEGPRrkUhgFfoiYLcq8Po0+DUDja0e+DUdFkXBjEmjsHzVln4Hk6fi/ZHu65/K/Zu1pEsuMuvvPfXF4C1HhTNpigJVlbvX6AwtASWHF/Sm9IvV1ZDOxcozIfSB+PQbn+ArVyeA4JJVuSgUsO0/1AG3N4CiAgtKCm3hwdZnnzIBjc1ujBoRXEqstdOP9i4/NL095rqyvT/AFBkoLrCiuNCKTo82pOBgoMAq9EWg0GmD1aKgtcMHfyC4Ysei+Ufh3W37MzKYPN0BUar3n4vd9WbEQHj4yLvg7al1dTjtxAk5UQA3lEVTJAkWVekOzqTuRdXluGuoUmbF6mpIxWLluTBl3+fTUVHqCH8Lz7WZZ5Fd1l6/Bl0EJyNYVQUFDgu80LBz72Fc0/2BFArwinsFeJHnFOsD7McXZua1j/wiUGBXUdA9qafTEzyPTM6qTHdAxIArN/G6DA95F7x1uH14cdMuLFmIjAVw/ZbfSPFanZR6sboahrpYebqm7CcTEJqhBENkGzW9e1UHo2dyQWiwdegDqffqFvHOKVsfYP2NOeJgciJKVN4Fb1ZVgaIY2PThVykP3mRZhiQBqixBVZRwkKZ2/8+uTnOKlalJdrHy3kFVe5dvSIFTrCANQFIBoRmCBVezG7IEfNPYBV03oBvBWaWh1Tl6D7bO9XPqb8xR9eY9fcfu2eOP3SOi/JV3wRsQrG12uM0zpH2ESnCoSncXpypjVLENFaUFzKQNQ70zNcksVh4ry3agyY3yEjtg7XlcokFGvKyd3aYmFRCaYeaZ06Ziv6sDshwc86npwRIgVlWOWX8v18+pvzFHu/e34NMvDncPpQD8mg5/h45Fc4/MdrOJKMfkZfDm1wyMGpHYItpSxJJQlvDEgdglOIShMXAbxqKq8lt0CGdipUJidU9aFBktHT4UOnuit0SDjHjdnd80dmJiRSG6vBpaO3wIaAZURUKnW4u5nxmTRuGVd3ZDNwQsqowChwqLouTUzLNgBTcAApAlCYocrMumGQZGFjsGnIyQi7Pp4nXZ7tx7GCVF1nDmzdqdedu597Cpy+4QUerlXfDm13TousDCOROjtksIBmrhIK27mC0nDhDQN9vV2uFLeIxarK68kcU2NLR44PUnH2TE6xoEgNZOP9o6/cHMsAwEdAOGN4Ca+uhAs6behXe37UdRgRVdngACmoH2rgAu/c5ROTPeDQA8Ph1lJXa0dfmDAY1FxogCKwQk3PfT0/o83syz6VzNbpQU2jCyyB7eFrk0Wi5McCGi3JB3wVtpsQMXnDEBMyaNDmfSQgGaqsgpWXGAzK/3B2VHlz8q22VVg6tVJDJGLVZXnqpImFhRhKICa9JBRryuwXFlBTjQ2AUBARnBgf0SgKICS592RpasGFlkAwB4/VrOZXlC5xpZxsTrDy51FY/ZZtOF3mst7V60dQClxfY+S6NxTUoiipR3wdsNPzwJBQ4HJw9QXHHHqI2MDhgSHaMWryvvxxceP6gP3vj7OwG/f/Fj+Pw6ND044L2k0A6nXe3Tzlwf2B9ihm7QoYh8r40aYUdjiwcNLR6UCQFVlaMmM+T6zGAiypy8C96sqsLAjeKqqXdhxXO18Po0WC0KSopsKLCrsCgSWtp9KOzOiACJj1FLR8HSyP05bCoURWBV9Q5oukCBQ43qevP6tT7tzPWB/SEDvXZm70rsHZRJkoTmNi8Ot/tw3FGl4fNZVb3DFME2EWVG3gVvRPGEsiBenwZFBjTdQGOLBxjpwMgiGxpbveExan7NgAWJZ4BS3ZUX2l/vLKGuG2jt8AEASgptcTNVZspoxXvthkNXYu8MaIFdhdNWgE6PFjWmzyzBNhFlRsaDtwMHDuCmm27C4cOHcfTRR2PFihUoKCiIeozf78ctt9yCuro62O12rFixApMmTUIgEMCcOXMwYcKE8GOrq6uhKEqmT4OGoVAWxGoJdlfJsgQDAq0dPowaYcMRFYUoLgiug1nkULGsMvtBQu/MTc/4Nb3fpZ7MPLA/JJGuxGxl5hI9bqJBmZmCbSJKv4wHb3feeSeWLl2K888/H48//jieeOIJ3HTTTVGPefbZZ+FwOPDmm29i27Zt+M1vfoM1a9Zg165dOOmkk/DUU09lutmUB0JZkJJCGxpbPcEB/5KAP2JMWegDuLa2FrNyINCJt+5qe0CHiOjijcVsA/tDQoHRJ18chlWVMbLYjgJ78DWI7ErMVmYumeMmGpQNh2CbiFInozUwAoEAtm3bhkWLFgEAqqqqsHHjxj6P27x5My688EIAwCmnnILm5mYcOHAAO3fuRHNzM6qqqnDZZZfho48+ymTzaZirKHXCF9BR4LCgrMQBVZWgG4DdpuKaHO2KC7U5pMsTQGOrF7IUHTjU1Luy2MrUCQVGLe0eWFUZge6u7S5vsJZdZNYqMjMnScGfavcM4XRK5rizp1XgmqqZGFnsQKcnOIs23ntt9rQK3PfT0/CnW76L+356Wk6+H4koMzKaeWtpaUFhYSFUNXjYsrIyuFx9P1QaGhpQVlYWvl1WVoZDhw5BkiR85zvfwTXXXIPdu3fjqquuwvr161FaWpqxc6DhKzIL4rSrwYr+msjZwA3om7lpbvcCAEpH2MOBQ7pmJSbSNZjqbsvIwCg4DtEDAYGWdi8U2R6VtcrWjNpkj2vWDCgRZU/agrc333wT999/f9S2I488sk8dtVh11YQQUduFEJBlGUuWLAlvO/744zFz5kx8/PHHOOeccxJuV11dXcKPHYxklk2i3CIBOHumA1vrO3G41YuSQhXzZxZCcn+N2tqv+zw+F6517zZruoFihwwYfnS5/QCCvz/7D3pT2t7PD3jw5rZWyEqwm/ZAgw+PvLANi08pwZRxjoQfk6z9B1tgt0ro0oLnVuSQ0OUV8AV0qJIWdb2cFh2tHT5Y1Z4OBr9moMihJv1aJPP4VB6XMo/XKH+Y+VqnLXhbvHgxFi9eHLUtNOFA13UoioLGxkaUl5f3eW5FRQUaGhowcWJwFYSmpiaUl5dj7dq1OPnkk8PbhRCwWPof19Pb9OnTYbPZBnlW/autrcWsWbPSsm/KjFmzgB9WDvy4XLrWkW1evmpLnwHwXr+GCaMcKW3vqx9tQUGBvc9xdn4t4YeVs/p9zJZdfuz8WhpUNm7CR9HnV+AECrqL9vZecUE4g12siiqFx5NZILCscmZS4xWTvdapOm48Zi+Pksty6fea0ssM19rn88VNOGV0zJvFYsHs2bOxYcMGAMDatWsxf/78Po8788wzsW7dOgBATU0NbDYbxo0bh127duHPf/4zAOCLL75AfX19zr/4RJlUtWAyNE3A69cghIi5eHsquJrd4SW5Qnp3DfZ+TJdXg+uwG/sOduDzfS2QJSQ9Ji+Z80tmPFkiaupdWL5qC35871+xfNWWuG1O9XF7tyE05m84jmkkosRkfLbp7bffjptvvhmrVq3C2LFjsXLlSgDACy+8gIaGBlx//fX413/9V/z2t7/F+eefD6vVioceeggA8LOf/QzLly/HBRdcAEmS8OCDD6KwsLC/wxHllUzNSkykxEXkY7q8GhpbPND04ELzhhBoavWibKQjPJg/kTYme36pGk+W7MzVdI1j40oLRARkIXgbP348nn322T7bf/jDnhUVbTYbHnzwwT6PKSwsxCOPPJLW9hHlmmS7yTIxAD6REheRj2lp90IgGLipsgRZ6qmhN260M6lJBNkY4J8rQZNZljUjovTKaLcpESUnV7vJEukajHyMXzNgUWRYVTk8GUmWgIBmmGKlgES6iTOhd2kYgCstEOUjLo9FlMNyJeMTSyIZsNBjQhMpdF2ECyALCCiybIqVAnJleSqutEBEADNvRDktVzI+QxWaaKAoEkaPsEOWAUMAY0cX5HQdvZBMTQQZSDonQxCReTDzRpTD0pXxyXS5id4TDaYcWWqqEhe5tDwVi/oSEYM3ohyWjm6ybK35afagw+ztJ6Lhg92mRDksHd1k2Vrzk4iIUoOZN6IsSbTrMtUZn3wqN8HVCIhoOGLmjSgLslkCJF/KTeRqmRUioqFi8EaUIokunwRkt+syV2ZOphu7h4louGLwRpQCyWZ5slkCJF/KTQyXMitERL1xzBtRCiRbTDfbRV/zYeZkf68xx8IRkZkx80aUAslmefKl6zKb4r3Go4ptuP/pj/DpF4fR3unDgcYOjoUjIlNh8EaUAslOAsiXrstsivUan33KBGzZcRC6EAAEfH4dh9t8aGrz4Ok3Psl2k4mIEsJuU8oL6e4mG0wx3Xzousy23q/x8lVbYBgCEgQ0o+dxmi7wtasTNfUuXhMiynkM3mjYy8SKArm0fBLF52p2w6LK4SypJAEQgACgKnLcMYr94fg5Iso0Bm807CU7mWCwmEnLfRWlTui6Aa+/p4tbAJAAjCy2JT0TNVtLjRFRfuOYNxr2WDKCQqoWTIZFkaEqwT99QvQEbqoiJT3bl7XkiCgbGLzRsJcvKwrQwEKTGMaXF0CRJdgsCipGOeG0q4Oa7csvBkSUDQzeaNhjWQ6KNHtaBR775dm49d/mYMqRIyEEBj3bl18MiCgbOOaNhj1OJqBYUjFGcTCzjImIhorBG+UFTiagdOAXAyLKBgZvRERDwC8GRJRpHPNGREREZCIM3oiIiIhMhMEbERERkYkweCMiIiIyEQZvRERERCbC4I2IiIjIRFgqhChP1NS7UL15D1zNblSwHhkRkWkx80aUB2rqXVhdvQMt7R4UOVS0tHuwunoHaupd2W4aERElicEbUR6o3rwHqirBblUhScGfqiqhevOebDeNiIiSxOCNKA+4mt2wWZSobTaLgoZmd5ZaREREg8XgjSgPVJQ64QvoUdt8AR3lpc4stYiIiAaLwRtRHqhaMBmaJuD1axAi+FPTBKoWTM5204iIKEkZD94OHDiAyy+/HOeeey5++tOfoqurK+5jt2zZgmXLloVvCyHw4IMP4txzz8V5552H2traTDSZyPRmT6vANVUzMbLYgU6PhpHFDlxTNZOzTYmITCjjpULuvPNOLF26FOeffz4ef/xxPPHEE7jpppuiHmMYBp5++mmsXr0aU6ZMCW9/6623sHfvXmzYsAH79u3DNddcgw0bNkBVWfGEaCCzp1WYMlhjiRMiomgZzbwFAgFs27YNixYtAgBUVVVh48aNfR63d+9e7N27F3fffXfU9vfeew/nnXceZFnG0UcfjbFjx2L79u0ZaTvRcFJT78LyVVvw43v/iuWrtuRsyRCWOCEi6iujwVtLSwsKCwvDmbKysjK4XH3/CB977LG49957MWLEiKjtDQ0NKC8vD98uKyvDoUOH0ttoomHGTAERS5wQEfWVtv7GN998E/fff3/UtiOPPBKSJEVt6327P4ZhRD1eCAFZTi7+rKurS+rxyeI4vPxh1mv9zDuNCGgaJMhwa8FtAc3AM+u3Q3KXZbdxvew/2AK7VUKX5g9vE0Jg/0FvRl9/s15rSh6vdf4w87VOW/C2ePFiLF68OGpbIBDAnDlzoOs6FEVBY2NjVCZtIGPGjEFDQ0P4dlNTU1LPB4Dp06fDZrMl9ZxE1dbWYtasWWnZN+UWM1/rJzb+FSVFtqgvQk4h0OnRcu6cJny0BS3tHtitPX+qvH4NE0Y5MtZWM19rSg6vdf4ww7X2+XxxE04Z7Ta1WCyYPXs2NmzYAABYu3Yt5s+fn/Dz58+fj/Xr10PXdezbtw9ffvklZsyYka7mEg1LZqr5xhInRER9ZbxUyO233441a9bgvPPOQ01NDW644QYAwAsvvIA//OEP/T733HPPxbHHHosLL7wQ1157Le69917Y7fYMtJpo+DBTQMQSJ0REfWW8xsb48ePx7LPP9tn+wx/+sM+2OXPmYM6cOeHbkiTh17/+NX7961+ntY1Ew9nsaRVA1UxUb96DhmY3ynO8/IZZS5wQEaULC6QR5SEGRERE5sXlsYiIiIhMhMEbERERkYkweCMiIiIyEQZvRERERCbC4I2IiIjIRBi8EREREZkIgzciIiIiE2HwRkRERGQiDN6IiIiITITBGxEREZGJMHgjIiIiMhEGb0REREQmwuCNiIiIyEQYvBERERGZCIM3IiIiIhNRs90AIiIAqKl3oXrzHria3agodaJqwWTMnlaR7WYREeUcZt6IKOtq6l1YXb0DLe0eFDlUtLR7sLp6B2rqXdluGhFRzmHwRkRZV715D1RVgt2qQpKCP1VVQvXmPdluGhFRzmHwRkRZ52p2w2ZRorbZLAoamt1ZahERUe5i8EZEWVdR6oQvoEdt8wV0lJc6s9QiIqLcxeCNiLKuasFkaJqA169BiOBPTROoWjA5200