zoomInOutandEmbeddedSubplot.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "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>gender</th>\n",
       "      <th>race/ethnicity</th>\n",
       "      <th>parental level of education</th>\n",
       "      <th>lunch</th>\n",
       "      <th>test preparation course</th>\n",
       "      <th>math score</th>\n",
       "      <th>reading score</th>\n",
       "      <th>writing score</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>female</td>\n",
       "      <td>group B</td>\n",
       "      <td>bachelor's degree</td>\n",
       "      <td>standard</td>\n",
       "      <td>none</td>\n",
       "      <td>72</td>\n",
       "      <td>72</td>\n",
       "      <td>74</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>female</td>\n",
       "      <td>group C</td>\n",
       "      <td>some college</td>\n",
       "      <td>standard</td>\n",
       "      <td>completed</td>\n",
       "      <td>69</td>\n",
       "      <td>90</td>\n",
       "      <td>88</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>female</td>\n",
       "      <td>group B</td>\n",
       "      <td>master's degree</td>\n",
       "      <td>standard</td>\n",
       "      <td>none</td>\n",
       "      <td>90</td>\n",
       "      <td>95</td>\n",
       "      <td>93</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>male</td>\n",
       "      <td>group A</td>\n",
       "      <td>associate's degree</td>\n",
       "      <td>free/reduced</td>\n",
       "      <td>none</td>\n",
       "      <td>47</td>\n",
       "      <td>57</td>\n",
       "      <td>44</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>male</td>\n",
       "      <td>group C</td>\n",
       "      <td>some college</td>\n",
       "      <td>standard</td>\n",
       "      <td>none</td>\n",
       "      <td>76</td>\n",
       "      <td>78</td>\n",
       "      <td>75</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   gender race/ethnicity parental level of education         lunch  \\\n",
       "0  female        group B           bachelor's degree      standard   \n",
       "1  female        group C                some college      standard   \n",
       "2  female        group B             master's degree      standard   \n",
       "3    male        group A          associate's degree  free/reduced   \n",
       "4    male        group C                some college      standard   \n",
       "\n",
       "  test preparation course  math score  reading score  writing score  \n",
       "0                    none          72             72             74  \n",
       "1               completed          69             90             88  \n",
       "2                    none          90             95             93  \n",
       "3                    none          47             57             44  \n",
       "4                    none          76             78             75  "
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = pd.read_csv(\"StudentsPerformance.csv\")\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "pe = df['parental level of education']\n",
