Visualization.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import os"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'C:\\\\Users\\\\Ravishankar.kumar\\\\Desktop\\\\Python Programming Course'"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "os.getcwd()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "movies = pd.read_csv('P4-Movie-Ratings.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "559"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(movies)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "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>Film</th>\n",
       "      <th>Genre</th>\n",
       "      <th>Rotten Tomatoes Ratings %</th>\n",
       "      <th>Audience Ratings %</th>\n",
       "      <th>Budget (million $)</th>\n",
       "      <th>Year of release</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>(500) Days of Summer</td>\n",
       "      <td>Comedy</td>\n",
       "      <td>87</td>\n",
       "      <td>81</td>\n",
       "      <td>8</td>\n",
       "      <td>2009</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>10,000 B.C.</td>\n",
       "      <td>Adventure</td>\n",
       "      <td>9</td>\n",
       "      <td>44</td>\n",
       "      <td>105</td>\n",
       "      <td>2008</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>12 Rounds</td>\n",
       "      <td>Action</td>\n",
       "      <td>30</td>\n",
       "      <td>52</td>\n",
       "      <td>20</td>\n",
       "      <td>2009</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>127 Hours</td>\n",
       "      <td>Adventure</td>\n",
       "      <td>93</td>\n",
       "      <td>84</td>\n",
       "      <td>18</td>\n",
       "      <td>2010</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>17 Again</td>\n",
       "      <td>Comedy</td>\n",
       "      <td>55</td>\n",
       "      <td>70</td>\n",
       "      <td>20</td>\n",
       "      <td>2009</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                    Film      Genre  Rotten Tomatoes Ratings %  \\\n",
       "0  (500) Days of Summer      Comedy                         87   \n",
       "1            10,000 B.C.  Adventure                          9   \n",
       "2             12 Rounds      Action                         30   \n",
       "3              127 Hours  Adventure                         93   \n",
       "4              17 Again      Comedy                         55   \n",
       "\n",
       "   Audience Ratings %  Budget (million $)  Year of release  \n",
       "0                  81                   8             2009  \n",
       "1                  44                 105             2008  \n",
       "2                  52                  20             2009  \n",
       "3                  84                  18             2010  \n",
       "4                  70                  20             2009  "
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "movies.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0      (500) Days of Summer \n",
       "1                10,000 B.C.\n",
       "2                 12 Rounds \n",
       "3                  127 Hours\n",
       "4                  17 Again \n",
       "               ...          \n",
       "554            Your Highness\n",
       "555          Youth in Revolt\n",
       "556                   Zodiac\n",
       "557              Zombieland \n",
       "558                Zookeeper\n",
       "Name: Film, Length: 559, dtype: category\n",
       "Categories (559, object): [(500) Days of Summer, 10,000 B.C., 12 Rounds, 127 Hours, ..., Youth in Revolt, Zodiac, Zombieland, Zookeeper]"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "movies.Film.astype('category')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "from matplotlib import pyplot as plt\n",
    "import seaborn as sns\n",
    "%matplotlib inline\n",
    "import warnings\n",
    "warnings.filterwarnings('ignore')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['Film', 'Genre', 'Rotten Tomatoes Ratings %', 'Audience Ratings %',\n",
       "       'Budget (million $)', 'Year of release'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "movies.columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "movies.columns = ['Film','Genre','CriticRatings','AudienceRatings','BudgetMillions','YearOfRelease']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['Film', 'Genre', 'CriticRatings', 'AudienceRatings', 'BudgetMillions',\n",
       "       'YearOfRelease'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "movies.columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x432 with 3 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "j = sns.jointplot(data = movies, x = 'CriticRatings', y = 'AudienceRatings', kind='hex')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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0XTwrD59fuWtDpdtRzBCsAJiY88aBRk509Nqwj2NoYkYSC4oyue+Ng5xo73E7jhmEFQATc57ZXkNaYhwfmGWnFY+lS2ZPpKPXz922FxC2rACYmNLjC7BuVy2Xz80nKd6af8ZSfkYSH5pfwO/fOEhTh+0FhCMrACambCxvoLmzl6sWWPPPePinFTNo6/bxu40H3Y5iBmAFwMSUZ7YfJT0pjgtn2Tnq42HOpAxWzpvEPRsrae60q4PDjRUAEzO6fX5e2H2MK+ZNIjHOmn/Gyz+tmEFrl4/f215A2LECYGLGa+810Nrl4yo7+2dczZucyeVz87l7Q4WNFxBmQroS2JhocMfL5STHe6k63skDmw67HSemfOXSmXx4dy33vXGQmy+d6XYc47A9ABMTunr97D7awrzJGXg9NvTEeFtQlMmKORO5a0Mlbd0+t+MYhxUAExNe2VdHjy/AgqJMt6PErK+smElTRy/3vXnQ7SjGYQXAxIRnnL5/puWmuR0lZi0qzuLi2Xn89rUK2m0vICxYATBRr6PHx/o9dcyfnGnNPy77yoqZnOjo5d43D7odxWAFwMSAl/fW09nrt+afMHDmlAlcPDuP37xWYaOGhQErACbqPbO9hty0REpzU92OYoCvXz6bpo5efrfhoNtRYp4VABPV2rp9vLS3jg8tmIRHrPknHCwoyuSKefnc9XqF9RHkMrsOwES19Xtq6fYFWLVwMuV1bW7HiTmDXW8xOz+DF3bV8tUHt3LFvEkDzvOJc6aMZTSD7QGYKPfM9qPkZySybOoEt6OYPiZlBscLePNAo10X4CIrACZqtXT18uq+ej60oACPnf0TdlbMyafXH+C19+rdjhKzrACYqPXi7lp6/AEb+D1M5aUnsmRKcOxg6ynUHVYATNR6ZvtRJmcmsaQ4y+0oZhCXzsknoMor++rcjhKTrACYqNTc0cvr++u5aqE1/4Sz7NQElk3NpuzgCU7YGUHjzgqAiUrrdh+j16/W/BMBLp6dBwIv77W9gPFmp4GaiBJqN873bKxkQko8O6ub2VXTMsapzEhkpSRwdmk2myoa+cCsPHLSEt2OFDNsD8BEnY5uHwfq21hQmIXYxV8R4eJZeXg9wnrbCxhXVgBM1NlV00JAYaH1/RMx0pPiWT4th21Hmqht6XI7TsywAmCizvbqJnJSEyjITHI7ijkFF83MIz7Ow/o9tW5HiRlWAExUaev2UVHfzoKiTGv+iTCpiXGcPz2XnTUt1DR1uh0nJlgBMFFlZ3UzCiwotOafSHTBjFyS4j28aHsB48IKgIkqO6qbyUtLZFKGNf9EouQELxfOzGPvsVa2HD7hdpyoZwXARI2Wrl4ONljzT6Q7b1oOKQlefvzn99yOEvWsAJioYc0/0SEx3stFM/N4fX8D2440uR0nqlkBMFFjR3Uz+RmJ5FvzT8Q7pzSbjKQ47nyl3O0oUc0KgIkKzZ29HGrssK3/KJEY7+XG80pYt6uW8rpWt+NELSsAJirsqG4GYGGh9fwZLT59XglJ8R5+9UqF21GilhUAExV2VDVRkJlEbrr1IxMtctISWXPWFJ7aWk21XRcwJkIqACKyUkT2iUi5iNwywOOJIvKQ8/gmESlxpueIyMsi0iYiv+y3zFIR2eEs83Ox0zbMaTrR0cORE53W/BOFPn/RNBS4942DbkeJSsMWABHxAncAVwJzgetFZG6/2T4LnFDVGcBPgNud6V3AbcA3Blj1r4CbgJnOz8rTeQLG7Khymn+KrPkn2hRmJXPl/En88e3DtNvYwaMulD2As4FyVa1Q1R7gQWB1v3lWA/c6tx8FVoiIqGq7qm4gWAjeJyIFQIaqvqmqCtwHXDOSJ2Ji147qZgqzkslOTXA7ihkDn7mglNYuH49urnI7StQJpQAUAkf63K9ypg04j6r6gGYgZ5h19n03B1onACJyk4iUiUhZfb0NHm3+WmNbN9VN1vwTzc6cMoHFxVncs7GSQEDdjhNVQikAA7XN938XQpnntOZX1d+o6jJVXZaXlzfEKk0s2n7y7B/r+jmqffaCUg42dvCSjRcwqkIZEawKKO5zvwioGWSeKhGJAzKB48Oss2iYdRozrO1VTUzNTiErxZp/ok3f0d/8ASUzOZ7/eG4Pda3dwy77iXOmjGW0qBHKHsA7wEwRKRWRBGANsLbfPGuBG53b1wIvOW37A1LVo0CriCx3zv65AXjqlNObmHaspYvalm7b+o8BXo9wdmk2B+rbaQihAJjQDFsAnDb9m4F1wB7gYVXdJSLfF5GrndnuBnJEpBz4F+D9U0VF5CDwY+DTIlLV5wyiLwF3AeXAAeC50XlKJlZsr2pCgPnW/h8Tlk6dgEfg7YNDNS6YUxHSoPCq+izwbL9p3+lzuwu4bpBlSwaZXgbMDzWoMX2pKturmpmel0Z6Urzbccw4yEiK54yCDN49fILL5+YT77XrWEfKXkETkaqbOjne3mPNPzHmnNIcOnr87KppdjtKVLACYCLS9qpmvCLMm2wFIJZMy0slJzWBTZXWDDQarACYiBNQZXtVEzPz00hO8Lodx4wjjwQPBh9q7KC2pWv4BcyQrACYiHOosYOWLh+LrOuHmLRkSvBg8Ls2ZOSIWQEwEWd7VRPxXmFOQbrbUYwL0hLjmJ2fztbDTfjtyuARsQJgIoo/oOyobmbOpAwS46z5J1YtnTqB1m4f+2ttsJiRsAJgIkpFfRsdPX4W2dk/MW32pAxSE7xstmagEbECYCLKtqpmEuM8zMy35p9Y5vUIi4uz2Hu01bqJHgErACZidPUGz/+eNznDLgIynDl1An5VtlU1uR0lYtmnyESMP++updsXYMmUCW5HMWGgIDOZgswkth2xAnC6rACYiPH4u1VkJsdTmpvqdhQTJhYWZXHkRPCqcHPqrACYiFDf2s1r+xtYVJSFx4aPNo6TXYFst2ag02IFwESEp7fV4A8oS6bYxV/mLyakJDA1O8WOA5wmKwAmIjyxpZp5kzPIz0hyO4oJMwuLs6ht6eaYdQ1xyqwAmLBXXtfKjupmPrJkwGGjTYxbUJiJR2C7HQw+ZVYATNh7/N1qPAJXL57sdhQThtIS45iel8a2qiaGGIjQDMAKgAlrgYDy1NYaLpyZx8R0a/4xA1tUlMWJjl6OnOh0O0pEsQJgwtqmyuNUN3Xy0TOt+ccMbu7kDOI8YgeDT5EVABPWnthSRWqClw/OneR2FBPGkuK9zJ6Uzs6qZgLWDBQyKwAmbHX1+nl2xzFWzi+wgV/MsBYWZdHa7aOivt3tKBHDCoAJWy/srqWt28ffWfOPCcGcSekkxnnsorBTYAXAhK3HNldRkJnE8mk5bkcxESDe62FuQQY7a5rp9vndjhMRrACYsFTd1Mlr++u5bmkRHo91/WBCs6g4i67eAK/uq3c7SkSwAmDC0iNlRwC4blmxy0lMJJmel0ZKgpdndxx1O0pEsAJgwo4/oDxSVsUFM3Ipzk5xO46JIF6PMG9yBn/eXUtXrzUDDccKgAk7G8sbqG7q5ONn2da/OXULCrNo7/HzijUDDcsKgAk7D71zhAkp8Vw+N9/tKCYCleamkp2awJ+sGWhYVgBMWGls6+aF3cf4yJIiEuPs3H9z6rweYeX8SazfU0tnjzUDDcUKgAkrT2ypptev1vxjRmTVwgI6evy8vK/O7ShhzQqACRuqyoPvHGHJlCxmT0p3O46JYOeU5pCblsCftlsz0FCsAJiw8e7hE5TXtbHGtv7NCHk9wpXzC1i/t5b2bp/bccKWFQATNh565wipCV5WLbR+/83IXbWwgK7eAC/ttWagwVgBMGGhtauXp7cdZdXCyaQmxrkdx0SBs0qymZieaM1AQ7ACYMLC2m01dPb6+Zg1/5hR4vUIH1pQwMv76mizZqABWQEwrlNV7nvjEHMLMjhzSpbbcUwUuWphAd2+AOv31LodJSzZvrYZVw9sOvw30yrq29hX28pHlxTyx7ePuJDKRKulUyYwKSOJZ7YfZfVi61a8P9sDMK57s6KR5Hgvi4pt69+MLo/TDPTqvnpau3rdjhN2QioAIrJSRPaJSLmI3DLA44ki8pDz+CYRKenz2K3O9H0ickWf6QdFZIeIbBWRstF4MibyNHX0sLumhbNKJhDvte0RM/quWlhAjz/An3dbM1B/w37iRMQL3AFcCcwFrheRuf1m+yxwQlVnAD8BbneWnQusAeYBK4E7nfWddImqLlbVZSN+JiYibao8DgQv3DFmLCwpzmJyZpKdDTSAUDa5zgbKVbVCVXuAB4HV/eZZDdzr3H4UWCEi4kx/UFW7VbUSKHfWZwy9/gDvHDzOnIIMJqQmuB3HRCmPR7hqYQGv7a+nudOagfoKpQAUAn2PzFU50wacR1V9QDOQM8yyCrwgIptF5KbB/riI3CQiZSJSVl9v3btGkx1VzXT0+DnXhnw0Y+yqhZPp9Ssv7DrmdpSwEkoBGGg8Pg1xnqGWPV9VzyTYtPRlEblooD+uqr9R1WWquiwvLy+EuCYSqCpvVjSSl57I9LxUt+OYKLeoKJPCrGTrIrqfUApAFdD36pwioGaweUQkDsgEjg+1rKqe/F0HPIE1DcWUIyc6qW7q5NxpOQRbC40ZOyLCqoUFbNjfQFNHj9txwkYoBeAdYKaIlIpIAsGDumv7zbMWuNG5fS3wkqqqM32Nc5ZQKTATeFtEUkUkHUBEUoEPAjtH/nRMpHjzQAOJcR6W2IVfZpysWjgZX0BZZ81A7xu2ADht+jcD64A9wMOquktEvi8iVzuz3Q3kiEg58C/ALc6yu4CHgd3A88CXVdUP5AMbRGQb8DbwJ1V9fnSfmglXLV297Kxu4cypE2zQFzNu5hdmUJKTwlNb+zdgxK6QrgRW1WeBZ/tN+06f213AdYMs+wPgB/2mVQCLTjWsiQ5vHmgkoGoHf824EhGuWVLIz9bv52hzJwWZyW5Hcp1deWPGVXevn02VjcydnEFuWqLbcUyMuWZxIarYXoDDCoAZV+8cOkFXb4CLZtoZXWb8leSmsmRKFk9uqXY7SliwAmDGTa8/wMbyBkpyUinOTnE7jolRH11SyN5jreyuaXE7iuusAJhx88z2Gpo7e7loVq7bUUwMu2rhZOI8wpNbbS/ACoAZF4GAcufLB5iYnsisfBvw3bgnOzWBi2fn8eSWanz+gNtxXGUFwIyL53cdY39dG5fMmYjHLvwyLrt2aTF1rd28+l5sdy9jBcCMuUBA+fn6/UzLS2VBYabbcYxhxRkTyU1L4KF3YnsAIisAZsy9uKeWvcdaufmSGbb1b8JCvNfD351ZxPq9ddS1drkdxzVWAMyYUlV+/tJ+puakcPWiyW7HMeZ9HzurGH9Aefzd2D0YbGMCmzG1btcxdla38J/XLiTORvwy42SgsacHMjUnhbteryA9Me6vOiX8xDlTxipaWLFPpBkzPn+A/1q3jxkT0/joEhuQ24Sfs6Zm09DWQ2Vju9tRXGEFwIyZx9+t5kB9O9/44Gzb+jdhaX5hJsnxXt460Oh2FFfYp9KMia5ePz958T0WFWdxxbx8t+MYM6CEOA9nlWSz+2hLTI4TYAXAjInfv3GQo81dfPOK2Tbgiwlry6dlowqbKo+7HWXcWQEwo66utYtfrN/PijkTOX+GdftgwltWSgJzJ2fwduVxemPsymArAGbU/efz++jxB/i/q+a6HcWYkJw3PZfOXj/bjjS5HWVcWQEwo2rrkSYe3VzFZ84vpTTXBns3kaEkJ4WCzCRe399AQNXtOOPGCoAZNf6A8q9P7SQ3LZGbL53hdhxjQiYifGBWHvVt3eysbnY7zrixAmBGzT0bK9lW1cxtq84gPSne7TjGnJL5hZnkpSfy8r46AoHY2AuwAmBGxeHGDn70wj5WzJloXT6YiOQR4ZLZedS2dPPC7lq344wLKwBmxFSVWx7fTpzHw79/ZL6d9mki1oLCLHJSE/jFS/vRGDgWYAXAjNg9Gw/yxoFGbrlyDgWZyW7HMea0eT3CJbMnsqumhae3H3U7zpizAmBGZGd1Mz98bi+XnTGRT8ZIB1omui2eksW8yRn88Nk9dPX63Y4zpqwAmNPW3u3jn/64hezUBP7z2kXW9GOigkeE21bNpaa5i9++VuF2nDFlBcCcFlXlW6gduLUAAA6CSURBVI9t51BjOz9ds5js1AS3IxkzapZPy+HK+ZO485UD1LZE74AxVgDMafnpi/t5ZvtRvrlyDsun5bgdx5hRd+uVZ+BX5TtP7YzaA8JWAMwpW7uthp+t3891S4v4wkXT3I5jzJiYkpPC1y+fxbpdtTyxJTpHDbMRwcwpeWVfHV97aCslOSksKMrkj2/H9qDaJrp97sJpvLinln9du4vl03KYnBVdZ7nZHoAJ2ev767np/s3kpyfyqeVTifPYv4+Jbl6P8KPrFuEPKN94ZBu+KOst1D7BJiQv76vj8/eVMS03lc+cX0pKgu08mtgwNSeV7109jzcONPL9Z3a7HWdUWQEww/rftw7xuXvLmJabxh8+dw4pifblb2LLdcuKuemiadz35iHufeOg23FGjX2SzaB6fAH+47k93LPxIJfMzuMXnziTNPvyNzHqWyvnUFHfzvee3sWE1ISo6PPK9gDMgA7Ut/HRX23kno0H+fR5Jfz2hmX25W9imtcj/GzNYpaVZPPVB7fwh02H3I40YvaJNn+l2+fnrtcr+eVL5STGe/jN3y/lg/MmuR3LmLCQmhjHfZ85m3/8w7t8+4md1DZ38dXLZuH1ROZV8FYADBAczOW5nUf50bp9HGzs4Ip5+Xzv6vlMykxyO5oxYSUp3sv//P1Sbn18Bz9/qZw3Kxr5yccXUzQhxe1op8wKgEse2HR4RMt/YpQ6Xmvt6uXpbUf57esVVDa0M2NiGvd95mwumpU3Kus3JhrFez386LpFnD8jh9ue3MXKn77OFy6axmcuKCU1gppKIydphOnxBaht6aKmqZPj7T209/jp6PHR3h38vbO6hXivEOcR4rwe4jxCamIc6UlxpCXGkZYUN2bn2Td39LKhvIEXdh9j3a5jdPUGmF+YwZ2fPJMr5k2K2N1ZY8bbR5YUsXRKNv/+p93895/f4943D3HDuVO5dmlRRFw0JqH0cSEiK4GfAV7gLlX9Yb/HE4H7gKVAI/BxVT3oPHYr8FnAD3xFVdeFss6BLFu2TMvKykJ+cmNFVTnR0UtNUyfVTZ3UNHVytLnr/ds1TZ3UtXYz2EsrAigM98qnJHjJSIonMzmejOQ4MpLjyUyKJyM5nuvPnkJGcrBYpCbE4en3pa2qtPf4qW/t5sjxDg4d72B3TTM7qpvZVd2CAsnxXhYWZXLmlAkUTUi23jyNcZzOHvbmQyf46Yvv8fr+BkRgeWkOH5idxwUzcpk9KZ14r3vn3IjIZlVd9jfThysAIuIF3gMuB6qAd4DrVXV3n3n+EVioql8UkTXAR1T14yIyF/gjcDYwGXgRmOUsNuQ6BzKSAhAIKH5V/AHFFwj+Dt4O0OML0N7tp63bR7vz09bto6PHT0tnL/Vt3dS3dtPg/D7W0kVX719fEZgY52FyVjKTs5KYnJnM5KxkCrOCv3PSEkhLjCMlwUtqYhyJcR4e2HQYvyo+fzBPry9Ae4+P1i4fbV0+Wrt7aeny0dLZS0tXL82dwVyDSUnwkpLgJaDg8wfo6PHj6zeuaWZyPPMLM0jwepmVn0bRhBTb2jdmACNpYj3c2MEjm4/w59217D3WCkCC18PM/DRKclPJT08iPyORiRmJTExPIj0pjuR4L0nv/3iI83jweMArgtcjI944G6wAhNIEdDZQrqoVzooeBFYDfb+sVwPfdW4/CvxSgolXAw+qajdQKSLlzvoIYZ2j5vIfv8r+urbTXj4zOZ689ETy0hJZUJTFZemJzpf9yS/5JLJTE07pTRIR4kSIO7lRkAgThulS2ecP0Nrlo7mzlwVFmbR2/aVYtXf76Oj1v/8Pk5LgJTM5nuzUBIqzU5iSnUJBZhIiMuLjD8aYwU3JSeHrH5zN1z84m9qWLt6qaGR3TQu7j7awp6aFl1vq6Og59YFm9v7bSpLivaOaNZQCUAj07fGrCjhnsHlU1ScizUCOM/2tfssWOreHWycAInITcJNzt01E9jm3c4GGEPKHq0jPD5H/HCy/u8I2/ydDn3XcnkPy7SNafOpAE0MpAANt1vZvNxpsnsGmD9QYNmBblKr+BvjN34QSKRtolyZSRHp+iPznYPndFen5IfKfQyhHJaqA4j73i4CaweYRkTggEzg+xLKhrNMYY8wYCqUAvAPMFJFSEUkA1gBr+82zFrjRuX0t8JIGjy6vBdaISKKIlAIzgbdDXKcxxpgxNGwTkNOmfzOwjuApm79T1V0i8n2gTFXXAncD9zsHeY8T/ELHme9hggd3fcCXVdUPMNA6TzH73zQLRZhIzw+R/xwsv7siPT9E+HMI6ToAY4wx0cd6AzXGmBhlBcAYY2JUxBUAEfkvEdkrIttF5AkRyerz2K0iUi4i+0TkCjdzDkVEVjoZy0XkFrfzDEdEikXkZRHZIyK7ROSrzvRsEfmziOx3fk9wO+tQRMQrIltE5BnnfqmIbHLyP+SckBCWRCRLRB51/vf3iMi5Efj6f835/9kpIn8UkaRwfg9E5HciUiciO/tMG/A1l6CfO5/p7SJypnvJQxdxBQD4MzBfVRcS7E7iVgCn24k1wDxgJXCn041FWHEy3QFcCcwFrneyhzMf8HVVPQNYDnzZyXwLsF5VZwLrnfvh7KvAnj73bwd+4uQ/QbDPqnD1M+B5VZ0DLCL4PCLm9ReRQuArwDJVnU/w5I81hPd78HuC3yV9DfaaX0nwLMeZBC9c/dU4ZRyRiCsAqvqCqp7sFOctgtcQQJ9uJ1S1Eujb7UQ4eb9rDVXtAU52gxG2VPWoqr7r3G4l+OVTSDD3vc5s9wLXuJNweCJSBFwF3OXcF+BSgl2XQBjnF5EM4CKCZ9uhqj2q2kQEvf6OOCDZuVYoBThKGL8HqvoawbMa+xrsNV8N3KdBbwFZIlIwPklPX8QVgH4+Azzn3B6oy4rCv1nCfZGSc0AiUgIsATYB+ap6FIJFApjoXrJh/RT4JnCyF78coKnPxkQ4vw/TgHrgHqcJ6y4RSSWCXn9VrQZ+BBwm+MXfDGwmct6DkwZ7zSPycx2WBUBEXnTaCfv/rO4zz7cJNk384eSkAVYVjue4RkrOvyEiacBjwD+raovbeUIlIquAOlXd3HfyALOG6/sQB5wJ/EpVlwDthHFzz0CctvLVQCnBnoFTCTab9Beu78FwIun/6X1hOSCMql421OMiciOwClihf7mQIVK6l4iUnH9FROIJfvn/QVUfdybXikiBqh51dnfr3Es4pPOBq0XkQ0ASkEFwjyBLROKcLdBwfh+qgCpV3eTcf5RgAYiU1x/gMqBSVesBRORx4Dwi5z04abDXPCI/12G5BzAUCQ4k8y3galXt6PPQYN1OhJuI6wbDaS+/G9ijqj/u81DfLkBuBJ4a72yhUNVbVbVIVUsIvt4vqeongZcJdl0C4Z3/GHBERGY7k1YQvLo+Il5/x2FguYikOP9PJ59DRLwHfQz2mq8FbnDOBloONJ9sKgprqhpRPwQP7h4Btjo/v+7z2LeBA8A+4Eq3sw7xHD5E8AymA8C33c4TQt4LCO7Obu/zun+IYDv6emC/8zvb7awhPJeLgWec29MIbiSUA48AiW7nGyL3YqDMeQ+eBCZE2usPfA/YC+wE7gcSw/k9IDiY1VGgl+AW/mcHe80JNgHd4XymdxA828n15zDcj3UFYYwxMSrimoCMMcaMDisAxhgTo6wAGGNMjLICYIwxMcoKgDHGxCgrACYiiMhHRERFZM4pLndxn94/rx6v3ldF5NMiUi8iW50ePL8WwjIXi8h5fe5/UURuGNukJpZZATCR4npgA85wo6dDVdeq6g9HL9KwHlLVxQSvRP62iBQPM//FBK+OBUBVf62q941hPhPjrACYsOf0QXQ+wQtx1jjT3t+yd+7/UkQ+7dxe6Wx1bwA+2meeT4vIL53beSLymIi84/yc70z/rtMP/CsiUiEiX+mz/A1OX+/bROT+odbTl6o2ErzQqcBZ5sNOH/hbnH6v8p1O9r4IfM3Za7jQyfINZ5lXROR2EXlbRN4TkQud6Ski8rCT6yFnvcskOPbB750+tHaEsgdiYk9Y9gVkTD/XEOwL/z0ROS5DDLYhIknAbwl2M1wOPDTIrD8j2A/9BhGZAqwDznAemwNcAqQD+0TkV8Asglean6+qDSKSHcJ6TmaaQrAPou3OpA3AclVVEfkc8E1V/bqI/BpoU9UfOcut6Jc5TlXPdvo0+leC/ev8I3BCVReKyHyCV2lD8MrhQg32vY/0GTjJmJOsAJhIcD3BztsgOH7C9cCfBpl3DsFOx/YDiMj/Ehygo7/LgLnBbmkAyBCRdOf2n1S1G+gWkTogH6ffelVtAFDV4yGs5+MicgkwG/i8qnY504uAh5zOxBKAyhBeA4CTnfBtBkqc2xcQLEKo6k4ROVlkKoBpIvILgq/VCyH+DRNDrACYsCYiOQS/fOeLiBIcSUoJdr7Vtwkzqc/tUPo38QDnqmpnv78H0N1nkp/g50QGWe9Q63lIVW8WkXOBP4nIcxrs2O0XwI9Vda2IXAx8N4S8fXOdzAQDd0OMqp4QkUXAFcCXgY8RHD/DmPfZMQAT7q4lONLSVFUtUdVi/rLFPNfp/TWTYO+SEOxsrFREpjv3rx9kvS8AN5+8IyKLh8mxHviYU5Do0wQ07HpU9U2CnZ991ZmUCVQ7t2/sM2srwWanU7GB4Jf7yWFRFzi3cwGPqj4G3EZwPAFj/ooVABPurgee6DftMeATwMME29X/AGwBcJpZbiK4xb0BODTIer8CLHMOnu4meAB2UKq6C/gB8KqIbANOdosd6npuB/7BaR76LvCIiLwONPSZ52ngIycPAg+Vp487gTyn6edbBF+PZoKjUb0iIlsJjm17a4jrMzHEegM1JoKJiBeIV9UuZ69nPTBLg+NNGzMkOwZgTGRLAV6W4IhtAnzJvvxNqGwPwBhjYpQdAzDGmBhlBcAYY2KUFQBjjIlRVgCMMSZGWQEwxpgY9f8BjkBJjmAYL5UAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "m1 = sns.distplot(movies.AudienceRatings, bins = 15)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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P1NfbgH+snv8E1iTZ8Nu2vxLCfa7bHGxcolrOqiTjwFXAQWB9VR2H3i8AYN3SVTZSHwc+APymm78IeKGqTnbzLff/a4AZ4NPdsNQdSS5gFfR9VX0P+CjwDL1Q/zFwiNXT96ecqa8HzsGVEO593eagNUleAXweeE9V/WSp6zkbkrwVOFFVh2Y3z7Foq/1/LvB64Paqugr4OQ0OwcylG1veBlwKvAq4gN5QxOla7fv5DPzvYCWE+6q7zUGSl9AL9s9W1X1d83On/hvWTU8sVX0jdC3wtiRH6Q2/XUfvSH5N9191aLv/jwHHqupgN7+XXtivhr5/M/Dtqpqpql8B9wFvZPX0/Sln6uuBc3AlhPuqus1BN8Z8J3C4qj426639wGT3ehLYd7ZrG7Wq+lBVbaqqcXr9/MWqeifwMHBTt1iT+w5QVd8Hvpvksq5pC/AEq6Dv6Q3HXJPk/O7fwKl9XxV9P8uZ+no/8BfdWTPXAD8+NXxzRlW17H+AtwD/DXwL+NulrmfE+/pH9P679XXg0e7nLfTGng8AR7rphUtd64j/HP4YeKB7/RrgK8BTwOeAly51fSPc7yuB6a7//wVYu1r6HvgI8CTwGPBPwEtb7nvgLnrfL/yK3pH5jjP1Nb1hmU92GfgNemcV/dbte/sBSWrQShiWkSQNyHCXpAYZ7pLUIMNdkhpkuEtSgwx3SWqQ4S5JDfo/Vl7lTKEm09MAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.set_style = 'white'\n",
    "m1 = plt.hist(movies.AudienceRatings, bins = 15)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(array([237., 162.,  75.,  28.,  17.,  20.,  13.,   3.,   3.,   1.]),\n",
       " array([  0.,  30.,  60.,  90., 120., 150., 180., 210., 240., 270., 300.]),\n",
       " <a list of 10 Patch objects>)"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.hist(movies.BudgetMillions)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.hist(movies[movies.Genre=='Drama'].BudgetMillions)\n",
    "plt.hist(movies[movies.Genre=='Thriller'].BudgetMillions)\n",
    "#plt.hist(movies[movies.Genre=='Action'].BudgetMillions)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.hist([movies[movies.Genre=='Drama'].BudgetMillions,\\\n",
    "         movies[movies.Genre=='Thriller'].BudgetMillions])\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {},
   "outputs": [
    {
     "ename": "AttributeError",
     "evalue": "Can only use .cat accessor with a 'category' dtype",
     "output_type": "error",
     "traceback": [
      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[1;31mAttributeError\u001b[0m                            Traceback (most recent call last)",