jIso5DN6IKOtmT6vANVUzMbLYgU6PhpHFDlxTNZOzTYmIYmCpECLKCbOnVTBYIyJKADNvRERERCbC4I2IiIjIRBi8EREREZkIgzciIiIiE2HwRkRERGQiDN6IiIiITITBGxEREZGJMHgjIiIiMhEGb0REREQmkjcrLAghAAB+vz+tx/H5fGndP+UOXuv8wWudP3it80euX+tQvBKKXyJJItbWYaijowOff/55tptBRERElLApU6agqKgoalveBG+GYaCrqwsWiwWSJGW7OURERERxCSEQCARQUFAAWY4e5ZY3wRsRERHRcMAJC0REREQmwuCNiIiIyEQYvBERERGZCIM3IiIiIhNh8EZERERkIgzeiIiIiEyEwRsRERGRiTB4S8KBAwdw+eWX49xzz8VPf/pTdHV19XmM3+/HTTfdhMWLF+Piiy/G3r17AQBdXV24/vrrUVlZicrKSrzxxhuZbj4laP369TjvvPOwcOFCPPfcc33ur6+vR1VVFRYtWoRbbrkFmqYBSOz9QbllsNe6trYWl1xyCS666CIsW7YM33zzTaabTkka7LUO+fTTTzF9+vRMNZeGYLDXuqGhAVdffTW+973vYcmSJfj6668z3fTECUrY1VdfLV5//XUhhBCPPfaYeOihh/o85k9/+pO47bbbhBBCfPTRR+LSSy8VQgixcuVK8cADDwghhGhqahKnnXaaaGxszFDLKVGHDh0SZ511lmhpaRFdXV2isrJS7N69O+ox559/vti+fbsQQojf/OY34rnnnhNCJPb+oNwxlGt91llnifr6eiGEEC+//LL4yU9+ktG2U3KGcq2FEMLtdoslS5aIKVOmZLLZNAhDudbLli0Tzz//vBBCiOeff15cf/31mWx6Uph5S1AgEMC2bduwaNEiAEBVVRU2btzY53GbN2/GhRdeCAA45ZRT0NzcjAMHDuDUU0/Fv/7rvwIARo0ahZKSEjQ1NWXuBCghW7duxdy5c1FSUgKn04lFixZFXedvvvkGXq8XJ554IoCe90Gi7w/KHYO91n6/H9dffz2OO+44AMDUqVNx8ODBbJwCJWiw1zrkgQcewLJlyzLdbBqEwV7r5uZmfPbZZ1iyZAkA4Pvf/z5uuOGGLJxBYhi8JailpQWFhYVQVRUAUFZWBpfL1edxDQ0NKCsrC98uKyvDoUOHcNppp2HcuHEAgA0bNsDv92Py5MmZaTwlrPf1Ky8vj7rOsa6vy+VK+P1BuWOw19pqteKiiy4CEFwz+bHHHsM555yTuYZT0gZ7rQHgnXfegdfrxbnnnpu5BtOgDfZa79+/H+PGjcMDDzyA73//+7juuutgsVgy2vZkqNluQC568803cf/990dtO/LII/ssaB9rgXshRNR2IUTUgrJvvvkm7rvvPvzpT38Kf9BT7jAMo8/1i7wd7/7ejwNivz8odwz2Wof4/X7cfPPN0DQN11xzTWYaTYMy2Gvd2NiIVatW4emnn85kc2kIBnutNU3Dp59+il/84hf4zW9+g5dffhk333wznn322Yy2P1HMvMWwePFi/P3vf4/6/89//jM6Ojqg6zoAoLGxEeXl5X2eW1FRgYaGhvDtpqam8OOeffZZPPjgg3jqqafCXS6UW8aMGYPGxsbw7d7Xuff9oetbWlqa0PuDcsdgrzUQnIB05ZVXQtM0rFq1Kqe/odPgr/XmzZvR2tqKyy+/PJxtveiii9DZ2Zm5xlNSBnuty8rKUFBQgLPOOgsAcMEFF2DHjh2Za3iSGLwlyGKxYPbs2diwYQMAYO3atZg/f36fx5155plYt24dAKCmpgY2mw3jxo3D22+/jaeffhovvPACpk6dmtG2U+LmzZuH999/H83NzfB4PNi0aVPUdR4/fjxsNhtqa2sBAOvWrcP8+fMTfn9Q7hjstQaAm266CUceeSR+//vfw2q1ZqX9lLjBXutLL70Ub7/9NtatWxf+u75u3ToUFhZm5TxoYIO91hMnTsSYMWPw3nvvAQD+9re/4YQTTsjKOSRCEkKIbDfCLL755hvcfPPNOHz4MMaOHYuVK1dixIgReOGFF9DQ0IDrr78ePp8Pv/3tb1FXVwer1Yp77rkHJ5xwAi688EI0Nzdj1KhR4f3dc889mDFjRhbPiGJZv349Vq9ejUAggEsuuQRXXXUVrrrqKlx33XWYMWMGPvvsM9x6663o7OzECSecgPvvvx9WqzXu+4Ny12Cu9Z49e3DxxRdj8uTJ4aEP5eXlePLJJ7N8NtSfwf5eR5o6dSp27dqVpTOgRA32Wn/xxRe4/fbbw2OYH3jgARx11FHZPp2YGLwRERERmQi7TYmIiIhMhMEbERERkYkweCMiIiIyEQZvRERERCbC4I2IiIjIRBi8ERGlkBACv/71r/HUU09luylENEwxeCMiSpG9e/di2bJleOutt7LdFCIaxri4JhHRAD788EOsXLkSY8eOxT//+U84HA5cffXVePbZZ/HPf/4TCxcuxPLly/Hcc8/h0ksvxbhx47LdZCIaxph5IyJKwM6dO3H11VeHl0f64x//iNWrV6O6uhrPP/88XC4Xfvvb36KysjLbTSWiYY6ZNyKiBBxxxBE4/vjjAQATJ05EUVERrFYrSktLUVBQgLa2NlRUVGS5lUSUD5h5IyJKQO91LkPrmhIRZRqDNyIiIiITYfBGREREZCKSEEJkuxFERERElBhm3oiIiIhMhMEbERERkYkweCMiIiIyEQZvRERERCbC4I2IiIjIRBi8EREREZkIgzciIiIiE2HwRkRERGQi/z8XmWTWGU2G+wAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 720x432 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.regplot('m1', 'unemp', data=trans_data)#绘图数据和线性回归模型拟合\n",
    "plt.title('Changes in log %s versus log %s' % ('m1', 'unemp'))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 109,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<seaborn.axisgrid.PairGrid at 0x246617f3730>"