    "math = df['math score']\n",
    "gender = df['gender']\n",
    "writing = df['writing score']\n",
    "lunch = df['lunch']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<BarContainer object of 1000 artists>"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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9T4f2k4C2MtaewCckbQt8FGgFxgAfBzqet8L2fsAvgbOAg2zvAcwFPi9pfeA7wETb44FpwDcafUMlnSxprqS5K5e3NeoSERE90BcfpbTU9iIASUuAO2xb0iJqoQEwEri27PQMrF/aZwP/KumdwE22fyup4/gHlz8LyvMR1ELxj8AfbN/XoKZFwMWSLgRutX1P/UFJI4FNbM8qTT8EPlQ3327tu7xS+2hqwX6D7VXAc5Lu7DDnT8vXvYGdgV+XtbytrHMHYFfg9tI+BHi2Qe3YngpMBRjWMtqN+kRExJrrixB8o+7xqrrnq+rm+xpwp+2PSGoF7gKw/SNJ9wOHATMkfRx4osP4As63fcXfNdbGeb1RQbYflzQeOBQ4X9JM2+d1GLOzcBHwGdszOszX3Qdktdci4HbbH+tw/hhgSYOdZ0RErCPNevHISODp8vj49kZJ2wFP2P42cAu1S6qvAhvXnTsDOLHuvtooSVt2NZmkrYHltq8DLgb2qD9u+2WgTdJ+pemYDvOdWi5fIum9kjYC7gWOLPcGtwIO6GT6+4B9JW1fzh8u6b3AY8AWkvYp7etL2qWrdURERO9q1ifL/xu1y6GfB35V1z4JOFbSm8BzwHm2/1ReWLMY+K9yX3AnYHa5jPgacCywsov5xgAXSVoFvAmc2qDPCcA0ScupBV+7q6hdxp2v2oQvAEcANwIHAouBx4H7gbfcsLP9gqTjgR9LGlaazyq704nAt8vl2KHAJcCSLtYRERG9SHZuMfWUpBG2X5O0GfAAsK/t5/pyzmEto90y+ZK+nCIiolctu6C7u0d9S9I82xMaHWvWTnCwuFXSJtRe7PK1vg7AiIjoXQnBtWD7gGbXEBERPdcvfqtKREREMyQEIyKishKCERFRWQnBiIiorIRgRERUVkIwIiIqK2+RGGDGjBrJ3Ca/8TQiYrDITjAiIiorIRgREZWVEIyIiMpKCEZERGUlBCMiorISghERUVl5i8QAs+jpNlqnTG92GRER60xffh5hdoIREVFZCcGIiKishGBERFRWQjAiIiorIRgREZWVEIyIiMpKCEZERGUlBCMiorISghERUVkJwR6QdLyk75bH50g6o9k1RUTEmksIRkREZfWrEJS0kaTpkh6StFjSpNJ+oKQFkhZJmiZpWGlfJumbkmZLmitpD0kzJP1e0il1435R0hxJCyWd28nch0iaX+a+o7RtKunmct59knbrpv73SLpN0jxJ90jasa79vlLDeZJeW5PaIiKib/SrEAQOAZ6xPdb2rsBtkjYArgEm2R5D7Zd+n1p3zpO29wHuKf0mAnsD5wFIOhgYDewFjAPGS9q/flJJWwBXAkfaHgscVQ6dCyywvRvwZeAH3dQ/FfiM7fHAGcDlpf1S4FLbewLP1M3bbW2l38kl5OeuXN7WTQkREbG6+lsILgIOknShpPfbbgN2AJbafrz0uRaoD4pb6s693/artl8AVkjaBDi4/FkAzAd2pBY89fYG7ra9FMD2n0r7fsAPS9uvgM0kjWxUuKQRwPuAGyQ9CFwBtJTD+wA3lMc/qjttdWrD9lTbE2xPGDK84fQREdED/eqjlGw/Lmk8cChwvqSZ/C3kOvNG+bqq7nH786GAgPNtX9HFGALcSftbyuxkjPWAl22P67Lat47fXW0REdFH+tVOUNLWwHLb1wEXA3sAjwKtkrYv3Y4DZq3BsDOAE8tODUmjJG3Zoc9s4B8kbVv6bFra7waOKW0HAC/afqXRJKV9qaSjSn9JGlsO3wccWR4fvYa1RUREH+lXO0FgDHCRpFXAm8CptldIOoHaZcahwBzg+6s7oO2ZknYCZksCeA04Fni+rs8Lkk4GbpK0Xjn2j8A5wNWSFgLLgcndTHcM8D1JZwHrAz8BHgJOB66T9AVgOtC2urVFRETfkd3Z1b3oLZKGA3+2bUlHAx+zfXhPxhrWMtotky/p1foiIvqztf1keUnzbE9odKy/7QQHq/HAd1Xb7r0MnNjcciIiAhKC64Tte4Cx3XaMiIh1ql+9MCYiImJdSghGRERlJQQjIqKyEoIREVFZCcGIiKishGBERFRW3iIxwIwZNZK5a/nG0YiIqMlOMCIiKishGBERlZUQjIiIykoIRkREZSUEIyKishKCERFRWXmLxACz6Ok2WqdMb3YZERHrzNp+nmBXshOMiIjKSghGRERlJQQjIqKyEoIREVFZCcGIiKishGBERFRWQjAiIiorIRgREZWVEIyIiMpaoxCU1Cpp8dpOKukASbeu4TnXSJrYg3MOWJNz6s5dJmnznpwbEREDw6DdCUoa0uwaACTlV9NFRPRTPQnBoZKulbRQ0s8kDQeQdLakOZIWS5oqSaV9e0m/lPSQpPmS3lPGGVHOf1TS9XX9x0uaJWmepBmSWjoWIOlASQskLZI0TdKw0r6s1HEvcBTQBvylHLtA0sOl7osbjLmZpJll3CsA1R07VtIDkh6UdEV7wEo6SdLjku6SdKWk75b2ayT9u6Q7gQslvUfSbWVN90jasfTbQtKN5fs2R9K+Pfj7iIiIHupJCO4ATLW9G/AK8MnS/l3be9reFdgQ+HBpvx64zPZY4H3As6V9d+B0YGdgO2BfSesD3wEm2h4PTAO+UT+5pA2Aa4BJtsdQ+yXgp9Z1WWF7P9s/sf1Z27+RtCnwEWCXUvfXG6zrq8C9tncHbgHeVebbCZgE7Gt7HLASOEbS1sBXgL2BfwR27DDee4GDbH8BmAp8pqzpDODy0udS4Fu29wSOBK5qUBeSTpY0V9LclcvbGnWJiIge6Mmluidt/7o8vg44DbgY+J+SvgQMBzYFlki6Cxhl++cAtlcAlE3fA7afKs8fBFqBl4FdgdtLnyH8LTTb7QAstf14eX4t8CngkvL8pw1qfgVYAVwlaTrQ6H7k/sBHS53TJb1U2g8ExgNzSk0bAs8DewGzbP+prOEGasHX7gbbKyWNoBb+N5TzAYaVrwcBO9e1v13SxrZfrS/M9lRqQcqwltFuUHtERPRAT0Kw4w9hl93Z5cAE209KOgfYgLpLig28Ufd4ZalFwBLb+3RxXldjArz+loLtv0rai1qgHQ18GvhAg3MbBYyAa22f+XeN0kdWs471gJfLLrKj9YB9bP+5m7EiIqIP9ORy6LsktYfUx4B7qQUewItl5zMRwPYrwFOSjgCQNKz9HmInHgO2aB9f0vqSdunQ51GgVdL25flxwKyuCi41jbT9C2qXYMc16HY3cEzp/yHgHaX9DmCipC3LsU0lvRt4APgHSe8oL345stHc5XuwVNJR5XxJGlsOz6QWyO11NqorIiL6SE9C8BFgsqSF1C57fs/2y8CVwCLgZmBOXf/jgNNK/98A/6OzgW3/hVqAXijpIeBBapcS6/usAE6gdnlxEbAK+H43NW8M3FpqmAV8rkGfc4H9Jc0HDgb+WOZ7GDgLmFnOvx1osf008E3gfuCXwMPUXojTyDHASWVNS4DDS/tpwITyYp2HgVO6WUdERPQi2bnF1FOSRth+rewEfw5Ma7//2VeGtYx2y+RL+nKKiIh+ZW0/WV7SPNsTGh0btO8TXEfOKS/qWQwspbYLjoiIASJv5F4Lts9odg0REdFz2QlGRERlJQQjIqKyEoIREVFZCcGIiKishGBERFRWQjAiIiorb5EYYMaMGsnctXzjaERE1GQnGBERlZUQjIiIykoIRkREZSUEIyKishKCERFRWQnBiIiorIRgRERUVkIwIiIqKyEYERGVJdvNriHWgKRXgceaXUeTbA682Owimijrz/qruv61Xfu7bW/R6EB+bdrA85jtCc0uohkkza3q2iHrz/qru/6+XHsuh0ZERGUlBCMiorISggPP1GYX0ERVXjtk/Vl/dfXZ2vPCmIiIqKzsBCMiorISghERUVkJwQFC0iGSHpP0O0lTml1PX5O0jaQ7JT0iaYmkz5b2TSXdLum35es7ml1rX5E0RNICSbeW51Va+yaSfibp0fLfwD4VW//nyn/3iyX9WNIGg3n9kqZJel7S4rq2Ttcr6czys/AxSR9cm7kTggOApCHAZcCHgJ2Bj0naublV9bm/Al+wvROwN/CpsuYpwB22RwN3lOeD1WeBR+qeV2ntlwK32d4RGEvt+1CJ9UsaBZwGTLC9KzAEOJrBvf5rgEM6tDVcb/k5cDSwSznn8vIzskcSggPDXsDvbD9h+y/AT4DDm1xTn7L9rO355fGr1H4IjqK27mtLt2uBI5pSYB+T9E7gMOCquuaqrP3twP7AfwDY/ovtl6nI+ouhwIaShgLDgWcYxOu3fTfwpw7Nna33cOAntt+wvRT4HbWfkT2SEBwYRgFP1j1/qrRVgqRWYHfgfmAr289CLSiBLZtYWl+6BPgSsKqurSpr3w54Abi6XA6+StJGVGT9tp8GLgb+CDwLtNmeSUXWX6ez9fbqz8OE4MCgBm2VeG+LpBHAjcDptl9pdj3rgqQPA8/bntfsWppkKLAH8D3buwOvM7gu/XWp3Ps6HNgW2BrYSNKxza2qX+nVn4cJwYHhKWCbuufvpHZ5ZFCTtD61ALze9k2l+b8ltZTjLcDzzaqvD+0L/JOkZdQufX9A0nVUY+1Q++/9Kdv3l+c/oxaKVVn/QcBS2y/YfhO4CXgf1Vl/u87W26s/DxOCA8McYLSkbSW9jdpN4VuaXFOfkiRq94Qesf3vdYduASaXx5OB/1zXtfU122fafqftVmp/17+yfSwVWDuA7eeAJyXtUJoOBB6mIuundhl0b0nDy/8HB1K7J16V9bfrbL23AEdLGiZpW2A08EBPJ8lvjBkgJB1K7T7REGCa7W80t6K+JWk/4B5gEX+7L/ZlavcF/y/wLmo/LI6y3fGG+qAh6QDgDNsflrQZFVm7pHHUXhT0NuAJ4ARq/2ivyvrPBSZRe5X0AuDjwAgG6fol/Rg4gNpHJv038FXgZjpZr6R/BU6k9v053fZ/9XjuhGBERFRVLodGRERlJQQjIqKyEoIREVFZCcGIiKishGBERFRWQjAiIiorIRgREZX1/wH5KbtNysj1xwAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.barh(pe, math)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "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>symboling</th>\n",
       "      <th>normalized-losses</th>\n",
       "      <th>make</th>\n",
       "      <th>aspiration</th>\n",
       "      <th>num-of-doors</th>\n",
       "      <th>body-style</th>\n",
       "      <th>drive-wheels</th>\n",
       "      <th>engine-location</th>\n",
       "      <th>wheel-base</th>\n",
       "      <th>length</th>\n",
       "      <th>...</th>\n",
       "      <th>compression-ratio</th>\n",
       "      <th>horsepower</th>\n",
       "      <th>peak-rpm</th>\n",
       "      <th>city-mpg</th>\n",
       "      <th>highway-mpg</th>\n",
       "      <th>price</th>\n",
       "      <th>city-L/100km</th>\n",
       "      <th>horsepower-binned</th>\n",
       "      <th>diesel</th>\n",
       "      <th>gas</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>3</td>\n",
       "      <td>122</td>\n",
       "      <td>alfa-romero</td>\n",
       "      <td>std</td>\n",
       "      <td>two</td>\n",
       "      <td>convertible</td>\n",
       "      <td>rwd</td>\n",
       "      <td>front</td>\n",
       "      <td>88.6</td>\n",
       "      <td>0.811148</td>\n",
       "      <td>...</td>\n",
       "      <td>9.0</td>\n",
       "      <td>111.0</td>\n",
       "      <td>5000.0</td>\n",
       "      <td>21</td>\n",
       "      <td>27</td>\n",
       "      <td>13495.0</td>\n",
       "      <td>11.190476</td>\n",
       "      <td>Medium</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>3</td>\n",
       "      <td>122</td>\n",
       "      <td>alfa-romero</td>\n",
       "      <td>std</td>\n",
       "      <td>two</td>\n",
       "      <td>convertible</td>\n",
       "      <td>rwd</td>\n",
       "      <td>front</td>\n",
       "      <td>88.6</td>\n",
       "      <td>0.811148</td>\n",
       "      <td>...</td>\n",
       "      <td>9.0</td>\n",
       "      <td>111.0</td>\n",
       "      <td>5000.0</td>\n",
       "      <td>21</td>\n",
       "      <td>27</td>\n",
       "      <td>16500.0</td>\n",
       "      <td>11.190476</td>\n",
       "      <td>Medium</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1</td>\n",
       "      <td>122</td>\n",
       "      <td>alfa-romero</td>\n",
       "      <td>std</td>\n",
       "      <td>two</td>\n",
       "      <td>hatchback</td>\n",
       "      <td>rwd</td>\n",
       "      <td>front</td>\n",
       "      <td>94.5</td>\n",
       "      <td>0.822681</td>\n",
       "      <td>...</td>\n",
       "      <td>9.0</td>\n",
       "      <td>154.0</td>\n",
       "      <td>5000.0</td>\n",
       "      <td>19</td>\n",
       "      <td>26</td>\n",
       "      <td>16500.0</td>\n",
       "      <td>12.368421</td>\n",
       "      <td>Medium</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2</td>\n",
       "      <td>164</td>\n",
       "      <td>audi</td>\n",
       "      <td>std</td>\n",
       "      <td>four</td>\n",
       "      <td>sedan</td>\n",
       "      <td>fwd</td>\n",
       "      <td>front</td>\n",
       "      <td>99.8</td>\n",
       "      <td>0.848630</td>\n",
       "      <td>...</td>\n",
       "      <td>10.0</td>\n",
       "      <td>102.0</td>\n",
       "      <td>5500.0</td>\n",
       "      <td>24</td>\n",
       "      <td>30</td>\n",
       "      <td>13950.0</td>\n",
       "      <td>9.791667</td>\n",
       "      <td>Medium</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2</td>\n",
       "      <td>164</td>\n",
       "      <td>audi</td>\n",
       "      <td>std</td>\n",
       "      <td>four</td>\n",
       "      <td>sedan</td>\n",
       "      <td>4wd</td>\n",
       "      <td>front</td>\n",
       "      <td>99.4</td>\n",
       "      <td>0.848630</td>\n",
       "      <td>...</td>\n",
       "      <td>8.0</td>\n",
       "      <td>115.0</td>\n",
       "      <td>5500.0</td>\n",
       "      <td>18</td>\n",
       "      <td>22</td>\n",
       "      <td>17450.0</td>\n",
       "      <td>13.055556</td>\n",