      "\u001b[1;32m<ipython-input-44-d82ec154ac83>\u001b[0m in \u001b[0;36m<module>\u001b[1;34m\u001b[0m\n\u001b[0;32m      1\u001b[0m \u001b[0mlist1\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mlist\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m----> 2\u001b[1;33m \u001b[1;32mfor\u001b[0m \u001b[0mgen\u001b[0m \u001b[1;32min\u001b[0m \u001b[0mmovies\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mGenre\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mcat\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mcategories\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m      3\u001b[0m     \u001b[0mlist1\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mappend\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mmovies\u001b[0m\u001b[1;33m[\u001b[0m\u001b[0mmovies\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mGenre\u001b[0m\u001b[1;33m==\u001b[0m\u001b[0mgen\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mBudgetMillions\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m      4\u001b[0m \u001b[0mplt\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mhist\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mlist1\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32m~\\Anaconda3\\lib\\site-packages\\pandas\\core\\generic.py\u001b[0m in \u001b[0;36m__getattr__\u001b[1;34m(self, name)\u001b[0m\n\u001b[0;32m   5268\u001b[0m             \u001b[1;32mor\u001b[0m \u001b[0mname\u001b[0m \u001b[1;32min\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_accessors\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m   5269\u001b[0m         ):\n\u001b[1;32m-> 5270\u001b[1;33m             \u001b[1;32mreturn\u001b[0m \u001b[0mobject\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m__getattribute__\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mname\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m   5271\u001b[0m         \u001b[1;32melse\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m   5272\u001b[0m             \u001b[1;32mif\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_info_axis\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_can_hold_identifiers_and_holds_name\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mname\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32m~\\Anaconda3\\lib\\site-packages\\pandas\\core\\accessor.py\u001b[0m in \u001b[0;36m__get__\u001b[1;34m(self, obj, cls)\u001b[0m\n\u001b[0;32m    185\u001b[0m             \u001b[1;31m# we're accessing the attribute of the class, i.e., Dataset.geo\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    186\u001b[0m             \u001b[1;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_accessor\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 187\u001b[1;33m         \u001b[0maccessor_obj\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_accessor\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mobj\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m    188\u001b[0m         \u001b[1;31m# Replace the property with the accessor object. Inspired by:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    189\u001b[0m         \u001b[1;31m# http://www.pydanny.com/cached-property.html\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32m~\\Anaconda3\\lib\\site-packages\\pandas\\core\\arrays\\categorical.py\u001b[0m in \u001b[0;36m__init__\u001b[1;34m(self, data)\u001b[0m\n\u001b[0;32m   2510\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m   2511\u001b[0m     \u001b[1;32mdef\u001b[0m \u001b[0m__init__\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mdata\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m-> 2512\u001b[1;33m         \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_validate\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mdata\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m   2513\u001b[0m         \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_parent\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mdata\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mvalues\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m   2514\u001b[0m         \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_index\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mdata\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mindex\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32m~\\Anaconda3\\lib\\site-packages\\pandas\\core\\arrays\\categorical.py\u001b[0m in \u001b[0;36m_validate\u001b[1;34m(data)\u001b[0m\n\u001b[0;32m   2519\u001b[0m     \u001b[1;32mdef\u001b[0m \u001b[0m_validate\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mdata\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m   2520\u001b[0m         \u001b[1;32mif\u001b[0m \u001b[1;32mnot\u001b[0m \u001b[0mis_categorical_dtype\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mdata\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mdtype\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m-> 2521\u001b[1;33m             \u001b[1;32mraise\u001b[0m \u001b[0mAttributeError\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;34m\"Can only use .cat accessor with a 'category' dtype\"\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m   2522\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m   2523\u001b[0m     \u001b[1;32mdef\u001b[0m \u001b[0m_delegate_property_get\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mname\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;31mAttributeError\u001b[0m: Can only use .cat accessor with a 'category' dtype"
     ]
    }
   ],
   "source": [
    "list1 = list()\n",
    "for gen in movies.Genre.cat.categories:\n",
    "    list1.append(movies[movies.Genre==gen].BudgetMillions)\n",
    "plt.hist(list1)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "list1 = list()\n",
    "for gen in movies.Genre.cat.categories:\n",
    "    print(gen)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {},
   "outputs": [
    {
     "ename": "AttributeError",
     "evalue": "Can only use .cat accessor with a 'category' dtype",
     "output_type": "error",
     "traceback": [
      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[1;31mAttributeError\u001b[0m                            Traceback (most recent call last)",
      "\u001b[1;32m<ipython-input-46-877c9b92477e>\u001b[0m in \u001b[0;36m<module>\u001b[1;34m\u001b[0m\n\u001b[1;32m----> 1\u001b[1;33m \u001b[1;32mfor\u001b[0m \u001b[0mgen\u001b[0m \u001b[1;32min\u001b[0m \u001b[0mmovies\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mGenre\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mcat\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mcategories\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m      2\u001b[0m     \u001b[0mprint\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mgen\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32m~\\Anaconda3\\lib\\site-packages\\pandas\\core\\generic.py\u001b[0m in \u001b[0;36m__getattr__\u001b[1;34m(self, name)\u001b[0m\n\u001b[0;32m   5268\u001b[0m             \u001b[1;32mor\u001b[0m \u001b[0mname\u001b[0m \u001b[1;32min\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_accessors\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m   5269\u001b[0m         ):\n\u001b[1;32m-> 5270\u001b[1;33m             \u001b[1;32mreturn\u001b[0m \u001b[0mobject\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m__getattribute__\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mname\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m   5271\u001b[0m         \u001b[1;32melse\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m   5272\u001b[0m             \u001b[1;32mif\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_info_axis\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_can_hold_identifiers_and_holds_name\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mname\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32m~\\Anaconda3\\lib\\site-packages\\pandas\\core\\accessor.py\u001b[0m in \u001b[0;36m__get__\u001b[1;34m(self, obj, cls)\u001b[0m\n\u001b[0;32m    185\u001b[0m             \u001b[1;31m# we're accessing the attribute of the class, i.e., Dataset.geo\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    186\u001b[0m             \u001b[1;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_accessor\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 187\u001b[1;33m         \u001b[0maccessor_obj\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_accessor\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mobj\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m    188\u001b[0m         \u001b[1;31m# Replace the property with the accessor object. Inspired by:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    189\u001b[0m         \u001b[1;31m# http://www.pydanny.com/cached-property.html\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32m~\\Anaconda3\\lib\\site-packages\\pandas\\core\\arrays\\categorical.py\u001b[0m