      ]
     },
     "execution_count": 109,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x720 with 20 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.pairplot(trans_data, diag_kind='kde', plot_kws={'alpha': 0.2})#diag_kind对角用图\n",
    "#pairplot:pair是成对的意思，即是说这个用来展现变量两两之间的关系，线性、非线性、相关\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Facet Grids and Categorical Data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 111,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\ProgramData\\Anaconda3\\lib\\site-packages\\seaborn\\categorical.py:3704: UserWarning: The `factorplot` function has been renamed to `catplot`. The original name will be removed in a future release. Please update your code. Note that the default `kind` in `factorplot` (`'point'`) has changed `'strip'` in `catplot`.\n",
      "  warnings.warn(msg)\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<seaborn.axisgrid.FacetGrid at 0x246614e4700>"
      ]
     },
     "execution_count": 111,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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4QH5+folXoD4jdAAAAAAwitABAAAAwChCBwAAAACjCB0AAAAAjCJ0AAAAADCK0AEAAADAKEIHAAAAAKMIHQAAAACMInQAAAAAMIrQAQAAAMAoQgcAAAAAowgdAAAAAIwidAAAAAAwitBRQenp6YqJiVF6erqrSwFcis8CAAAoL3dXF1DXrF69WocOHVJ+fr6Cg4NdXQ7gMnwWAABAeXGmo4Ly8/NLvAINFZ8FAABQXoQOAADqGC5vBFDXEDpQ4/hjCQBVs3r1au3Zs0erV692dSkAUC7c04Eax70AAFA1XN4IoK7hTAdqHH8sAQAAGhajoSM5OVlhYWHq06eP1q5dW2r5p59+qoiICPXv318TJkxQTk6OJOnYsWMaPny4QkNDNX78eJ09e9ZkmQCACjpvL27Q+wcAVIyxy6syMzOVkJCgxMREeXp6aujQoerSpYtatmwpScrLy9OcOXO0ceNGBQYGasmSJVq6dKlmzZqluXPnatiwYXr44Ye1bNkyLV++XLGxsaZKBQBUkKeHm4ZNK/2fSeVx4kSuJOn4idxKb2PdouGVagegtPP2Ynl6uLm6DNRzxkLH9u3bFRwcrKZNm0qSQkJClJKSokmTJkmS7Ha7Zs+ercDAQElSq1atlJycLLvdrp07d2rZsmWSpMjISI0YMYLQAQAAYAD/iYCaYOzyqqysLPn7+zunAwIClJmZ6Zz29fVV7969JUnnzp3TypUr9dBDD+n06dPy8fGRu/uFPOTv71+iHQAAAIC6xdiZDofDIZvN5py2LKvE9EW5ubmaOHGiWrdurUceeUSZmZml1rtUuyvJyMioXNHlUFhY6HzdvXu3sf3UZ/Rh/cD7eEGnTp1cXUKZ/V/ZGq80ltaF467P+PzVD7XlfawNn+fa4ErvAX1UdcZCR7NmzbRr1y7ndHZ2tgICAkqsk5WVpdGjRys4OFgzZsyQJPn5+Sk3N1fFxcVyc3O7ZLuyBAUFycvLq+oHcQkXt+vl5cUvYCXRh/UD72PtYar/TY6l1aEh/97x+as9HEV2NXL3qFTb6ngfq7J/lMRnySxjoaNr165aunSpTp06pauvvlqpqal67rnnnMuLi4s1btw49e3bVxMmTHDO9/DwUOfOnbVlyxaFh4dr06ZN6tGjh6kyAQAAKq2Ru4d2LxpTqbaFpzOdr5XdRqdpr1eqHVDTjIWOwMBATZkyRSNHjpTdbtegQYPUvn17RUdHa/LkyTp+/Li+++47FRcX65NPPpF04X/VXnjhBc2ePVtxcXFasWKFmjdvrvj4eFNlAgAAADDM6BPJw8PDFR4eXmLeqlWrJEnt2rXTgQMHLtmuRYsWWrNmjcnSAAAAANQQnkgOAAAAwKgGFzpqw1Nsa0MNgHThBsSGvH8AAFAzjF5eVRtV5QE4Eg/BQf3CDZAAAKAmNLgzHQAAAABqFqEDleLqS8RcvX8AAACUX4O7vArVoyqXqXGJ2gXn7cXy9HBzdRkAAADGEToAF6nq/UXVoT6ENwAAUPtxeRUAAAAAowgdAAAAAIwidABosNLT0xUTE6P09HRXlwIAqCQv90YlXlE7cU8HgAZr9erVOnTokPLz8xUcHOzqcgAAldCnpa8+P5Kjnrdd6+pScAWEDgANVn5+folXAEDdc5e/t+7y93Z1GSgD56EAAAAAGEXoAAAAAGAUoQMAAACAUYQOAABc4Ly92NUl1IoaADQM3EgOAIALeHq4adi0tZVqe+JEriTp+IncSm9DktYtGl7ptgBQEZzpqCCbm0eJVwAAAABXRuioIJ8bOsrDp5l8bujo6lIAl+JhTAAAoLy4vKqCvK69SV7X3uTqMgCX42FMAACgvAgdqHFcolY/8DAmAABQXlwXgRrHJWoAAAANC2c6UOO4RA0AAO6NQ8PCbzkAAIAL9Gnpq//yvUp9Wvq6uhTAOM50AAAAuAD3xqEh4UwHAAAAAKPKDB2WZZWal5OTY6QYAAAAAPVPmaEjMjKy1Lzhw4cbKQYAAABA/XPZezoeffRR7du3T+fOnVPHjv/+alOHw