       "      <td>Medium</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 29 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "   symboling  normalized-losses         make aspiration num-of-doors  \\\n",
       "0          3                122  alfa-romero        std          two   \n",
       "1          3                122  alfa-romero        std          two   \n",
       "2          1                122  alfa-romero        std          two   \n",
       "3          2                164         audi        std         four   \n",
       "4          2                164         audi        std         four   \n",
       "\n",
       "    body-style drive-wheels engine-location  wheel-base    length  ...  \\\n",
       "0  convertible          rwd           front        88.6  0.811148  ...   \n",
       "1  convertible          rwd           front        88.6  0.811148  ...   \n",
       "2    hatchback          rwd           front        94.5  0.822681  ...   \n",
       "3        sedan          fwd           front        99.8  0.848630  ...   \n",
       "4        sedan          4wd           front        99.4  0.848630  ...   \n",
       "\n",
       "   compression-ratio  horsepower  peak-rpm city-mpg highway-mpg    price  \\\n",
       "0                9.0       111.0    5000.0       21          27  13495.0   \n",
       "1                9.0       111.0    5000.0       21          27  16500.0   \n",
       "2                9.0       154.0    5000.0       19          26  16500.0   \n",
       "3               10.0       102.0    5500.0       24          30  13950.0   \n",
       "4                8.0       115.0    5500.0       18          22  17450.0   \n",
       "\n",
       "  city-L/100km  horsepower-binned  diesel  gas  \n",
       "0    11.190476             Medium       0    1  \n",
       "1    11.190476             Medium       0    1  \n",
       "2    12.368421             Medium       0    1  \n",
       "3     9.791667             Medium       0    1  \n",
       "4    13.055556             Medium       0    1  \n",
       "\n",
       "[5 rows x 29 columns]"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "d = pd.read_csv(\"auto_clean.csv\")\n",
    "d.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['symboling', 'normalized-losses', 'make', 'aspiration', 'num-of-doors',\n",
       "       'body-style', 'drive-wheels', 'engine-location', 'wheel-base', 'length',\n",
       "       'width', 'height', 'curb-weight', 'engine-type', 'num-of-cylinders',\n",
       "       'engine-size', 'fuel-system', 'bore', 'stroke', 'compression-ratio',\n",
       "       'horsepower', 'peak-rpm', 'city-mpg', 'highway-mpg', 'price',\n",
       "       'city-L/100km', 'horsepower-binned', 'diesel', 'gas'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "d.columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array(['alfa-romero', 'audi', 'bmw', 'chevrolet', 'dodge', 'honda',\n",
       "       'isuzu', 'jaguar', 'mazda', 'mercedes-benz', 'mercury',\n",
       "       'mitsubishi', 'nissan', 'peugot', 'plymouth', 'porsche', 'renault',\n",