in \u001b[0;36m__init__\u001b[1;34m(self, data)\u001b[0m\n\u001b[0;32m   2510\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m   2511\u001b[0m     \u001b[1;32mdef\u001b[0m \u001b[0m__init__\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mdata\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m-> 2512\u001b[1;33m         \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_validate\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mdata\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m   2513\u001b[0m         \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_parent\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mdata\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mvalues\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m   2514\u001b[0m         \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_index\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mdata\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mindex\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32m~\\Anaconda3\\lib\\site-packages\\pandas\\core\\arrays\\categorical.py\u001b[0m in \u001b[0;36m_validate\u001b[1;34m(data)\u001b[0m\n\u001b[0;32m   2519\u001b[0m     \u001b[1;32mdef\u001b[0m \u001b[0m_validate\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mdata\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m   2520\u001b[0m         \u001b[1;32mif\u001b[0m \u001b[1;32mnot\u001b[0m \u001b[0mis_categorical_dtype\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mdata\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mdtype\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m-> 2521\u001b[1;33m             \u001b[1;32mraise\u001b[0m \u001b[0mAttributeError\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;34m\"Can only use .cat accessor with a 'category' dtype\"\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m   2522\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m   2523\u001b[0m     \u001b[1;32mdef\u001b[0m \u001b[0m_delegate_property_get\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mname\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;31mAttributeError\u001b[0m: Can only use .cat accessor with a 'category' dtype"
     ]
    }
   ],
   "source": [
    "for gen in movies.Genre.cat.categories:\n",
    "    print(gen)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 448.125x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "vis1 = sns.lmplot(data = movies, x ='CriticRatings',y = 'AudienceRatings', fit_reg=False, hue='Genre',size = 5, aspect=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['Film', 'Genre', 'CriticRatings', 'AudienceRatings', 'BudgetMillions',\n",
       "       'YearOfRelease'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 47,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "movies.columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "k1 = sns.kdeplot(movies.CriticRatings,movies.AudienceRatings, cmap =\"Reds\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "ename": "ValueError",
     "evalue": "Illegal argument(s) to subplot: (2, 2)",
     "output_type": "error",
     "traceback": [
      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[1;31mValueError\u001b[0m                                Traceback (most recent call last)",
      "\u001b[1;32m<ipython-input-57-081166b8298c>\u001b[0m in \u001b[0;36m<module>\u001b[1;34m\u001b[0m\n\u001b[1;32m----> 1\u001b[1;33m \u001b[0mf\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0maxes\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mplt\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0msubplot\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;36m2\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;36m2\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m",
      "\u001b[1;32m~\\Anaconda3\\lib\\site-packages\\matplotlib\\pyplot.py\u001b[0m in \u001b[0;36msubplot\u001b[1;34m(*args, **kwargs)\u001b[0m\n\u001b[0;32m   1074\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m   1075\u001b[0m     \u001b[0mfig\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mgcf\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m-> 1076\u001b[1;33m     \u001b[0ma\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mfig\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0madd_subplot\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m*\u001b[0m\u001b[0margs\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;33m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m   1077\u001b[0m     \u001b[0mbbox\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0ma\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mbbox\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m   1078\u001b[0m     \u001b[0mbyebye\u001b[0m \u001b[1;33m=\u001b[0m \u001b[1;33m[\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32m~\\Anaconda3\\lib\\site-packages\\matplotlib\\figure.py\u001b[0m in \u001b[0;36madd_subplot\u001b[1;34m(self, *args, **kwargs)\u001b[0m\n\u001b[0;32m   1412\u001b[0m                     \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_axstack\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mremove\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0max\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m   1413\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m-> 1414\u001b[1;33m             \u001b[0ma\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0msubplot_class_factory\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mprojection_class\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;33m*\u001b[0m\u001b[0margs\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;33m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m   1415\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m   1416\u001b[0m         \u001b[1;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_add_axes_internal\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0ma\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32m~\\Anaconda3\\lib\\site-packages\\matplotlib\\axes\\_subplots.py\u001b[0m in \u001b[0;36m__init__\u001b[1;34m(self, fig, *args, **kwargs)\u001b[0m\n\u001b[0;32m     62\u001b[0m                 \u001b[1;31m# num - 1 for converting from MATLAB to python indexing\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m     63\u001b[0m         \u001b[1;32melse\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m---> 64\u001b[1;33m             \u001b[1;32mraise\u001b[0m \u001b[0mValueError\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;34mf'Illegal argument(s) to subplot: {args}'\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m     65\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m     66\u001b[0m         \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mupdate_params\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;31mValueError\u001b[0m: Illegal argument(s) to subplot: (2, 2)"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<Figure size 432x288 with 0 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "f, axes = plt.subplot(2, 2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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AQ2nvG7Zeuwsi+jYRnSWis+khjyLo7u7G7OwM9JpNS17Xa9oBwNHiV7ly7NgxeFTCR+pzEw4PN5nvcyJeuhBs3w7XmyYlvU7H1WtX101HtUgkgvDiYko4AHeir9Yao6OjeP31N7Cl/n4EPMGs728ItqG5ajP+8YV/XDPaw8jICELz86hZxaQEmL0d/G5XyYWDYRh4/vvPozXYiAPNuwsaY0NlEx5s3o1XXnlFSlHEteaQziQ+M4bUMPOzzHyQmQ82NjYKXcTJkycBImg1bUvn9FUD/hqcOHlS6HzFYhgGjh09ggfq4vBl9sXdRaPfwNYqA0ePHpG7uAK5ePEiFL8C2JF9DUA0Ek3lnqx1bEFQaz2AtVt+5fvf/z7AwO4NuUXLAMDejY9hLjSHf/7nf5a3sDywN/uaFSKVbMhySl8qcQmZ48ePo3+gH5/f8smMzv9c+fy2TyESiUj5P5RKOIzb5iLr2Xa5DwNoT3tfGwDHbThHjh41HdHuu22viZpNuHDhwpqK1rhy5QqmZ2bxSHN+DWUeborh+vUbay7BjJlx7vw5aI1a6rjATeYZYT0k7wF3BEEtUi6TNSkcBgcHcejQIWxr/EhOWoNNQ+VGtFZvwz++8I9ropT3lStX4FZVVGYxKwGm32FicrJkZj5mxvPffx7NFQ042Hp3Pkk+tFe14CNNO/HySy8Jr3pQKuHwUwDftL7+JoDX0l7/11bU0scAhGzzk1MMDAxgoL8fydrNAADPwCl4Bu6YkfS6rTB0fU1F+hw9ehRuxYxCyodHLNPSWiuJ0Nvbi9BcCGhOe9Fv+h1OnzldsnXlg+3LqQPgAqFGUdZkm8rnnnsOquLG7taP3vWzC4Pv4sLguyt+dl/bJ7CwuIAXX3xR5hJz4vKlS6hyqznZ7m3tolRh6SdPnkRvXy8+t/UTRWkNNk9v+xTCCwv4yU9+ImB1d3AilPWfAJwCsJOIhonoWwD+A4BfJqIeAL9sfQ8AbwDoA3ATwH8F8D/KXt9y3n3XvBn0uq0AAGVxGsrinRh1o6IB8FXh7bffcXppGUmZlOoTCGQwKf2wy48fdmWOPmkJGNgcNHDk3ZU3gFLw/vvvAzCT39LRm3RcvHhxzdi5V2NwcBABRUHAUn3qDAPDQ0NZPuUsPT09OHLkCDqaHoLPXXHXz+ciE5iLrBxHXxtoRnvdLrz80sslTfJbXFzErf7+rCYlmyqPmQxXCuHAzPjB8z9AY0XditVX82Vz9QbsbbgPP37xx0LvDSeilX6DmVuZ2c3Mbcz8HDNPM/OTzNxhPc9Y72Vm/n1m3s7M9zOzo3GjzIy3Dh+GXtUK9tx9swAAiJCo24rz589hZmZ5EJbzXLt2DZNT0yktYDkDYRUD4ZVV7Uea4rh2/fqaMi2d/MVJUC0By2QatzK0pIZz586VZmF5MDg4iHrjjnBrsF5bS1npzz33HDwuH3a2HCx4jH0bH0M8EccLL7wgcGX5ce3aNTAzalZIfluOmQznwmUrl8lJzp07hxtdN/DU5o9DVbKbwHLl89s+idB8CD/72c+EjbnWHNIlpbu7GyPDw9CW9W9djlZ/HwzDwJEjpXfmHj16FC4FONBYWAP7R5rMz62VqKXZ2Vlcu3oNemuGqKRGgDy0pkx6KzFw6xaa0mIpGgFEotE1E85648YN/OIXv8CO5oPwuHwFjxP01WFz3R785Cevlqxyru2Mrs5RcwDMOkvdPT2Otw194YUXUO0L4tGNqxfYy5f7ajejo3Yzfvzij4Xl05SFQxqHDx8GKSo0y6S0EhyoBVfU49DPf+7QylZYBzOOHT2CfXXJjCalXGitMNAe5DWTEHfixAkwM3ijubHSRQJdtOzICqC36Dj+3vE1nVAWCoUwGwohPYbOjtW+detWKZZ0F88//zy8bh86mosvQrB7w6PQtGTJfA9XrlxB0OOGW8l9O6vxuqHrOrq7uyWubCk9PT04d+4cPtP+UbiV7Dfsj6+/iR9ffzPn8Z/a8nFMTE6kTOPFUhYOFpqm4edvvYVkdRvg8mZ9f6J+O7pu3Ej1fCgF3d3dGJ+YxMMFag02DzfGcOny5TVRHO7I0SOgIKWSA2iOQHN3nIzcxlgIL6zpbnZ2mY90f3rTsp+Vklu3buHkyZO4r/FBuNXs13o2gr5abKrbjddefc3xKD7DMHDt6tWMyW/XZ8O4Pps5kqrGa27OTiZWvvzyy/C43Phk+0M5vX84PIbhcO65MfsaO9Bc0YCXX3pZiPmyLBwszp8/j9DcHLQc09h1y/TkVMu+TJw4cQIKIWuhvWw81JgEM5v5HSVkbm4O58+dh75Rz5zxAgAtALlI2OlIBnZphmYAb4DxBhgVIAQVZU3kadg1lO4ToDXY7Gx5GLF4zPGs6eHhYSwsLmZ0RocTGsKJzBqmV1URcDAZLhQK4Z133sGjrR9BRYYQeREopODTmx5BV3eXkLLkZeFg8dZbb4Hc3lQWdDbYUwG9agN+/tZbJXMynnjvODqqNVR5ipt/U6WOxgDw3nvvCVpZYRw/fhyGYYDbVvl9VEBv1XHk6JE1a1rq7e01q7ECGLUeANBiGOixOpWVilAohLfffhub6/auWkMpX2oCTWiu2oxXf/Kqo/8XexNcrdjeSgTdKq45JBzefPNNJJNJfKr9YanzfGzDA/C6PEKEdFk4wOyDcOz4cSRqNgM52AJttPrtGL19uyTNQ8bHx9HbdwsPFmlSAszyUQfqYzh39ixisZiA1RXG2++8DaoioGb193G7aVo6e3ZtFkHsunEDLYYBWqb+tAIYGBx03AmazqFDh5BMJnFfk1iHKABsb9qPyalJRxtJXb9+HS5FySn5bTnVHjfGJyakN2JiZrzx+hvYWtOGjcHm7B8oAr/Lh4PNe3Hk3SNFh7WWhQPMuPp4LAatPr/KiFrdFkBR8M47zuc82LkA+Sa+rcT+hiQSyWTJSpJPTU2h82In9LZVTEo2LWbU0lo0LcXjcfT39yNTi/gNAHTDKKnf4c0330R9ZSuqA2JLzgDAhurt8HkCOHTokPCxV+LGjRsIul0FFa6z+z50Sdbment70T/Qj4+1rlwKXSQf2/ARRGPRoi0BZeEAM/GNPH4YVS35fdDlhVbVhnfefReGkbktpyw++OADNPiBDSu0A82XXTUaPGrp2ocePXrUjFJqz8FEpgL6Bh3Hjh8r6Sk8E729vdANI2O1SPs12ZvRSgwMDKCvrw/tdYUVesuGoqhoq9mFX/zilCOJirquo6enB0FPYfkCVQ61DT1y5AiICA+17JU6j819tZtQ46vCsSIjEO954RCPx/GLU6eQqNkCFJDKrtVvxfTUlKNRD5qm4fy5c7i/Lo4CDkwZ8ajAzpoEzpaoPMXb77wNqiGgKrf3czsjGoni9Om1VU7Dvg4yCYdqABUlbFNp54e01XRIm6OttgPJZMKR/8vQ0BASiQSq3IXFcbsUBRUet/TeDifeO4GO2s0IrpRYKxiFFOxv2oXTH3xQ1OHpnhcOp0+fRiIeN01EBaDXbAJIcTSJrLu7G5FoFHvrxJiUbPbWJjEwOOR4otb4+LiZ+NaWRznuJoC8tCYSEdO5du0aqhQlo4wjEDYaBq6WqKbPmTNnUBNoRMCbowQugIZgG9wuryNZ7PamHswxMzoTlaoiVZObmJjArf5buL9BnkDOxP0NHYgnEkWFfN/zwuHkyZMglwdGsMCeQi4v9KpWR8t4236B3VnagebL7lpzPKdzCGzBumqU0nIU07T03on31pRp6dqVK9iYwRlt0w5gcGjI8Uqmmqbh8uUraKzMLRqvUBRS0FCxERfOX5A6D2Ca8IgIlQVqDoApWMbGxhCJRASu7A72vbqrfpuU8VdiR91mqKQU5UO8p4UDM+MXp04hWbURyCO7cjladTuGBgcd6xB36dIltFYwqr1iQ2i3BHV4XYTLly8LHTcbR44eMU1KuVeMBmAKk3gsvmailubm5jAyOorVtl/7Z06blszOegnUV2ZylYulrqIFg0OD0jZcm76+PlS6XVCKsK3agqW/v1/QqpZy5coV+NxetEmOUlqOR/WgvboVly8Vfi/f08Khr68Pc7OzOec2rIRuNQU6c+aMiGWtCjPj2pXLuK+q+BDW5agKsD2YxJUrzgmHmZkZXL1yFfqGAjq8NZlRS6XOz7Cxq3xuWuU9bTCDsZyuCGpHSMmIUlpOTaAJzCxtw7Xp6+tDRbaG6VmwQ2BlrbW7uxvtlS15l+b+8fU3MRQew1B4DH99+r/lVUbDZnOwFT09PQXnYd3TwsE+cepVGTuR5gz7qkHeSkdOsBMTE5ibD2NblZx2mdurk+jr7UMiIV74ZOLUqVNmlNKGAi5gBdCbdZw4ecLxaLFMXL58GSpRxjBWGy8ILUSOVwQ1e0kQKr1ZkkgEEPTVpc0ph1gshomJCVQUYVICgIBLhaqQFOHAzOi/dQsbK5uyv3kZw+ExRLU4oloc3bMDeZXRsNkYbEYkGsHExMpl11fjnhYOnZ2dgL8a7C0yioAIiWALLly4KD1b2i4UtrVKThbqlqAOTdcdKxD3/vvvQwkoWRPfVmQDMB+aL0ki4nIud3ZiAwB3lkSNTcy4evWqo5nEk5OT8HsroOaR5FkofqujnOje7umMjIyAmVHhKq7sNREh4HJJqZEWCoUQiUbRVFEvfOxcaAqYQrpQc/c9KxyYGZ2XLiNZkb9Uz4QRbMH8fCjVAUwWdm2etko5mkO7Na4TiVqapuH0mdPQmrXsiW8rYDcEKnVIazwex43ubmzO4XCwCUAsHpceQpnO7OwsfK5A9jcKwK164FLdUgs52pt5RQGZ0cvxqwoGBwaKHmc59om91icvOmw16nzVS9aRLyUVDkT0PxHRVSK6QkT/REQ+ItpKRB8QUQ8R/ZiIPDLmHh0dRXg+BKMAlS8TujWO7EJet27dQlMA8InrE7KEZr8BtyLPBpvOjRs3EI1E7+r4lhdeAHUoefvQ69evQ9M0bM7hvVus50sOmpYiixGocm6ljLhdXqkOafs0HChSc7DHGBsbE26atMtyVDmU37AcO6+i0PIgJRMORLQRwB8AOMjM+wCoAL4O4D8C+Btm7gAwC+BbMua3Y5uNSjEOOvbXgFQXenp6hIy3EkODA2jxi81vSEdVgKYAO1KKPBVmV6R8NhoNXL92vaR1oTo7O0FY3RltUwVCnaI4GjIcT8QdMSnZqORCMinvOr19+za8LhWuIqIMbQIuFUlNE57fYwtHXw4tAGRgz1totnqpzUouAH4icgEIwCxg+RkAr1g/fx7Al2VMfPPmTYAIhr9WzICkQPfXoluicGBm3L59G81+OSYlmxZ/EsNDg1LnAKwNtZrM038RcCND13Vcu3ZNzMIKoLOzE81EqZ7R2dhsGOi8cMExR7qhG3nVH7ow+G6qh/SRGy/iwmB+dayICLou7zodGxuDTxWzffmsiCfRrXJt4ehyUCino5AClZSCg0tKJhyYeQTAXwEYhCkUQgDOAZhjZttTN4zMlQhARN8morNEdLYQx1d/fz/grwYE9nHV/bVSHbkLCwuIRGNo9MvdUOp9BsbHx6U615kZl69chl4nYAOx/H1O1eZfjqZpuHL5ck7+BpstAOYXFjAgwdadCUVV8vp/zkUmkNTjSOpxTIaHMBfJz27NYKiqJNsnTOHgFaA1AIDfWqdo4VBIMUDRcBHrKKVZqRbAlwBshVmwsgLA5zK8NeMVzczPMvNBZj7Y2Ji/aah/YBCatzrvz60G+2oQmpvDwsKC0HFtbMdSnU+ucGjwGYjG4tJ+D8A0C0QWI0CdgME8AAWpZAXturq6EIvHU76EXLDf61QVXLfbDYPlapzpGIYOl0veiXlqakqY5uC1NAfRZiX799eM0vQdMdiAwUbB/4dSmpV+CcAtZp5k5iSA/w7g4wBqLDMTYOYMCU87ZmaMjY6CBdeYMXxmCJ+siCW7gXutV65wqLHGl9kw3vbNcK0Y7USv0XGjuzThrPYGvyWPz9QCqFaKK2+QDz6fD7qDm5RuaPB65djao9EoIpEIvIKEg4sILkURLhwCATM6LK45kzO0HHtev7+wpk6lFA6DAD5GRAEy9Z4nAVwDcATAV633fBOA8L6Dc3NzSCYTMLyVQsdlrykcCg0dy1CPmO8AACAASURBVIYddRB057ah/rDLj4GwioGwiv/zbCV+2JXbRVJljS+zCUpfX58ZvipKPlcDE2MT0ks2ZOLixYtoVBRU5hGPSyBsNgxcPH/ekU6Cfr8fOjuzSTEzklq84E0pG3aIrCjhQETwulTMzMwIGc8mGDT3g4Wk/PLlmVhImvdCdXVhFpJS+hw+gOl4Pg/gsrWWZwH8CYB/R0Q3YVqTnxM9t715s0ds3LdhjScr+ScUCgHIXTgMhFVEdQVRXcGNOTcGwrnZgINW21GZzeIHBgagVCpmjJoAOGiu2Ykoq3R0Xcelzk5sKcCxvAXAbCjkyJoDgQA0Q170UDoG6zDYSJ2cRWNv4h5BwgEA3ATheRm1tWawy3xcnnl2NeYTiwCAmprCMkxL40a3YOY/BfCny17uA/CIzHntEzG7BV+8Lh8A8ReZje0DqMhROBRKwMVL5pPB0PAQ9IBAG7hVtG94eBg7d+4UN24Wbt68iWgslpdJycb+TGdnJzZtyiUItnACgQCSDpk3krpZJbeiQk58v31I8ghySAOAm0j4fdvQ0ACFFMzGQkLHzZWZqDlvU1NhseKlDmUtCfbFxdZmLgxSQB5fanzRLC4uwqsSFMlBEH4HhMPo6Ci4QqCQC9wZ10nsXIUtBXy2AUClQ36HyspKJLS4IyaspG4KIVmag63RukVqDqoi/L51uVxoaGjAZFRepvhqTFvztrYW1o7gnhQOdi19dknIGFW90mr1R6NR+BzQ9byquYHISiqLxWJYXFhMbehCcAOKR5FazycTFy9eRL2ioKqA+h93/A7yex+YGzU7YlrSLOEgS3Ow7y+3wFOSWyEsLi4KG8+mfVM7xiPyAjtWY2xxGvW1dQUL6XtSOKSclqp44WCobmn9cxOJBDyq/JOfiwAiSGuik4qCEuyvZD872sWOmXG5sxObikhk2wJgcnpKusZjbxD2xi0TzZCrOdgarUtgHoFLURCLxYQXQ9yyZQvGF6dhsPNVg0cXJ7F565aCP39PCodYLGbufgX0jM6GQS5pETOJRAJuB/5jRIBHIWllu23bLgtuVmR4DKkRVssZGBhAKBzOqZ7SStifld1gyeczTaiOaA5WyKysUNZIJAKXoghNMrMFjeiD3bZt2xDT4in7v1MYbGB0cRJbt24teIx7UjjE43GQ6jJ3QdGQikRCzg2YTCbhIvmaAwC4FEgrKZ0yu4lW3DzAXMg54WAXzitGODQD8BFJL8LndrsBwJFEOMMSDh6PnEJ/0WgULoH+BgBwWSYq0Qe77du3AwCGCujHUAyTkRnEtQQ6OgrvXX1PCodkMgmQnNR+VgqvZZINXdehOCQc1HUoHNjDCC8415v5ypUrqFAUFFOtXwGhzTJPycTOknVEOFhz2AJJNNFoFGqWg9312TDCCQ3hhIbT47O4Prv6dWGPJ9qUun37diiKgoF5Z1oI2wzMm2ZK6cKBiCqITBsMEe0gomeISM5/3gE0TSuqZ/SqkCJtU9V1HapDwkEhSCsKl1LdRTvXXUAs6lxl1suXLqHdMECFNqOw2ASgf3BQanSYYl3vTkQr2XPIqi0Uj8ezRuyFExo0ZmjMmI0nEU6sfk+qksxKXq8XW7dsRX9Ibp+X5fSHRuBxexwxKx0H4LPKbL8D4HcAfL/gWUuMuellv3A9A6egRKahRKbhu/YzeAZO5TA6QZe0qRqGUeQ2lDsKQVpVTZnCIR5zJlwzFAph5PZtFNd93KQd5oZ6/fp1AaNlJrVhO3IFyZ0jkUgIN3nYwkZGmfE9e/dgIDzqqFO6f34EO3Z0FFXfKte/MTFzBMBXAPwtM/8qgD0Fz1piDMPIyRmtLE6D9CRIT0INj0FZzCEkjQiGIWdTZWZQ5jqE64qU6i7asqeafyMn2m/abUnbBIxllx2W2erUFvROVApVrDlkHS4SiYRw8WOvWYZJeO/evYgkohjPZf+wiFrlR7761a/C7/cjquVu7tIMDYPzo9izd28hy02Rs3AgokcBfAPA69ZrJc2uLgZTOEi6SUiBrss5ITCztGUvhyDPBJE6nQm/w5eNLxF7I98gYCw/CPWKIlVzsDc9Jxr+KNYcskKhk8mkcM3BFpoyDhZ7rU26LzSc82eiyRiefvpp/MEf/AGefvppRJO5m0uH5seQ1DXs27cv77Wmk+uV8kcAvgvgJ8x8lYi2wSyQty4xTzRydlmW3OTEKWQKoWQyCVJJmnBIJBLSYuxturq60KAo8BliBOgGw0CXROFgJzSqinxXocuaQ6pwEHyB2sJGhnBob29HsDKI3tlBPLbxQE6f8bt9eP118xz++uuvo8Gde/G83jmzVpcjwoGZjwE4lvZ9H8wWn+sSXdelag5OmDXWM2ZAgISBlbTxJdPT1YWWHH1XubABwOXpaYRCoYKraK6GHaLplpD4uRyXNYeMjGMA0DVN+O1rjyfjYKcoCvbdvw+9l2/m/Bm/y4toOIpXXjGbYvprc6+P1Ds3iJbmFjQ0NOS91nRyEg5E9C+4u+lOCMBZAP8fM5eueW8BaJoGlhTKapqVysJhNTRNA+VQ+oAuEmClLShHFXANg/evclK3hINszW1hYQHjk5O4X+CYLdZzb28vHnzwQYEjm4TDYRAILkW+cPCo3tScMtB1XbjSaTvqZR0s9u3bh1OnTmEhEUGl4GrQ6TAzekPDePgTHy16rFzPb30AFgD8V+sxD2AcwA7r+3VFIpEAS8iOBgAo8pLgnERmwE+umgPNEShpPSYJNJdlS3DI59Df3w/gzoYuguZlY4tmfn4eXrffEYe0x2XWRZEmHAxdeNSV/WeRFb59//3mUaJvTm559unoHEKxcGq+YsjV53CAmR9P+/5fiOg4Mz9ORKVp3FsEsVgMhrQkOBeSkpLgiEjqpp1OMb1ns5FMJqWalWQLB7vvc/7NaVemEoBPUaQJh1AoBK9bTvOd5bhVLxRSpJUyYYOF+6vs4WRpnbt27YKqquidG8IDTfJKytv+BhHCIddbtJGIUgXnra9tg1bBOyER1RDRK0R0g4iuE9GjRFRHRIeJqMd6ri10/JVYWFwEq5Icc4obuq5JccaZm3Xpm5YXSzweFx/GCoCtooSyMtRthoaGoBJBpGeAQKhnxvBw7hEt+TAzMwOP6oxwICL4PAFpfU2czPcRhc/nQ8d9HanNWxa9c0Pw+/xFJb/Z5Coc/hjACSI6QkRHAbwH4H8mogoAzxcx/38BcIiZdwH4CIDrAL4D4B1m7oCZcPedIsbPSDi8IKUiKwCwNa6sbFenshyY5Wa4sozqspbAkVVq3GZ0dBS1RFAFb1F1zBiR1BVuenoGXpecEtqZ8LoCwttu2hgS1Gf7PynLrAQAe/ftxUB4FLqkPCjADJfds2c3VLX401dOwoGZ3wDQATOk9Y8A7GTm15l5kZm/V8jERFQF4HFYbUCZOcHMcwC+hDsC53kAXy5k/NWYn58X3+jHgt3e1ByiURTF0RQ4RVKJkcXIIgxVwk1oKYOy+0iPjo6iWsImUgNgcmpKygY1OzMDn9tJ4VCB6Sk5fQxYhuZgHYRkZtfv3bsXCS2BkQU5PeYTegIj4fGik99s8rn7HwKwF8ADAH6diP51kXNvAzAJ4L8R0QUi+ntLE2lm5lEAsJ4L63G3AvF4HLFoBOyWJBwsZ5wMldr0OTijUMtM9A+FQuIrsgIp4SDLEWozNTGBKgnjVgHQdF14R7JYLIZINAK/g8LB566QpjmwhCOSfVfJFA579phFJW7lkQyXD4PzZokOe55iybXw3g8B/BWATwB42HocLHJuF4AHAfwdMx8AsIg8TEhE9G0iOktEZ/Pp/mU3mhHeP9qCrTA1GU1nnNQcmCFENc3E3Nyc8F4OAADvnfFlwcyYnZtDpYSxrTbYwjdVezwnNQefqwKzc7NSNltmeTWiZAqH1tZWBCuDGAzJaezUHzIrv+7atUvIeLlGKx0EsIfF/uWGAQwz8wfW96/AFA7jRNTKzKNE1Aogow7GzM8CeBYADh48mPO6JibM4dgj50axx5XRrlJRFIiP8M6MIcnnoGkaQnMhoLC2tqvjBkglqa1CFxcXoRsGcrl63gDD3gaeA6MVwOdX+f/ZxxXRmoOtxToqHNwB6LqOcDiMqirBehaLj1a6M7Q84UBE2LV7Fwa65PiVBuZvo76uHvX1xRSRv0OuZqUrEBvWDWYeAzBERHZc15MArgH4KYBvWq99E8BrIucdHx8HABheGWc/AKob5PZhbEx8cw9VVSGoWkNWdEmaw8TEhHkDylDcCKAKkvK3t7FNVrnE/YwCiFuPfuv71bANnaLNYrZw8ErSljNhCyIZpiUZG7hT0U8dHR24vTCZ6pYnkqGFcezYuUPYeLlqDg0ArhHRaZjXOgCAmZ8pcv5/C+AFIvLATLT7HZgC6yUi+haAQQC/VuQcS7h921S92BvM8s7CMbxBKT2BXS4XdId8Drohp1mLHarJlXKknB7QMTA4IGVs4E4klAyXid1UU3RPAdvM5nXlHsqa1M2qoE8//TRef/11JPX8QrPtuWSY+AxmaZu57HLvHR0d0A0dowtTaK8Sd95O6kmMLUzilzs+K2zMXIXDnwmbMQ1mvojMvosnZcwHACMjIyBfJaBIKp8BQPcEMTAoXnV0u92QVPD1LjSDi6oFvxK9vb3mFzI8ugC4mjF0cwiapklZv52/IiNLxl6t6BwZO3IuL+GgxfH0M2ZVUAB486eH85rTYyXcyYjak5EJaltQZQsHu23oyMK4UOEwujgJZk6NL4J8Cu99KBgcGoLmkbQzWRi+KkyM3kIymRR6+na73Ug6oDnohulzkNEDuLu7G0qFAt0rKda7xsxy7evrw44d4lRsG7v2jowgX/u4Irq+z/z8PBRS86rI6nZ5l1QF9bry07Q9qi81t2hk5DmkxpaY5wAAbW1tcKkujC6I9YvdtsYTkfxms+o1TkQnrOcwEc2nPcJEJOFIIBdmxuDgIAyfXOHAvmowc8qEJQqPx4OEA9XAk9b9IdqsxMzovNQJvVbeL8H15sZx+fJlOeM7Vb9EIAsLC/C6fXkFGLhVL6JRsypoNBqFW/Vm/1AaHiuPSEYyKBuGhKLK5oCyhYPL5cLGjRswtig2mnFscQqKomDjxo3Z35wjqwoHZv6E9Rxk5qq0R5CZ5e6wEgiFQogsLsLwiS+JnI7hN8cfEpzt6vV6Edfkb05x3bxRfD6xuSCjo6OYmpwCN0r8HQKmU/rChQtShk/1YpYwtj2m6OTDSCSSKqPtFHb1VxkJiYaAvt3LcSJD2qatvR2TUbF5UJORGbQ0twg90OWT55D1tbWOvVmzbOFgjS+6Tk4gEIBmAFqO129Uo2WtBnO7oWKWcPD7xdbi+eADM2qZmyUKBwL0Rh1nzp6RUn7Zvvlk6D72mKI1tkgk4kip7nSICC7VI0U46BIypGVXZU1n48aNmIzMCNVCJ6Oz2LBRRF/CO+R6RFmSj01ELpgZ0+uKkZERAJCuOcDlBbl9wjWHigozPDDXTT6i0ZJWg5EcP2ePX1kpNtz35MmToCBBSgZZGtzKiEai6OzsFD627YeRUffVHlO0rycej0Ml57v6ulS3lCKIhq6Lb/ZjPTvRxbG5uRkJPYmFpDjBORMLobVVbPLQqlcMEX0XwP8KwJ/mYyCYlVifFboSB7gTxip5dwKge4PCfQ62cIhohKAn+6kj4OIlTsUmV24nFVuI2POJIBwO49y5c9C36/KDylsAchGOHTuGhx4Se4axtSkZwsHeRkVrbPFYHIrE6LyVUBWXlCKImq6DBGtXMntIL6epyawINBubR1BAMm7S0BCOL6bGFUU2n8NfMHMQwH9a5m+oZ+bvCl2JA4yOjoK8csNYbQxPJW6Pik3GCgbNiJHFHDUAv4uXOBX9OQoHe3x7PhEcP34cuq6D2x1w6LoAo8XAu0ffFX6z272pZdR9tQNYRfe/TiQSJdEcFFKk9NbQJWgOMntIL8du3xmKi0l2tMcRlRltk2tV1u8SUS0RPUJEj9sPoStxgMnJSeiSymYshz0VmJqcFGpXtHsLhxNyj97z1vg1NTXCxjz080OmSUl4d47MGJsMzM/N4+zZs0LHraioABFJEQ72mKLNeclkEoqszoeroJAqfLM1DAOGYUARLB2ICETOCIfaWvMmCCfE9NheSESWjCuKXB3SvwvgOICfA/hz6/nPhK7EASYmp2DkkQhUDIYngGQyIbTJuv3Pn0/IvdHD1viiGt2Pjo6i82In9E0OmJRsWgHFq+DQoUNCh1UUBRV+vxThYOdFi9TYAKtnd0mEgyJ8s7U1ESmNBCVpOsuxa00tJsVkwtvCQXQNq1z/xn8IsxLrADN/GsABmOW21xWhuTlppbrvQkL5gLq6OgBASLLmEEoQKisCwhyj9gbNmx3MEVAArV3D8feOC0/ECgaDkNExQpZw0A2jJMKBoAiP/kkJBwlFIVUiR4RDIBAAESGaFHPEiGqmQVL0dZPrFRNj5hgAEJGXmW8AkNcIVQLMjEgkAs4zmafg+VziO8IFAgH4vF7MxeXe6HNxBfWWICoWwzDws9d/BjQDOZUyFQhvYWhJDYcP51f6IRtV1dUQW/3IJApTMxFtVpKRF5ALRCQ8+seOflIk/DqKQtJbzJrzKPD7fIjpYuaKW+OIDmTIdZcZJqIaAK8COExErwEQG4ojGU3ToOsaoDrjmGOrVIHoaI3GxgbMSBYOMwkVjc1i6r5cuHABkxOTMLY4VBQqnVqAagmvv/G60GGDVVWISthsowAqrVOlSMyM4lJ0XSbhmoNdd0qVpDk4IRwAwOPxIqmL0VIS1jher9iDb64O6V9l5jlm/jMA/wfM1p5fEroSydjqIjsV0mfNI/pia2puxnRc7u8wE3cJC4t74403QB4CbyxN2Ql9s46bPTfvFPwTQDAYRFzC0TUG8c5ooJRmJRJebsQWDjLMSgrJ7z9u43a5oLMYwamzqZ2JTp7M+4qxivAdB/C/CF2JZO5cpE6doOT0pG1ubsFMXJ72oxnAXIzR3Nxc9FiRSATHjh+D3qbfqSrnMLyJAQVCHdOVlZXSopUqJAgHLpFZab1pDgqcEw6KqgoTDnYhQtHaYbbCe+1E9CwR/YyIfpeIAkT01wC6Ibi3s2zu/OHy2Kz1xJLyE8jLRijnH9bS0oLZGKeK44lmOma2IhUhHE6cOIFEPOGsI3o5XrNcx+G3DwvbqPx+P+ISCvAlIDbx0MbcPErjcxAtHOxeF6oEzc1J4cASe1KIIpvm8AOYvoW/hVlC430AGwA8wMx/KHltQrFr+5ORu4OMtMSS8hOk5SEcDDmqXkuL6QuYisoxE0xa44pIxT9y5AgoQIDY3Jy84U2MmekZXLlyRch4Xq8XmgThkCSCV3CxQ0BWFdMc5xb8d7I3b1k+h6iEWlCZEOkHsk1sogVxNvtEneVnAICfE9E4gIeZWVg3EiJSAZwFMMLMXyCirQBeBFAH4DyA32Lmog33brfbrHaZR3s+dnmWlJ/gPHIkyJpHtJPI3rQnYwpaK8SrD5MxUzhs2FBcEa9oNIrTp09D3+xgbsMKcCuDFMLx48fxwAMPFD2ex+OBAUAHQxX4y+lEUnpoWDqs8HGzIcPnkNIcsmysmmEs6WSn5XCwcykkpVBgJpKaBheJsbXa44jOKcl6/LQyo+uIqA7AGIBA2vci+EMA19O+/48A/oaZOwDMAviWiEmICD6/H5RPhIDqWVJ+AvmUPbbmEV0Kwd60xyNyjPgTUQUuVU2l+BfKhQsXkEwmwRuK2BySWGrWKzS4ww0YjQZOvX+q8LWkISvyhyWOvdZNGLlib96uLGalpMFLtP5kDs3XVXJOOCQSCbhVMVYFtxWBKTr4JZvmUA3gHJZeW+etZwawrZjJiagNwNMA/j2Af0fmnfEZAL9pveV5mJnYf1fMPDYVFRUICYotzgZZ84iOPqmvr4fb7Uqd8EUzEVXR3NwIVS1O+Jw9exbkIrP7eKEkkbrBAeDlN18ueChuZgxdGsLk5CQaGxuLWJS8hj8EeSWjS+X1Ef23sjfvbJqDW6ElWr87Bx+FqpDw/t2ZYGbEE3G4FTGBJR5JYfOrro6Ztwid7W6+BzPqyU7tqwcwx8y2fjQMIGNrIyL6NoBvA8CmTZtymqyqqgqjU2L7864EycpaVBS0tjRjUtIJZzKqonVHW9HjdF7qBNdycVFKbiy5wVGEhc5uMHT58mV85jOfKWJR5glNAYSalABAZZYSZ2/apEsjHkRrQrlqDi5FQdjS+gGg1pv9lO4iQiweM53FEp00iUQCuq7D5xJjcvZaCbeiBVuutZV+lYiq076vIaIvFzMxEX0BwAQzn0t/OcNbM17VzPwsMx9k5oO5ngRrqquhaM4JB7fHI9znAACtG9owKSmcdTLmKtrfkEwm0dfbB6OuyFOwG0vNesVo4TUAKYSurq7i1gRgcXERHsHd2gDAy4yIwFpcNoqilKS9qcFG0RrociKRCBQiKXkOLuvvJFt7sMf3CurOZ48jso4bkHuew58yc8j+hpnnAPxpkXM/BuAZIuqH6YD+DExNosZqJgQAbRCYiV1VVQXFkF87BQCgx1FZKVZrsGltbcVkVLzPIaoB4QSnIqIKZXBw0CybIK6oa/EoAKqBmzdvFj3U/Pw8xHqSTPww63+JxuVywWAHmo8vg2GkogRFEYlE4BEscGxsbUS238EuqRMQVOfNHqdUwiHT+4r6rzPzd5m5zTJdfR3Au8z8DQBHAHzVets3AbxWzDzpBIPBlLlHNqTFUVUlTzgsJhkRwdWFp2JiwlhT7ViDJcxvyIBeqWNwaLDocSYnJhCU4BsIApiamhJ+yvd4PNDzCOEWhcGa8OirxcVFKTkOgGlWAsTWQ8uEPb5fkFnJ7/ItGVcUuQqHs0T0n4loOxFtI6K/gemolsGfwHRO34Tpg3hO1MAVFRWAY8IhgSrB/gYbu7TFtGCntD1esQlwExMT5hcyjtfFEACmJovffMdGRyGj0WwNgGg8LryKrD8QgGY4E4iRjmYkhUfrLS4uwiXJHeC85iCmUF7AEg7hsJjmQTa57i7/FmYC548BvAwz0//3RS2CmY8y8xesr/uY+RFmvo+Zf01kTkVFRQXY0FMJajJRjKSUbFfgzuYtSzgUW1dpdnbWvLKc7WmfHZ/ZRayYE1Y0GsX45GRRQVgrYY85OFi8dpNOZWUFNIei9NJJ6nHh98Di4qKUXg7AHc1BtHlmOfYmbm/qxeJ3y9EccjINMfMigO8InbkE+OzsU0OT3iqUWBdeQtfGdsDPCq7OOhNXoBCl+kYUSiQSgeJRoJPzpoxVsRzakUik4CiyW7duAZBTO8bW13p7e3H//fcLG7empgY39X5h4+WCwQbiyajQboKAuQFmi1QqFJcVZOCU5uAXJBwUUuB3+5wVDkT0PWb+IyL6F2SIGmLmZ4SuRjJ25BAZuvTAPmJdeOkMG7tXrGjhMBdXUFtTXbQTMZFIyGnVVSzWecAu3lYI16+b+ZoZ46uLpBpAQFFw48YNoePW19cjkliQHqKZTjwZATMXfdBYzuLiQuqELxpb6MjWHEQ7pAHA7/YKX3e2XeCH1vNfCZ21RCh2+KETYX3MwsP4bFwuF6qClQglxCa9zMUV1BeZGf1h5/Lly6hSFFRLcEgTCO2Ggc6LF4WO29zcDE1PIK5F4XM74whaTJjBjcVGvi0nGomiWkIYMXAnsc4JzYFAwkJZAcCvitccVv0rp+Ug7GfmY+kPAPuFrsQBUtmnDtUSkBlbXltbi3nBmkM4qaCmtviTntvtBkrQ2ycrlpWrUI2OmXHh3DlsllgCeyuAkdu37zj1BdDe3g4AWIjN5PyZmkAT3KoXbtWLxmA7agL5GdLCUXOutrbiEyrTicZiUoruAc45pCORCHxur1Atzqd6ShbK+s0Mr/22wHU4gt2ykJ1ofEIkvBBWOjW1tQgnxf4eC5oqxEbs9/vBybUVxgoAsP4dhfqCenp6MBsKoUPgkpZzn/V8+vRpYWNu3boVADAXncr5Mwc2fQY1gSbUBJrw6V1fx4FN+WWVh6KTcLvdRSdUpqNpGpLJpDSfA8HM6JZdtjsajaaymkXhUd3OZkgT0W9Y/oatRPTTtMcRANNCV+IAKVuzoJomq8GKqyjbdjaqqqqxoIs1Wy0kSUi5j2AwCNY5tRmvGayAnULrXZ08eRIESBUOTQBqFAUnT54UNmZzczOCwSrMLo4JGzMbs5FxdNzXIdS0KrPRD2AKBpeiSM+QjsfjqXpIovCqHsSdrK0E4BcARmFG2f112uthAJeErsQBUmqXA8LBUNxSHVuVlZWIaOI0B4OBaJKFFAq0HeZm38uihxNHDAhWBwt2uB87cgSbQFJ/JQJhl2Hg9AcfIBKJCMkTICLs27sXVzuLLx2SC7qhYWZxDE/se1TouDJ7OdioCkk91AFWRdYse1BbsAVDYVOYtwdb0BZc3XfjUlQkEmKrP2QrvDcAYACA2P9yiQiHwyC3D050PjFUD+ZCYpOZ0gkEAogJPJnHdDMcTURceqrWVQRrSjhQhNDUWFgQan9/P/r6+/F5cySRy7qLfQDe1zScOHECTz31lJAxDzx4AKfeP4VIIoyAR05yps30wm3ohoYHH3xQ6Lh3+kcLHXYJqgNmJV3XoWYxbX9t9+cwbAmHP37kd7KO6VJUaEmxwiGbWemE9Rwmovm0R5iI5O18kpibmwMEho+tBrt8ZjKYJAKBAKIarxp4tTmow68a8KsGdtUksTm4ct5BTKPUuMVi25lpYW11EVAWFbS3tRf02bfffhsEc+OWTTtM09Lhw4eFjfnII48AAEbn+oSNuRKjoT64XC4cOHBA6Lh2xVoZRfdsFDILR8rEENgFzoZAqV7SosimOXzCepZ71HCIqelpaKpDwsEdwPzELRiGcSeEViA+nw/MgMaAe4Xr7Ld2RjEQNm2+//vB1cPc4jqlxi2W5uZmuN1uHQEhSAAAIABJREFUxMPOlCrJCR3gBU5F7uSDYRh469AhbAPBiRtBAeF+w8DJM2cwMzMjJFdg69ataGluwchcD7Y3fUTAKjPDzLgduokD+w8IL51hb9oyhQNBvnBQFEV4nhWDoQreZ3LpBKcQkZjmuyVmYmIC7JFT0mI57AlA1zWEQqHsby4AO6EvoYu5URIGLRm3GFRVxabNm0ChNaQ5hAHwncidfLh06RLGJiaw38GeCPthCiVR2gMR4dOf+TQm5gcQ1+Q5XGcj4whHZ/Hpz3xa+Nh2tKFMqzClzSMLVVWFF0LUDQOK4LyqrMKBmQ0AnUSUW0edNQozY3p6GobHmSQgWwiJjFdPJyUcBOUTJI2l4xbLzh07oc6ppWtBtgyaNXeUHTt25P3ZN954A14i7MnzczEsbXOajyW7CYQ2Irz5+uvC8mV+6Zd+CQYbGJoRm4GdzsD0NbhcLjz++OPCx04JB+Ej38EJ4eD1epHMo5d9LiSMpBCtP51c9ZBWAFeJ6J30kFahK5FMKBSClkw6qDnIFQ52KeSkIeZWsccRVfJj9+7dMOIGUETAFtcw2G09GhlcU8QmOQP4A/68k7IikQiOHjmCfczw5LktxYAlfYzzdXPuZ0Zffz96enry/GRmOjo6sH3bdvRPyTEE6IaGoZnreOyxx1BVVSV8fFtIriF9tCD8fj9iuliTa0xLCK/llq220n0w64H9+bIffQrAiNCVSGZ8fBwAwB5nwmds4TA5OSllfHsT1wRpDvY4ourv24XjaIrAlYVt6ryfQXPmVmA8Udwvqk6peOD+B/L2/xw/fhyxeLygcgA+LG1zmm+Z7/sBvEmEQ4cOFaTxZOKLz3wR3/ve9zCzOIa6CrGlLUZmexBLRvDFL35R6LjLka2Myu6aV1lZiUgiKrTWVUSLoa1K7P8z253yPQDhDKUz3gBQVJtQp5maMrND2SmzktsPkJKaVzS2cFirmsOWLVsQrAoCchSn/IgBPM8FRc+89fOfo44UbC5gWh+WtjnNV+kPgLCTGW8fPiws2/6pp56Cz+vDzYkLQsZL5+bkBbS2tOLgwYPCxwYgJbAjE7JqotnU1NRAM3Sh2sNCclF4Bdxsf+0tzHxXshsznwWwpZiJiaidiI4Q0XUiukpEf2i9XkdEh4mox3quLWYem+lpM6GbHSo8BiKQN5CaVzR3zEpixrM1B1HCQVEUPHzwYagTpfc70Jgp+B566KG8Pjc9PY3z58/jfpZXSykbHwEwFwrh/PnzQsarrKzEZz/3WQzN3EAsKa6G0OziOKbCI/hXX/1X0jZxe9OWebBnyBdCdpJoKC6mUJ7BBuZjC8Ir4Gb7K6x22CnWwKUB+GNm3g3gYwB+n4j2wOwb8Q4zdwB4B4L6SNg5Byyo+1IuGC6/tFwHWzhogjQHkdFKNo8++ig4yoC8dI+coFFCbV1t3qaZ48ePw2CGuM4K+bMDgJcIR44cETbmV77yFeiGht5JcdVfu8fPwufz43Of+5ywMZdjX5ui4/nTYYgzra6E3UxrJiqmX3govgCdjaI7OC4nm3A4Q0T/w/IXiehbKLJNKDOPMvN56+swgOswy+R/CcDz1tuehyDzVTgcBqlu6U1+0tFVD+YkhbLaF7DoaCWRN8ajjz4KRVVAwyV0IWqAMqbg8U8+nrd99/jx42gkBc0ldIG6LNPSe8eOCYui2bJlCx555BH0TV6ELiBqJppYwNBsF55++vNCanOthH1t6hKFg85iD0iZsHu0T0bEnJqmouY4osujZxMOfwTgd4joKBH9tfU4BuB3AfyhqEUQ0RYABwB8AKCZmUcBU4BAUNOtSCQC5FkJ0aioB6tusOqGHmyBUVGf36SKG4uLcsr/2mFrcUF5DvY4IiMeqqqq8NCDD0EdKZ1piUYJrDGeeOKJvD4XiUTQefEidnDpa4/vBDC/sICuLnG1kb72ta8hmljE4PT1osfqmTgPZgO/9mu/JmBlK2Mn1WkyhYPB0jo42jQ2NsLr8WI8IsbkPL5o+jU3bRKbbZCtn8M4M38cZrRSv/X4c2Z+lJmFlHgkokoA/wzgj5g555IcRPRtIjpLRGdziQiKx+N5aw2JzY/CCNTDCNQjtucLSGzOs8SUxMqs9gVsl70oFls4iD41PfXUU+AFBuT45bNCA4Ta+lrs359fvFFnZyc0XZdagTVX7DLeZ86cETbmwYMHsXXrVnRPnCsqOkfTE7g11YlPfvKTQstzZ8IWDrohTzgkDUN4ZvdyFEXB5s2bcHtBTLTG7YVJeD1ex81KAABmPsLMf2s93hU1ORG5YQqGF5j5v1svjxNRq/XzVqwQ78LMzzLzQWY+mCr0tgrmDeCseYCJ7jQYEoxdIC8qSHOIaAS32yXc3vr444/D5/eBbpXANBM1ndGf/+zn845AuXz5MhSYdY5KTQCEZlJwqbNT2JhEhK9//esIRSYxPj9Q8Dj901cRT8bwta99TdjaVsLj8cDj8SApSTjoBkM3DCk5Gsu5r6MDwwvjQsJmh8Nj2Lp1q/Aoq5J1+iXTAPwcgOvM/J/TfvRT3Gku9E0Ar4mYT1VVwGETgcw+0nZp7UhSnHCorBB/YvL7/fiVp34F6rAKOFxqifoIBMIXvvCFvD/b3dWFZqK8E99k0cYGuru6hMbgP/nkk6ipqUXPeGHuQ2bGzYnz2LVrVyqvRTbBykokcjhwBT0uuIjgIkKt142gJ3uZ9qQ1rhPCoaOjA+H4IubixdUvNdjAYHgMO3ftFLSyO5SyDfxjAH4LwGeI6KL1+DyA/wDgl4moB8AvW98Xjd/vB3S5BbXuQk8iEJBjv3S73Qj4fQgLEg4LCUJ1tdg4aZuvfOUrYJ1BfQ5utDqg3lLx0Y9+FBs3bsz74329vWhyotd4jjQDCIXDQqPfPB4PfvVXv4zRUB/CebQQtRkL3cJ8dAa//uu/LmxN2airq0NCzy4cdtcGEfS4EPS48EhzLXbXZneUxy3hUFsrJHp+VXbv3g0AuDVXXC7x+OI0oskYdu3aJWJZSyiZcGDmE8xMzPwAM++3Hm8w8zQzP8nMHdZz/ldtBmpra8HJGCDJzJMJRYuhXnDscTo1NdWYT4j5F4YE9Y/OxNatW3Hw4EGovWqqj7NsaIDAUS7I3KFpGqZnZyHvP5c/tti2M/1F8cwzz0BVXbg5nn9S3M2J86irrcOnPvUpoWtajfqGBiQkCe24JXRSzaok0tHRAY/bg5tzg0WN02t9XobmVkrNwVFsvwQl5HVnW46aXERDQ4O08evrGzGXEHMan0u6pK71G9/4BjjKoH4HtAcDULtVdOzoKKjhzOzsLJjZkfLcuWKvZWZGyFkpRX19PZ544lMYmLkGTU/k/LmF2BxGQ/145kvPSDOdZqKpqQlxXZJwsDJBc/FhFovb7caevXuKFg49swOoqa4uqBR9Nu4Z4WCHeSkxMYknWdHi4HhEeHhZOk3NzZhJFH9jGgzMROXeFA8++CD27N0DtUu+9kCDBA4zfvubv11Q7Ro7wsy5LS87dpiAjOi3L3/5y0hoMQzN5B4q2zd1CUQoyJ9TDM3NzYhrmpSIpaiuQ1UV4ZnGK3HgwAEMzo8ikiyshDozo2t2APsPHBDePAi4h4SDXcdfWXQmplJZNGOYt2/fLm2OlpYWTEXNzb0YQgmCZohPokmHiPCtf/Mt8KJk34MBqNdVbL9vOx577LGChpBdeK0YZKztgQf+//bOPDqOq0z0v6+6Jbkly/Ii27Ikb5Il25Jsy7K8J3bsOIuV1UmwY2cFgrNCgMcL8JjDgzOHmTfDecwcYFgyvBlgJgwEeDAJ8IAsJAxryOY1cbyvsq19l3q774+qkttSt9Td6u7qlu/vHB3V0nXrq+XWd5dvWUpp6WyOt+yL6vdBFeRkywHWrFkz6O2bKmwHsj5/4lsYff4AM6bPSHpsJZu6ujrzA996Iq7jL/S20NbXEXNYmGi5YpRDfn4+pbNnYyTItng0XN3m2LA98ZQMSkpKCAShuX9sj/F8r1kZYg1nHSv19fUsq12G610XJMk2QI4Jqlvx8O6H446RY/uQRD/IknxsWRIdsx9MxX3zzTfR3HWWrv7RJ7wvdJygz9vNTTfdlHBZRsM2LuhJhnIIBClNwvBMJKqrq8n1eDjYfCSu4w82HwVIXqDDpJSaptSvWEFW13lIcBamcLg7z1G+YEFSzeLsj3ljz9ge4znr+GSMW4YiIjz6yKOofoUcSkLvwWf2GmqX17J69eq4iykoKMAQoSuBoo0V2+AxWZOlW7ZsQUQ42XJw1N+ebDlI/sR81q6N0Sk0AdjvaE+CotTaKKXo8QWSOgw8FLfbTd2KFexvORpXj/BA82FKS0rissaLhitKOaxevRoV8OHqbEzuiXz9GF0XWLtmTVJPYw+VnekZWzf4bI8Lz4TEe1iGo6qqis2bN+M67IIERxaRdwTVr3js0cfGNAablZXF9MJCkhNPNz7saehkeSHPmDGD2mW1nGkb2ZfCH/BxruMo12y6JqUT0TYTJ05kypQp9PgS28DrDwTxB4PMnRtPcPb4Wbt2La197TF7Sw/4vRxqO8HqJH5jrijlUF9fzwSPB1frsaSex912AlQw6SZ+BQUFFE6bysmusSmHk11uysrKkzKpFY5HHnkEl7iQfQk8Xze4Dru44YYbEmLzXbFwIY0pyh8QDWeBGYWFSe2Jbtq8ic6+Fjr6Is/Lne88jj/gZdOmxOeIjpby8vKEDyt1+8yeSDw5xsfCGuvjvrfpvWH7SvOLKM0PPw/4butxfAF/3PNq0ZA+b38KyMnJ4ZqNG8luO5FUh7is5iOUlJQmLHvXSFQuXMSJ7vhDXgQVnOzOYmESnGgiUVRUxK6duzBOGQmLuWTsMcjOzubhhx9OSHnV1dU0B4N0Op2MAlAoThkG1Un2Qr7qqqsQEc62R05LerbtCBPzJsYcqyqRlJeX0+3zJzR0d5fXVA5lZWUJKzMapk+fTmVFBfuahyuHHYu3smNx+BDoe5sOkevxsHTp0qTJdkUpBzBN75Tfi7slOb0H6WvD6DrPLbfcnJKW+OLFiznXLfRE8JSemx9gbn7kVta5HoN+v2LhwsS734/EPffcw9RpU3HvcY89YusFkHPCA/c/kDBfDbtFN5bszbOAHOtvnrUeD+eBzmBwUKZkUVhYyKJFizjfEb5uBFWQ853HWLd+HW736OEokkVFRQWBoEro0FKnz8/MmTOTGnI8EuvWr+dY2xk6o0z+E1RB9jUfZuWqVUnNPXHFKYclS5Ywf34Z2RcPJCWlVNb5A2RlZdPQ0JDwssNRXV0NwNHO8ENL9y3s476Fke2oD3eYlbympibxwo2Ax+PhicefQLWqsQXlC4L7bTdFs4oSGsahrKyMopkz2TeG2EoNCLMwlcIHERriLGsfZiTPZCsHMMfAW7rPMxAmS1xbz3kGfH0pkWMk7IZMpzdxvf9ufzApISiiYf369SgU+5uja4qc6myko7+Lq6++OqlyXXHKQUTYvv19SE8rro6xxTUZhq+P7OYjXH/9dQnP5xqJqqoqDMPgUHt8LblDbW4mF0xKuhlrOK699lqWLFmC64ArbrtROSqoTsVHPvyRhLaiRIQbt27lGIp2B4eWAij2GAarV69OScyfVatWAYqLXcM9dy90nkREkmY6GS2zZ8/G4/HQ4U2MxZI3EKTH66Oqqioh5cVKZWUl0wuns+didE6Iey4ewhBjTBZ50XDFKQeA6667jqnTppHdmLgQyABZjftBBdi1a1dCyx2J3NxcKisW8E5b7JYjSsG7HTksq02Oh+VoiAhPPvkkDJiWRjEzAK6DLurr65MyMdfQ0ICI8FrCS46edzCHlFLliVxZWUlubl7YMN4Xu05RXl6esoZPJAzDYPHixXT4EqMcOqweSDJ9kkZCRFh/1XoOth7DF8Vc6J6mQyxduoSCgoKkynVFKofs7Gzu2bULo7MRo/NcYgr19ZPTdJBrrtmUdH+BodStqOdop5v+GIdgL/YZNPcRV/yhRFFZWUlDQwOuIy6IMd+6HBTEL3z4wx9OinIrKiri6quv5nUx6Heg96BQ/E6E4qIi1q1bl5Jzut1uli1dSnP3mcu2B4IBWrrPsXz58pTIMRo1NTV0DfjwJyCQZtuAD5dhODasBObQktfvHdVbuqWvnbNdF1iXRCslmytSOYAZjXLK1GnknHkzIXMPWY17IeDn/e9/cOzCxciKFSsIBOHdttiGlva3ugePd5KHHnqI7OxsjL0xvI5dYBwzuPnmm5NqfnjvfffRp4L8KWlniMxh4KxS3Hv//SkL6QCwZOkSOvtayZ8wlcm5ZniM9t4LBIL+lOVtGI0lS5agICFDS+1eP+ULFiTF+zxaamtrmZAzgb1NIw8t7bNMXlPRWLhilUNOTg7vf/ABjK7zuDrOjH7ACIi3l5yLB9myZQvz5s1LjIAxsHTpUrKzstjfEtvQ0v6WLGZML0x5T2co06ZNY9fOXchZueTtZaEmK9Tk4cpb9gs52Tl84AMfSKpsCxcuZN3atfxehN4U9h6CKF4UoWjGDG644YaUnRcuGTmUTF7A8jmbAWjpbrxsn9PU1NQgIrT1jy3ISVApOr0+R01zwfwe1a+sZ3/LkRGdEPc1HaakuCQlntxXrHIAuOmmm5hZVETOmdfH1HvIOvsWgkr6hyoSOTk5LKtdxr626PM/+4Owvz2HVavXODLfMJQdO3aQPykf1/7LW8iqVqFqhzybNjDOGOy8e2dKImjufvhhvMCrST/TJfYCjUrxoYcfTrkncmVlJSJCa++lNPFtveeZOmVqSsJZR0NeXh4VCxbQOjA2i6WOAR+BoGLZsmUJkix+Vq9eTUtvO409TWH3ewM+3ms7wZq1qbEWS1vlICI3isghETkiIp9KxjmysrL40EMPIT0tuOL0e5D+DrKaDnHrLbckLcZJNKxevYaz3UJzX3SP9EiHmz6fSrrFQ7Tk5uZy7z33wgUYLW6FcdDAk+tJWQaysrIytjY08CegKQW9hwEULxgGlRUVXHvttUk/31Dy8vIoLi6hvedSYqH2votJSUU5FpbX1dHp8xMYQ8OuZcCHiDjecwAG66IdUG8oR9pO4g34LIuy5JOWykFEXMA/AVuBKmCniCTFzmzLli3Mn1/GhHNvxJUlLvvMm2RnZ/HAAw+M/uMkYr9Ye1qim3fY0+LGMAzH5xtCuf3225mYPxHjnRFey07T4W3H9h2DebRTwe7du/F4PPwCQSVZQbyKaaH05Ec/Gndk2bFSWVlBR7/pvh4I+unsa2XBggWOyBKJ5cuXEwgq2sfQe2gb8FFeXu6I89tQioqKKC0p5Z0IDdV3Wo7hdrlTpsjSUjkAq4AjSqljSikv8H3gtmScyDAMHnnkYejrxB1mMiiYN41gXvhImEZPC+6Wo+zYvj0lqQVHYs6cORTNnMHbzdENQexpyWFJTU1KP7Cj4fF4uOvOu5BGIVJIVHlPyMrK4o477kipbFOmTOGh3bs5guJAEs9zEcUfRLjxxhsdnfydP38+3f0d+AM+uvrbUCqY8rhDo7Fs2TIMw6A1znkHW7GkUwOpfmU9h9tPEggTOfrdtuNUV1cPhpRPNumqHEqA0yHrZ6xtg4jIbhF5XUReb2oKP0YXLWvWrKGqqooJjW9D8HLrB+/ctXjnhg9NnHX2DXLz8rj77rvHdP5EICKsWbuOg205+EbpALX2C6e6DNY4EHJ5NLZt24bL5UKOhpkH8YLrtIsbb7zREVv72267jQXl5fzCiN601faQjgaF4nkET24ujz32WNxyJgIzOqmiq7+Vrn5znM8JY4uRyMvLY+HChRHnHfKz3eRnR+5Jt3t9BJVy1JR7KHV1dQz4vZwcYmLf6+vjdMd56lakTtZ0VQ7hZkgvq41KqaeVUvVKqfqxTpKJCLt370YN9OCO0kvR6G7C3XaKXTt3pkWXFMzQBwMBNapJ6z7LqsnpMAjhmDJlChs3bsR1ang6UTklKL/i1ltvdUQ2t9vNf3/qKbqV4sUoj2mIIWzGW8AJFI89/rjjjma2BVv3QNtgAiAnvOhHY+XKlXR4/fjCDAkvnpLP4imR62ZLvxeXy5UWk9E2tiyH2y53QjzafhpFaifO01U5nAFC7StLgQR5q4Vn+fLlLFmylAnn90aVDCjr3FvkTZzInXfemUyxYqK2tpYst4u9o5i07mnJonDa1JRHoIyWhoYG1ICCIWk3jFMG88vmpzxIYCiLFy/mjjvu4DXgTALnHnpQ/MowqKmuTllcrpGwjSu6+9vpHmhn6tRpjvoBRKK+vh6lFG39sc87tA6YITNyc3OTIFl8TJkyhdKSEo62nb5s+9H20xiGkdIQH+mqHP4CVIjIfBHJBu4GnkvmCUWEBx98wOw9jBIAS3pbcbedYsf27eTl5SVTrJjweDwsXVbL3tbIJq2BIBxoSx8T1nCsWLGCSQWTkDMh8vUCLXD9ddc7JpfNQw89xLSpU3lOhECCFMT/A7wiPPXJTzo2CR2Kx+OhYFIBPd4OegY6BnM3pxtVVVXkZGfTEuO8gzcQpGMgdZY/sVBdU8PxrrOX+Tscaz/DgvLylCpo59/CMCil/MATwK8ww8s8q5RK5jwgYLZCKioqyTm/f0S/h6zGfWTn5LBt27ZkixQzq1at4my30NIf/sN/vMtFj0+lZaWwcblcbLh6A67zLrBGC+SceT0bNmxwUDKTvLw8nvzYx2hUKiGe08dQ7AF27tqVVuP6RUVF9A500ufrYtas8ElnnCY7O5tltbW0xugp3TpgKpN0mm+wWbx4MZ393bT1dwBmiO5TXY0sTnFgwLRUDgBKqV8opSqVUuVKqS+k4pwiwo4d26GvPbLXtK+P7NZjNGzdmvTAV/GwcuVKAA60hh9a2teShYikZaUIZfXq1SifGvR5kPNC0awix725bTZs2MDaNWt4WYSOMfQe/Ch+Jgazioq4//77Eyjh2JkxcwZ9/m56vV1p4/wWjpUrV9Lt9dEfQ3a4ln4vngkTHAu2NxL2sOmpLtMJsbm3jT5ff8qHU9NWOTjFpk2bKJg8GffFd8Puz2p6DxUMpNyUMlrKysoomJTPwdbwk9IH27JYUF7m+ITnaNTV1SEiSJOAAqPFYGX9SqfFGkREePKjHwW3m1+OoZw/Ak0qyEc/9jFycqL3cE8F06ZNo6O3mWAw4Lip9kjYIcRjGVpqG/CzvK7O0aRFkSgrK0NEON1pKoczXaYzYqr9TLRyGEJWVhYNW7fibj+FeIckPFGK7ObD1NQsSavufyiGYVC7vI53O3KGjYx5A6Zn9PK69LHrjkR+fj5z5s5BmgU6QXlVUlMixkNxcTH33Hsv+zGtjGKlC8WrIqxdu5a1aWhWHBqaJBVhSuJl/vz5FEyaFLVy6PMH6PH5B3vZ6YbH42FW0Swauy8CcLb7IiKS8m+OVg5h2Lp1KyiFq/VyT0Wjpxn62mloCJ/XNV2ora2luQ+a+y9/vMc63fiCpEWogGiorqrG1eFC2sz5BidDKkdi586dTC8s5BciBGNUEC8CAcPgiSeeSI5wYyQ0uVA69zQNw2BFfT1t3sCIQetsbCWSTs5vQ5k3fx6NvaaHemNPE0Uzi1JuLaaVQxjmzZtHWVk5Wa3HL9vuaj2Gy+Vi48aNDkkWHXYL+70h2eHs9XRrgUeivLycYH8QLpo9unS0s58wYQIPP/IIjUqxL4bjLqB4C7jjzjvTZh5lKJMmTRpcTsf5tVBWrFhBv99PTxTzDq39XqZMnmw5+qUnc+bMoam3laAKcrG3hbnzUi+rVg4R2LhxA0bXBfBdyr+c3X6a5cvr0sbpLRJlZWXkeiZwuOPyCKeHO1zMmV16WaVPZ+zKK+eEktKSlOY0iIUtW7awoLyclw0jatPWlzCHD+67777kCjcGQt/zdH9nbAOL0UJpKKVo8wVYUV+ftqbcYPqZ+AJ+2vs7aeprcySop1YOEbDHgO0809LfBX3trFuXfmPDQ3G5XCxctIhjnZdyKisFx7pyqKqucVCy2LBt68UnzC5Nz9Y1mMMaH9q9m9ZgkGgSzzaieAe4e+fOtG6Rh8bdSid/nnAUFxdTOG0abaME4ev1B+j3+dN+aLW4uBiAE53n6PcNOOJnopVDBCoqKsjLm4jLinFi/3c6uXq0LFq0mJPdBn7LT6B1QOgYUI56F8fKjBkzwi6nI2vWrKFiwQJ+axijzj28CuR5PGnlXR+OUM/hVAV7ixcRYXldHW1e/4jzDnYcpnRXDjNnzgQY9JS211OJVg4RMGOuLCWrx7QYMLovMDE/P63HKUOprKwkEISzPeZQzIku9+D2TCEnJ4esbNNfI51NKcH8ON1z7720BIOEN4I2aUNxELht27a0H54MVQ7pOqQXyrJlyxjwB+gdYd6hrd9LQUFB2s7z2Nh+Jcctfysn/Ey0chiBqqoq6G0Hv5esniZqqqvTepwylPLycgBOd5uV+oz1396eKYgVtC7UciZd2bBhAzMKp/PnEQLt/RkQw0hbP5lQ0s3vYjRsQ4uRhpY6fAFqa2vTvh57PB5yPbmc6jQDjBUWFqZcBq0cRqCiogIAo6cJ+toH1zOB0tJSstyuQaVwutvFzBnT0yrIWCyk+4QomFFbb739No6haAkztORH8bZhcNVVV6X9MBmQloH2RmLOnDlMnDgxYvKffn+AXp/f0TwZsTBlyhR8VgoBJxpHWjmMgB211N16ApRK2yim4XC73RQXF9PYaz7i831u5s5Lr2Qt0WA7X6X7hKhNQ0MDhghvh9n3HtATDHLzzTenWqy4SEfv4ZEwDIMlNTV0+MIPK7V7TaVRXV2dSrHixlYIuZ7clOcRB60cRmT69OlkZWfjajcnhdLRzn4k5sydx/m+LJSCxl5X2o+zhuNTn/oUO3fuzJgKXVhYyPK6OvYZxrB0ovuAyZMmZYxRQ7oPvYSjqrqabq8vbH6HjgE/LpcrY0YAJhWYvWWnLNq0chgBwzCd0g2GAAARNklEQVSYObMIw9sN4Iit8VgoKSnhYp/Q4RUG/CrjlBuY9uuPPvpoRo1/b9q0iZZgkAsh23wo3hNhwzXXZFSLvKBgcsYoZmAwkF5nmCitHV4fCxYsIDs7e9i+dMQ2WMjPdyaVb+a8pQ5RPKuIM6dPkTNhQlrlW46GWbNm4bPiKYEZglmTfNatWwfAIcC+4ycAr1KsX7/eIani49lnf5ARlko2tjVep9fHtAmhfj6Kbn+AjWkYhTUS9vdmokNWbbrnMAr2mHe6m1KGw7aNfk8rh5RSWFhIeVkZR0Oslo5ijuEvX77cOcHiwOPxZExLG8wYUNOnFw7rOfT6A/gCwYwy5a6vr2fO7DmDjY1U44hyEJEvisi7IrJXRH4iIpND9n1aRI6IyCERucEJ+UKxJ4WmZoAp5VBs87ejVhgNJ8zhrlRW1NdzWkwLJYATIlRXV2ecBVAmUlm5kG7/5XMOXT5TWWTKfAPA+vXr+fdn/p3t27c7cn6neg4vADVKqaWYRhyfBhCRKsyUoNXAjcDXRMTRPq097pcp1jKh2L2dE11ustzujDAHHS/U1NTgV4pGwIuiUaVfyPHxyoIFC+jx+giEeEp3e/2OhL3OZByZc1BK/Tpk9U/AXdbybcD3lVIDwHEROQKswsyJ4gibN2/m4sWLbN682SkR4mby5MmICAMBmD5tUkZan2Qq9sToOWs9SHqGHB+PzJ8/HwX0+PxMsjzsu3wBiouLM8qwwWnSYUL6A8APrOUSuCwt7xlrm2MUFxfz8Y9/3EkR4sblcjF5Uj5tHZ1MzcA5k0xmxowZ5Oflcb6nZ3DmIdWZvK5U7N5Bty8wqBx6A0Fq52een4+TJE05iMiLXDLWCOUzSqn/tH7zGcAPPGMfFub3YaNoichuYDeYnpGa8Hz2c5/n8OHDekgjxYgI88rKaNq3DzcwISdHGwSkiNLSUkSEXmueIagUPT5/xsRFSxeSphyUUltG2i8iDwA3A9eqS2EUzwChnlqlXOqZDy3/aeBpgPr6+vgzvI9zVqxYkdYZr8Yzc+bM4ZUDB8gOBgc/WJrkk52dzcwZM+jpagfMtKBKqYx0AnUSp6yVbgQ+CdyqlApN1PwccLeI5IjIfKACeM0JGTWasVJcXExPMEiTCCUZ6ICYyZTOnk1fwLRYsqO0ZqITqJM4Za30VSAfeEFE3haRbwAopQ4AzwIHgV8CjyulRs/7p9GkIbafSbtSGRFobzxRUlIyqBz6LOVgJ9DRRIdT1koRZ+aUUl8AvpBCcTSapBDqV6J9TFJLUVERXn8AfzBInz+I2+0edGjVREc6WCtpNOOS6upqbr/9dgYGBti4caPT4lxR2JP//f4g/YEAM6ZPxzB0QIhY0MpBo0kSOTk5GWsGnenYmdP6AwEGAkHmOpBmM9PRqlSj0Yw77GG8/kCQAeVMms1MRysHjUYz7rBDx3gDQQb8gYwMnOk0WjloNJpxR05ODh6Phx5/gEAwqCej40ArB41GMy6ZXFBAt+UlPXny5FF+rRmKVg4ajWZcMmXKFHqsfNJOpdrMZLRy0Gg045KCyZMHw3Zr5RA7WjloNJpxSX5Ies18h1JtZjJaOWg0mnFJaM73TMv/ng5o5aDRaMYlodkbc3NzHZQkM9HKQaPRjEtCFYLOABc7WjloNJpxiR0JVzvAxYeOraTRaMYlW7ZsYdGiRdrHIU60ctBoNOMSEdHZ38aAHlbSaDQazTAcVQ4i8gkRUSJSaK2LiHxZRI6IyF4RqXNSPo1Go7lScUw5iMhs4DrgVMjmrZh5oyuA3cDXHRBNo9Fornic7Dn8A/AUoEK23QZ8V5n8CZgsIrMckU6j0WiuYBxRDiJyK3BWKbVnyK4S4HTI+hlrW7gydovI6yLyelNTU5Ik1Wg0miuTpFkriciLQFGYXZ8B/gdwfbjDwmxTYbahlHoaeBqgvr4+7G80Go1GEx9JUw5KqS3htovIEmA+sEdEAEqBN0VkFWZPIdT2rBQ4lywZNRqNRhMeUcrZRreInADqlVLNInIT8ATQAKwGvqyUWhVFGU3AySSKWQg0J7H8ZKPld5ZMlj+TZQct/2jMVUqFTbCdbk5wv8BUDEeAXuD90RwU6eIShYi8rpSqT+Y5komW31kyWf5Mlh20/GPBceWglJoXsqyAx52TRqPRaDSgPaQ1Go1GEwatHKLjaacFGCNafmfJZPkzWXbQ8seN4xPSGo1Go0k/dM9Bo9FoNMPQykGj0Wg0wxi3ykFEikTk+yJyVEQOisgvRKQyRec+YUeajfL326zotIsi7P+2iNyVOAlBRK4RkXWJLDOKc454nSG/e1BEikPWvyUiVcmXcESZuoesPygiX3VKnlgQkYCIvC0iB0Rkj4h8XETSqu6HyLhfRJ4XkYzO0CMi06zreVtEzovIWWu5XUQORlnGIyJyv7U8+A0QkVdEJOnmrWn1giQKMV2vfwK8opQqV0pVYYbsmOmsZBHZCfwOuDuF57wGiEk5iIhrjOeM9jofBAaVg1LqIaVUVBUqXRER90jr0R4XJ31KqVqlVDVmJOQG4H8m6VzxYstYA7SS4SbtSqkW63pqgW8A/2At1wLB0Y4XEbdS6htKqe+OVZZ46+24VA7AJsCnlPqGvUEp9TbwOxH5otU62SciO2CwFf2qiDwrIu+JyP8SkXtE5DXrd+XW76aLyI9F5C/W33pr+zQR+bWIvCUi38SKESUify0iT9oyiMgXROQjoYKKyERgPfBBrI+mldfiq1aP5+fADGv7VhF5NuTYa0TkeWv5ehH5o4i8KSI/tMq1ezGft7bvE5FFIjIPeAT4mNWauXpo78RuKVvn+I2IfA/YZ22717o3b4vIN6N5+cJdp7X9KUuuPdZ9vwuoB56xyveEtpREZKf1+/0i8neh8lr3d4+I/ElEUtYQEJG5IvKSmDlIXhKROdb2b4vIl0TkN8DficjnRORpEfk18F0RmSAi/2pdz1sissk67kHrGT4P/DqRsiqlLmKGw3/Ces8uO5eITLSuwX5fbrNkmici74rZi9svIs+IyBYR+b2IHBYz/A0iskpE/mBdzx9EZGEcYv4RK+CmJeNY6uwtIvJnS54X7ffCehb/Yr1bxySkXorI/daz3CMi/2ZtC1v348QlIv8sZk/u1yLisc7xioj8jYi8CjxpyfiJkQqSkev9Z0Xkd8D74pJSKTXu/oCPYGrqodvvBF4AXJi9iFPALMxWdLu1nAOcBT5vHfMk8I/W8veAq6zlOcA71vKXgc9ayzdhBgssBOYBb1rbDeAoMG2ITPcC/8da/gNQB9wRImexJdtdmE6Lp4A86/dft44vBH4bsv2TIfKcAD5sLT8GfMta/hzwiRA5vg3cFbLebf2/BugB5lvri4HngSxr/WvA/VE8k3DXudVazrW2T7X+v4IZUoXQdetenAKmW/fiZeB26zcKuMVa/nvgrxL8TgWAt0P+TgFftfY9DzxgLX8A+GnIPf0Z4Aq5528AHmv9vwH/ai0vssqcgNlzOmPfjwTI3h1mWxtmHbjsXNZ9nWQtF2JGKxDMd9kPLMF8l98A/sXad1vINU8C3NbyFuDHsciI+c7/ELgxQXV2CpesMh8C/nfIs/iDdWwh0AJkAdXAIaBwyDsZtu5HeW2fw6prIfex1lp/Frg35D3/WoTjvo1VP7lUH0ar90+N5b1x3EM6xVwF/IdSKgBcsDT0SqAT+ItSqhFARI5yqcW2D7MnAubLXiUyGDx2kojkAxswP+gopX4uIm3W8gkRaRGR5Zgv9ltKqZYhMu0E/tFa/r61nhUi5zkRedkqzy8ivwRuEZEfYSqip4CNQBXwe0u2bMzWl83/tf6/YcsZI68ppY5by9cCK4C/WOfyABejKCPcdRqYH8de6/paRyljJeZQYROAiDyDee9/CngxP8RgXud1UcgUC33KHBbAOveDmBUUYC2X7uu/YSonmx9az9HmOaVUn7V8FfAVAKXUuyJyErDnxV6I4n6MhdAIyKHnEuBvRGQD5vBHCZeGY48rpeze4wHgJaWUEpF9mB89gALgOyJSgamws6KUxyMib1vlvIGpEGDsdbYU+IGYeWGyAfs9Bvi5UmoAGBCRi9Z1bgZ+pJRqhsveybB1XynVFeX1hXJcmSMZWNc6L2TfD2IoZw0j1/tYyhrGeFUOBzBb2kMJFxLcZiBkORiyHuTSfTKAtSGV2yzUfDCRHEa+hdk6K8JsaYUeNw3zZawREYXZOlKY8yWRyvsB5nhsK2bl6BJTgBeUUjtHubYAkZ+537o+e84mO2RfT6jYwHeUUp+OUM4wRrjOHxP5OsMWNcI+n7KaTIx8nakg9Jp6huwbei8jMfS4hCEiZZj3yFbqoee6B7NntkIp5RMzMOYEa180deSvgd8opbaJOXz5SpRi9SmlakWkAFPJP47ZIx9rnf0K8CWl1HMicg1mazzc8fY7I4R/J8PW/TgZel5PyHosz320ej+md2i8zjm8DOSIyIfsDSKyErMrvUNEXCIyHbPV+VoM5f4aM2qsXabdkvwtZqVCRLZidmVtfgLciNna+dWQ8u7CzHw3Vyk1Tyk1G7Nl0wrcbck5i0utIDArWx3wIS61DP4ErBeRBZYMuTK6ZVYXkB+yfgKzRwDmMEGkFt9LwF0iYs+DTBWRuaOca6Tr/ICI5NplRZDN5s/ARhEpFHOeYyfw6ijnTgV/4NI8yj2Yk+7REPreVGIOVxxKuHQhWO/9NzCHxMJ9BAuAi5Zi2ASM9mzDHX/WWn4wVvmUUh2Yw8KfEJEszHs0ljobKs8DUfz+JWC71aAJfScj1X0niafeR824VA7WS78NuE5MU9YDmC2G7wF7gT2YCuQppdT5GIr+CFBvTVYdxJzUBfg8sEFE3sRMYjSYF1sp5QV+Azw7ZHgBzI/bT4Zs+zFmL+MwZvf464R8AK0yfoY5Xv8za1sTZkX8DxHZi/nSjGguijlOvk2sCWngnzE/vK9hhksP2+pQptXQX2FOXu7F7P6Plso10nUWA88Br1tDCvbk27eBb1iyDbaqrCGET2Pezz2Y8zn/Ocq5U8FHgPdb9+M+zDHvaPga5uTkPkxF/6A1zJFoPNa9PAC8iPmh+3yE3z6D+Y6/jqm43o3xXH8P/K2I/B6zhxgzSqm3MJ/v3ZjvzVjq7OeAH4rIfxFF6Gul1AHgC8CrIrIH+JK1K1Ldd4w4633U6PAZSUZMe/I3gfcppQ47LY9Go9FEw7jsOaQLYjpuHcGcuNOKQaPRZAy656DRaDSaYeieg0aj0WiGoZWDRqPRaIahlYNGo9FohqGVg0YTJSIyU0S+J2YsnjesmDbbnJZLo0kGWjloNFFgeY3/FPitUqpMKbUC0w6/NAFljzXarUaTcLRy0GiiYzPgVZdH+j2plPqK5b37RTGjde4VkYdhMHLoKyLyIzEjmj5jKZlhUTNFpFxEfmn1SP5LRsl5odEkm/EaW0mjSTTVmM6M4fgg0KGUWikiOZiB0OwgcMutY88Bv8cMW26H1+hXSl0FICIvAY8opQ6LyGpM7+nNybkUjWZ0tHLQaOJARP4JM2KoFzgJLJVL+TAKgApr32tKqTPWMXbUUVs5/MDaPhEz8dIPQ6J+5iT/KjSayGjloNFExwHM3AIAKKUeFzMV7OuYsbQ+rJS6LLCiFQU0XORPGzt+lQG0h4YE12icRs85aDTR8TIwQUQeDdmWa/3/FfCoFUUUEakUkbxoC1ZKdQLHReR91vEiIssSJLdGExdaOWg0UWBF+r0dM3LtcSt67Xcws299CzgIvCki+4FvEnuv/B7gg1Yk0AOYYdM1GsfQsZU0Go1GMwzdc9BoNBrNMLRy0Gg0Gs0wtHLQaDQazTC0ctBoNBrNMLRy0Gg0Gs0wtHLQaDQazTC0ctBoNBrNMP4/XitfDBQ9ZnoAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "z = sns.violinplot(data = movies, x='Genre',y='CriticRatings')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "w = sns.boxplot(data = movies, x='Genre',y='CriticRatings')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x1512 with 35 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "g = sns.FacetGrid(movies, row ='Genre', col='YearOfRelease',hue ='Genre')\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "metadata": {},
   "outputs": [
    {
     "ename": "ValueError",
     "evalue": "Axes instance argument was not found in a figure",
     "output_type": "error",
     "traceback": [
      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[1;31mValueError\u001b[0m                                Traceback (most recent call last)",
      "\u001b[1;32m<ipython-input-62-0b5973f5451a>\u001b[0m in \u001b[0;36m<module>\u001b[1;34m\u001b[0m\n\u001b[1;32m----> 1\u001b[1;33m \u001b[0mg\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mg\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mmap\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mplt\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mscatter\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;34m'CriticRatings'\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;34m'AudienceRatings'\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m",
      "\u001b[1;32m~\\Anaconda3\\lib\\site-packages\\seaborn\\axisgrid.py\u001b[0m in \u001b[0;36mmap\u001b[1;34m(self, func, *args, **kwargs)\u001b[0m\n\u001b[0;32m    741\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    742\u001b[0m             \u001b[1;31m# Get the current axis\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 743\u001b[1;33m             \u001b[0max\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mfacet_axis\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mrow_i\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mcol_j\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m    744\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    745\u001b[0m             \u001b[1;31m# Decide what color to plot with\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32m~\\Anaconda3\\lib\\site-packages\\seaborn\\axisgrid.py\u001b[0m in \u001b[0;36mfacet_axis\u001b[1;34m(self, row_i, col_j)\u001b[0m\n\u001b[0;32m    871\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    872\u001b[0m         \u001b[1;31m# Get a reference to the axes object we want, and make it active\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 873\u001b[1;33m         \u001b[0mplt\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0msca\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0max\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m    874\u001b[0m         \u001b[1;32mreturn\u001b[0m \u001b[0max\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    875\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32m~\\Anaconda3\\lib\\site-packages\\matplotlib\\pyplot.py\u001b[0m in \u001b[0;36msca\u001b[1;34m(ax)\u001b[0m\n\u001b[0;32m    903\u001b[0m             \u001b[0mm\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mcanvas\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mfigure\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0msca\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0max\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    904\u001b[0m             \u001b[1;32mreturn\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 905\u001b[1;33m     \u001b[1;32mraise\u001b[0m \u001b[0mValueError\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;34m\"Axes instance argument was not found in a figure\"\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m    906\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    907\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;31mValueError\u001b[0m: Axes instance argument was not found in a figure"
     ]
    }
   ],
   "source": [
    "g = g.map(plt.scatter, 'CriticRatings', 'AudienceRatings')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "sns.FacetGrid"
   ]
  }
 ],
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