6F27drVSHEAAAAA6r7Lho5ly5bpzJkzmjFjhubPn//vBu7u8vf3r5HiAAAAANR9l728ysfHRzfeeKOWL1+ujz76SC1atJAkvf766zp37lyNFQgAAACgbivzno7p06frzJkzkqRrrrlGNptNzzzzjOm6AAAAANQTZYaOH3/8UU8//bQkqUmTJpoxY4YOHTpkvDAAKMt5e7GrSwAAwJjHH39cp06dUnR0tA4fPuzqcqqkzIcDFhUVKS8vTz4+PpKks2fPXvJrdAGgpnl6uGnYtLWVbn/iRK4k6fiJ3EpvZ90ivs0PAGDGV199JUlatWqViyupujJDx4ABAzR48GCFhobKZrNp69atl/waXQAAAADVY/r06ZIufKPs4cOHtWHDBuXn5ys+Pl7NmzfXkSNHdPXVV2vs2LFas2aNjhw5oj59+mjGjBmSpG3btmnFihWy2+266qqr9PTTT+vuu+922fGUGTqeeOIJtWzZUmlpaXJ3d9fUqVPVs2fPmqgNAAAAaJDmz5+vxMRE/fd//7cGDRrknL9v3z7Nnj1bbdq00ZgxY7Ry5Uq9/fbbysvLU48ePTR69GgVFBQoISFBb7/9tnx9fXXo0CGNGjVKqamp8vb2dsnxlBk6JKljx45yOBxq1KhRiWd2AAAAAKg5N954o9q0aSNJuvnmm9WkSRN5enrKz89PjRs3Vk5Ojnbu3KmsrCw99thjznY2m00//fSTWrdu7ZK6ywwdW7du1YwZM9SqVSsVFxdr5syZWrx4sYKDg2uiPgAAANRSNjePEq8wz9PTs8S0u3vpf847HA7dd999Wrx4sXPeL7/8ooCAANPlXVaZ316VkJCgd955R++8847effddvfHGG1q4cGFN1AYAAIBazOeGjvLwaSafG7gSxgQ3NzcVFRVVuN19992nr776Sj/88IMk6fPPP1f//v1d+qy9Ms90XHXVVWrVqpVzum3btrLZbEaLAgAAQO3nde1N8rr2JleXUW+FhoYqKipKZ8+erVC7li1bat68eYqJiZFlWXJ3d9eKFSvUuHFjQ5WWrczQ0aNHD61cuVIjRoyQm5ubNm3apDvuuEM5OTmyLEtNmzatgTIBAMBFXNICNAzx8fGl5n300UfOn5999tkSy3bs2OH8uW/fvurbt6+54iqozNCxatUqFRcXlzrozZs3y2azaf/+/Zdtm5ycrBUrVqioqEiPPvqohg+/9PfZT5s2TcHBwc6v4k1KStLLL7+s6667TpL029/+VlOmTCn3QQEAUJ/53NBRZ4/vU+Nm7VxdCgCUS5mh49tvv73ssuTk5Msuy8zMVEJCghITE+Xp6amhQ4eqS5cuatmyZYl1Zs+erbS0tBI3pmdkZCguLk79+vUr73EAANBgcEkLgLqmzBvJr+TNN9+87LLt27crODhYTZs2lbe3t0JCQpSSklJineTkZPXq1avUqZ99+/YpKSlJ4eHhmjp1qnJycqpSJgAAAAAXKtdzOi7HsqzLLsvKypK/v79zOiAgQHv37i2xzpgxYyRJu3fvLjHf399fjz/+uDp27Kj4+HjNmzdPL7/8crnrysjIuOyyTp06lXs7Jv3nMdc1taEf6cP6oSrvI314QVl9WNl+qu1jKWNA9ajr/ehqteF9rOp7WBuOoTa4Uj/SR1VXpdBxpW+xcjgcJZZbllXub71atmyZ8+cxY8aod+/eFaorKChIXl5eFWpT0/jlrTr6sH7gfaw6U31Y28dSfneqB/1Y9/EeVg/60awqXV51Jc2aNVN2drZzOjs7u1wPJMnNzdXq1aud05Zlyc3NzUSJAAAAAGqAsdDRtWtXpaWl6dSpUyooKFBqaqp69OhRZjtvb2+9/vrr2rNnjyTpnXfeqfCZDgAAAKCmnLcXu3S7R48eVVBQkCIiIhQREaGQkBBNnz5dJ06c0L59+zRz5kwj9VWEsXs6AgMDNWXKFI0cOVJ2u12DBg1S+/btFR0drcmTJ6tdu0t/zZ+bm5sWL16sOXPm6Ny5c7r11lu1aNGiqpQJAAAAGOPp4aZh09ZW+3bXLbr04yYuJSAgQJs3b5Z04d/o8fHxmjx5statW3fZf3fXpHKHjpycHLm5ucnHx8c5Lzw8/IptwsPDS62zatWqUustWLCgxHTnzp2VlJRU3tIAAAAA/D+bzaYnn3xS999/v95++21t3bpVa9asUVRUlNq1a6fdu3fr1KlTmjVrlnr27Km4uDj5+Pjo22+/VWZmpiZOnKiBAwfq7Nmzmjdvng4dOqTi4mJFR0erX79+SkxMVFJSks6cOaMHHnhAMTExZdZUZuj43//9X8XGxmr//v2y2Wy6++67tWjRIt1www0aPXp0tXQMAAAAgOrj6empW265Rddff32J+Xa7XevXr9e2bdu0ZMkS9ezZU5J0/PhxrVu3Tt9//71GjhypgQMHasWKFWrbtq0WLlyovLw8DR06VL/5zW8kXXje3pYtW+TuXr5zGGWuNX36dA0ePFgDBw6UZVlav369Zs6cqbfeequixw4AAACghthsNl111VUl5nXv3l2SdMcdd+jMmTPO+ffff79sNpvuvPNO5/zt27fr3Llz2rhxoyQpPz9fhw4dkiS1adOm3IFDKkfoKCgo0NChQ53TUVFR2rBhQ7l3AAAAAKBmnT9/XkeOHNHJkydLzL/4Vej/+SiLS813OBz64x//qLZt20qSTpw4oWuvvVbJycmlwkxZyvz2qv/6r//S119/7Zz+/vvvdeONN1ZoJwAAXGRz8yjxCgCoXg6HQ0uXLtVvfvMb3XzzzZXeTnBwsN59911JFx783b9/f/3yyy+V2laZZzqOHTumqKgotWrVSu7u7vruu+/k7+/vvEE8OTm5UjsGADRMPjd01Nnj+9S4meu/TQUA6ousrCxFRERIuhA67rrrLsXHx+vAgQOV3uakSZM0Z84c9evXT8XFxYqNjdXNN9+sXbt2VXhbZYaOqVOnVqpIAAAuxevam+R17U2uLgMAqs15e3GFvt62Itv19Cj7Idk33nijMjIyLrmsS5cu6tKliyRpzZo1Jdps27ZNUulvkj148KAkycfHRy+99FKpbUZGRioyMrJ8B/H/Lhs6fvjhB91+++1q3LjxJZdfvLYLAAAAaMjKEwxq03Zd4bKhY9GiRXrttdc0ePBgNW/evMSDAAsKCpSWllYjBQKAKdxbAABAzbhs6Fi4cKHOnDmj22+/XWvWrJFlWbLZbLLb7RoxYkRN1ggARnBvAQAANeOyoeMPf/iDvvrqK9lsNt13333O+W5ubgoJCamR4gDAJO4tAACgZlw2dLzxxhuSLjwccP78+TVWEAAAAID6pczndBA4AAAAAFRFmaEDAAAAAKqC0AEAAABUgaPI7tLt7tixQ1FRUUZqWLp0qZYuXVrl7ZT5cEAAAAAAl9fI3UO7F42p9u12mvZ6tW/TVTjTAQAAANQz/3n2Iy4uTomJiTp69KgGDBig2NhY9evXT48++qjOnDkjSUpOTlZYWJgefvhhxcXFyW6/cKZl7969Gjp0qB544IFKn/UgdAAAAAANyIEDBzRq1Ch99NFHuuaaa5ScnKzMzEzNnz9fb775pj7++GMVFxfr888/lySdPHlSb7/9tjZu3Kg33nhDeXl5Fd4nl1cBAAAADch1112nNm3aSJLuuOMO5eTk6JtvvlHHjh3VrFkzSdIf//hHSdL+/fvVvXt3eXp6ys/PT76+vsrJyZGPj0+F9knoAAAAAOoZm80my7Kc0xcvlZIkLy+vUuu5u7vLZrM55586dcr5s7u7e6n1K4rLqwAAAIB6xtfXV//85z9VWFioM2fOaPfu3Vdcv127dvqf//kfZWdnS5JefPFF/eUvf6m2ejjTAQAAAFSBo8hu5JumHEV2NXL3KNe6u3bt0t133+2cDg8PV8+ePfXwww+rRYsW6tSp0xXbBwYGaubMmRo9erQcDoc6dOigyMhILV++vErHcBGhAwAAAKiC8gYDU9vt0qWL9u/fX+7tbtu2zfnzk08+6fw5NDRUoaGhJdb99fL/bFsRXF4FAAAAwChCBwAAAACjCB0AAAAAjCJ0AAAAADCK0AEAAADAKEIHAAAAAKMIHQAAAACMInQAAAAAMIrQAQAAAMAoQgcAAAAAowgdAAAAAIwidAAAAAAwitABAAAAwChCBwAAAACjCB0AAAAAjCJ0AAAAADCK0AEAAADAKEIHAAAAAKOMho7k5GSFhYWpT58+Wrt27WXXmzZtmhITE53Tx44d0/DhwxUaGqrx48fr7NmzJssEAAAAYJCx0JGZmamEhAStW7dOmzZt0vr163X48OFS64wbN06ffPJJiflz587VsGHDlJKSoqCgIC1fvtxUmQAAAAAMMxY6tm/fruDgYDVt2lTe3t4KCQlRSkpKiXWSk5PVq1cv9e3b1znPbrdr586dCgkJkSRFRkaWagcAAACg7nA3teGsrCz5+/s7pwMCArR3794S64wZM0aStHv3bue806dPy8fHR+7uF0rz9/dXZmamqTIBAAAAGGYsdDgcDtlsNue0ZVklpi/nUuuVp92vZWRkXHZZp06dKrQtU34dtOqi2tCP9GH9UJX3kT68oKw+rGw/1faxlDGgetT1fnS12vA+VvU9rA3HUBtcqR/po6ozFjqaNWumXbt2Oaezs7MVEBBQZjs/Pz/l5uaquLhYbm5u5W73a0FBQfLy8qpwzTWJX96qow/rB97HqjPVh7V9LOV3p3rQj3Uf72H1oB/NMnZPR9euXZWWlqZTp06poKBAqamp6tGjR5ntPDw81LlzZ23ZskWStGnTpnK1AwAAAFA7GQsdgYGBmjJlikaOHKkBAwaoX79+at++vaKjo7Vv374rtp09e7Y2bNigsLAw7dq1S0899ZSpMgEAAAAYZuzyKkkKDw9XeHh4iXmrVq0qtd6CBQtKTLdo0UJr1qwxWRoAAACAGsITyQEAAAAYRegAAAAAYBShAwAAAIBRhA4AAAAARhE6AAAAABhF6AAAAABgFKEDAAAAgFGEDgAAAABGEToAAAAAGEXoAAAAAGAUoQMAAACAUYQOAAAAAEYROgAAAAAYRegAAAAAYBShAwAAAIBRhA4AAAAARhE6AAAAABhF6AAAAABgFKEDAAAAgFGEDgAAAABGEToAAAAAGEXoAAAAAGAUoQMAAACAUYQOAAAAAEYROgAAAAAYRegAAAAAYBShAwAAAIBRhA4AAAAARhE6AAAAABhF6AAAAABgFKEDAAAAgFGEDgAAAABGEToAAAAAGEXoAAAAAGAUoQMAAACAUYQOAAAAAEYROgAAAAAYRegAAAAAYBShAwAAAIBRhA4AAAAARhkNHcnJyQoLC1OfPn20du3aUsv379+vyMhIhYSEaObMmSoqKpIkJSUlqVu3boqIiFBERIQSEhJMlgkAAADAIHdTG87MzFRCQoISExPl6empoUOHqkuXLmrZsqVzndjYWD3//PPq0KGDZsyYoQ0bNmjYsGHKyMhQXFyc+vXrZ6o8AAAAADXE2JmO7du3Kzg4WE2bNpW3t7dCQkKUkpLiXP7zzz/r3Llz6tChgyQpMjLSuXzfvn1KSkpSeHi4pk6dqpycHFNlAgAAADDMWOjIysqSv7+/czogIECZmZmXXe7v7+9c7u/vrwkTJujDDz9U8+bNNW/ePFNlAgAAADDM2OVVDodDNpvNOW1ZVonpKy1ftmyZc/6YMWPUu3fvCu07IyPjsss6depUoW2Zsnv3bleXUCW1oR/pw/qhKu8jfXhBWX1Y2X6q7WMpY0D1qOv96Gq14X2s6ntYG46hNrhSP9JHVWcsdDRr1ky7du1yTmdnZysgIKDE8uzsbOf0iRMnFBAQoNzcXG3cuFGPPfaYpAthxM3NrUL7DgoKkpeXV9UOwDB+eauOPqwfeB+rzlQf1vaxlN+d6kE/1n28h9WDfjTL2OVVXbt2VVpamk6dOqWCggKlpqaqR48ezuUtWrSQl5eXM1Vu3rxZPXr0kLe3t15//XXt2bNHkvTOO+9U+EwHAAAAgNrD2JmOwMBATZkyRSNHjpTdbtegQYPUvn17RUdHa/LkyWrXrp1eeuklzZo1S3l5eWrbtq1GjhwpNzc3LV68WHPmzNG5c+d06623atGiRabKBAAAAGCYsdAhSeHh4QoPDy8xb9WqVc6fW7durQ8++KBUu86dOyspKclkaQAAAABqCE8kBwAAAGAUoQMAAACAUYQOAAAAAEYROgAAAAAYRegAAAAAYBShAwAAAIBRhA4AAAAARhE6AAAAABhF6AAAAABgFKEDAAAAgFGEDgAAAABGEToAAAAAGEXoAAAAAGAUoQMAAACAUYQOAAAAAEYROgAAAAAYRegAAAAAYBShAwAAAIBRhA4AAAAARhE6AAAAABhF6AAAAABgFKEDAAAAgFGEDgAAAABGEToAAAAAGEXoAAAAAGAUoQMAAACAUYQOAAAAAEYROgAAAAAYRegAAAAAYBShAwAAAIBRhA4AAAAARhE6AAAAABhF6AAAAABgFKEDAAAAgFGEDgAAAABGEToAAAAAGEXoAAAAAGAUoQMAAACAUYQOAAAAAEYROgAAAAAYRegAAAAAYJTR0JGcnKywsDD16dNHa9euLbV8//79ioyMVEhIiGbOnKmioiJJ0rFjxzR8+HCFhoZq/PjxOnv2rMkyAQAAABhkLHRkZmYqISFB69at06ZNm7R+/XodPny4xDqxsbF69tln9cknn8iyLG3YsEGSNHfuXA0bNkwpKSkKCgrS8uXLTZUJAAAAwDB3Uxvevn27goOD1bRpU0lSSEiIUlJSNGnSJEnSzz//rHPnzqlDhw6SpMjISP3pT3/S4MGDtXPnTi1btsw5f8SIEYqNjS1zn5ZlSZLOnz9/xfWu8fao5FFVj8LCQpfuv7q4sh/pw+pRWFgoXdXEtfuvIvqwfH3o6ekpm81WrnXrwljKGFA96ks/ulwdGAPK4vLPswv70FlDGSoyjqI0m3Xxr0s1e+2115Sfn68pU6ZIkt5//33t3btXzz33nCTpm2++0aJFi/Tuu+9Kkv7xj39o7NixWrNmjQYNGqS//e1vkqSioiJ16NBBGRkZZe4zNzdX33//vYnDAYA6LSgoSF5eXuVal7EUAEqryDiK0oyd6XA4HCXSoGVZJaYvt/w/15NU7lTZuHFj3XnnnfLw8CCJAsCveHp6lntdxlIAKK0i4yhKMxY6mjVrpl27djmns7OzFRAQUGJ5dna2c/rEiRMKCAiQn5+fcnNzVVxcLDc3t1LtrqRRo0Zq0sS1p+cAoK5jLAUAVDdjN5J37dpVaWlpOnXqlAoKCpSamqoePXo4l7do0UJeXl7avXu3JGnz5s3q0aOHPDw81LlzZ23ZskWStGnTphLtAAAAANQtxu7pkC58Ze5rr70mu92uQYMGKTo6WtHR0Zo8ebLatWunAwcOaNasWcrLy1Pbtm01f/58eXp66ueff1ZcXJxOnjyp5s2bKz4+Xtdee62pMgEAAAAYZDR0AAAAAABPJAcAAABgFKEDAAAAgFGEDgAAAABGEToAAAAAGGXsOR0NWUpKilauXKmioiJZlqWIiAiNGTPG1WXVORXtxw0bNsjb21v9+vWrwSprn7lz5+rrr7+W3W7XTz/9pNtvv12S9K9//UuRkZF68sknXVxh3XT06FGFhoY6+/OiV199Vc2bN3dOR0dH6/nnn1dgYGBNl1ivMI5WH8bSimMcNYextOEidFSzzMxMLVy4UImJifL19dXZs2cVFRWl2267Tb169XJ1eXVGZfrx66+/1r333lvDldY+s2fPlnRhYB85cqQ2b94sSVq6dKkry6oXAgICnP15OatWraqhauovxtHqw1haOYyjZjGWNkxcXlXNTp8+LbvdrnPnzkmSGjdurAULFqhly5Z68MEHdfToUUnSjh07FBUVJUmKiorSokWL9Lvf/U69e/fW559/7rL6a4sr9eOf//xnDRkyRP3791doaKi+/vprbd++Xdu2bdOf/vQnffHFFy6uvvbau3evhg4dqgceeMD5xzMxMVFxcXHOdaKiorRjxw7t2LFDgwYNUmRkpJ5++mlXlVzrxcXFady4cerbt6+2bdtW4nOOymEcrT6MpdWPcdQMxtL6jzMd1ax169bq1auXHnroId11113q0qWLwsPDdcstt1yxnd1u1/r167Vt2zYtWbJEPXv2rKGKa6fL9eNNN92kZ599Vq+++qr8/Pz0wQcfaOXKlXr11Vf14IMP6t5771X37t1dXX6tdfLkSb333nvKy8vTgw8+qFGjRl1x/R9//FF//etf1aRJkxqqsHbLyspSRESEczo8PFyS1LRpU7366quSpOeff94ltdUnjKPVh7G0+jGOVh1jacNE6DBg7ty5mjBhgr788kt9+eWXGjJkiF566aUrtrk4uN9xxx06c+ZMDVRZ+12uH5ctW6Zt27bpyJEj+vvf/65GjThhV17du3eXp6en/Pz85Ovrq5ycnCuuf9ttt/GH8lcudUlAXFyc2rdv76KK6i/G0erDWFq9GEerjrG0YSJ0VLPPPvtM+fn5CgsL08CBAzVw4EBt2LBBH3zwgSTp4gPgi4qKSrTz8vKSJNlstpotuJa6XD+uXbtW8fHx6t+/v+655x61atVKa9eudXW5dYa7+78/8jabTZZlOV8vstvtzp+vuuqqGq2vrqKfqhfjaPVhLK1+jKPm0Ff1G/+tUc2uuuoqvfzyy87rEC3L0v79+3XXXXfJ19dXhw8fliT95S9/cWWZtd7l+tHT01M2m03jxo1Tly5dtHXrVhUXF0uS3NzcnD+j/Hx9ffXDDz/Isiz985//1MGDB11dEho4xtHqw1haMxhHgbJxpqOaBQcHa9KkSRo3bpzzfzq6d++uiRMnqmPHjnruuef0yiuvqFu3bi6utHa7XD8uW7ZMcXFx6tu3r2w2m7p166bdu3dLkrp27ar4+Hg1adJEoaGhriy/Tunatas2btyo0NBQ3XbbberUqZOrS0IDxzhafRhLawbjKFA2m/Xr84EAAAAAUM24vAoAAACAUYQOAAAAAEYROgAAAAAYRegAAAAAYBShAwAAAIBRhA6gGqSkpCgqKsrVZQBAncU4CtRvhA4AAAAARhE6gEpasmSJHnroIQ0aNEhbt26VJB05ckSjRo3SkCFD9MADD2j8+PEqLCzUhx9+qKFDhzrbHjt2TN26ddP58+ddVT4AuBzjKNBwEDqASvj000+VmpqqTZs26b333lNeXp4kacOGDRowYIA2bNig1NRUHT16VJ999plCQ0P1008/6dChQ5Kk999/X4888og8PT1deRgA4DKMo0DDQugAKiEtLU29e/eWj4+P3N3dNXDgQElSbGys/Pz8tGrVKs2ZM0dZWVnKz8+Xp6enBg8erPfff1/FxcVKSkrSkCFDXHwUAOA6jKNAw+Lu6gKAusqyLOfPbm5ukqSYmBgVFxerb9+++u1vf6tffvnFud7QoUM1aNAg3Xvvvbrjjjt00003uaRuAKgtGEeBhoMzHUAl9OjRQykpKfrXv/4lh8OhzZs3S5K+/PJLTZw4UWFhYZKkPXv2qLi4WJLUvHlzdejQQS+++KJ+//vfu6x2AKgNGEeBhoUzHUAl9OzZUwcPHtTAgQN1zTXXqHXr1jp9+rSmTJmiiRMnytvbWz4+Prrnnnv0008/OdtFRkbqueeeU8+ePV1YPQC4HuMo0LDYrF+f2wRgjMPh0Lx583TDDTdo7Nixri4HAOocxlGg7uLyKqAG5OXlqUuXLvrll180cuRIV5cDAHUO4yhQt3GmAwAAAIBRnOkAAAAAYBShAwAAAIBRhA4AAAAARhE6AAAAABhF6AAAAABgFKEDAAAAgFH/BwHbENxQgKtLAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 792.225x360 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.factorplot(x='day', y='tip_pct', hue='time', col='smoker',\n",
    "               kind='bar', data=tips[tips.tip_pct < 1])#用于绘制两维变量的关系图，也就是共用x坐标，按照hue分组，画出不同hue种类的y 的值\n",
    "#参数kind：point默认，bar柱形图，count频次，box箱体，violin提琴，strip散点，swarm分散点"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 112,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\ProgramData\\Anaconda3\\lib\\site-packages\\seaborn\\categorical.py:3704: UserWarning: The `factorplot` function has been renamed to `catplot`. The original name will be removed in a future release. Please update your code. Note that the default `kind` in `factorplot` (`'point'`) has changed `'strip'` in `catplot`.\n",
      "  warnings.warn(msg)\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<seaborn.axisgrid.FacetGrid at 0x246634b1190>"
      ]
     },
     "execution_count": 112,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x720 with 4 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.factorplot(x='day', y='tip_pct', row='time',\n",
    "               col='smoker',\n",
    "               kind='bar', data=tips[tips.tip_pct < 1])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 113,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\ProgramData\\Anaconda3\\lib\\site-packages\\seaborn\\categorical.py:3704: UserWarning: The `factorplot` function has been renamed to `catplot`. The original name will be removed in a future release. Please update your code. Note that the default `kind` in `factorplot` (`'point'`) has changed `'strip'` in `catplot`.\n",
      "  warnings.warn(msg)\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<seaborn.axisgrid.FacetGrid at 0x246635706d0>"
      ]
     },
     "execution_count": 113,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 360x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.factorplot(x='tip_pct', y='day', kind='box',\n",
    "               data=tips[tips.tip_pct < 0.5])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Other Python Visualization Tools"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 114,
   "metadata": {},
   "outputs": [],
   "source": [
    "pd.options.display.max_rows = PREVIOUS_MAX_ROWS"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Conclusion"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.8.5"
  },
  "toc": {
   "base_numbering": 1,
   "nav_menu": {},
   "number_sections": true,
   "sideBar": true,
   "skip_h1_title": false,
   "title_cell": "Table of Contents",
   "title_sidebar": "Contents",
   "toc_cell": false,
   "toc_position": {},
   "toc_section_display": true,
   "toc_window_display": false
  }
 },
 "nbformat": 4,
 "nbformat_minor": 1
}