       "       'saab', 'subaru', 'toyota', 'volkswagen', 'volvo'], dtype=object)"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "d['make'].unique()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\rashi\\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": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x576 with 3 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.style.use('ggplot')\n",
    "fig, (ax1, ax2, ax3) = plt.subplots(nrows=1, ncols=3, figsize=(12, 8))\n",
    "\n",
    "plt.subplots_adjust(wspace = 0.5)\n",
    "ax1.barh(d['body-style'], d['price'])\n",
    "ax2.scatter(d['length'], d['width'])\n",
    "ax3 = sns.barplot(d['body-style'], d['city-mpg'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 115,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 504x648 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#plt.figure()\n",
    "fig, ax1 = plt.subplots(figsize=(7, 9))\n",
    "ax1.barh(d['make'], d['price'])\n",
    "ax1.set_xlabel(\"Price\")\n",
    "ax1.set_title(\"Price of Automobile of Different Maker\")\n",
    "\n",
    "l, b, h, w = 0.71, 0.78, 0.26, 0.18\n",
    "ax2 = fig.add_axes([l, b, h, w])\n",
    "ax2.scatter(d['city-mpg'], d['price'], color = \"green\")\n",
    "ax2.set_xlabel(\"City MPG\")\n",
    "ax2.set_ylabel(\"Price\")\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### import numpy as np\n",
    "\n",
    "fig, axes = plt.subplots(2, 2)\n",
    "for ax in axes.flat:\n",
    "    ax.scatter(d['length'], d['width'])\n",
    "    ins = ax.inset_axes([0.7,0.3,0.2,0.2])\n",
    "    \n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0      0.811148\n",
       "1      0.811148\n",
       "2      0.822681\n",
       "3      0.848630\n",
       "4      0.848630\n",
       "         ...   \n",
       "196    0.907256\n",
       "197    0.907256\n",
       "198    0.907256\n",
       "199    0.907256\n",
       "200    0.907256\n",
       "Name: length, Length: 201, dtype: float64"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "d['length']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0      13495.0\n",
       "1      16500.0\n",
       "2      16500.0\n",
       "3      13950.0\n",
       "4      17450.0\n",
       "        ...   \n",
       "196    16845.0\n",
       "197    19045.0\n",
       "198    21485.0\n",
       "199    22470.0\n",
       "200    22625.0\n",
       "Name: price, Length: 201, dtype: float64"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "d['price']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 198,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x360 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from mpl_toolkits.axes_grid1.inset_locator import mark_inset, inset_axes\n",
    "\n",
    "#plt.rcParams[\"figure.figsize\"] = [8, 5]\n",
    "#plt.rcParams[\"figure.autolayout\"] = True\n",
    "\n",
    "plt.figure(figsize = (8, 5))\n",
    "x = d['length']\n",
    "y = d['price']\n",
    "\n",
    "ax = plt.subplot(1, 1, 1)\n",
    "ax.scatter(x, y)\n",
    "ax.set_xlabel(\"Length\")\n",
    "ax.set_ylabel(\"Price\")\n",
    "\n",
    "axins = inset_axes(ax, 1, 1, loc = 1, bbox_to_anchor=(0.3, 0.7),\n",
    "                   bbox_transform = ax.figure.transFigure)\n",
    "\n",
    "axins.scatter(x, y)\n",
    "\n",
    "x1, x2 = 0.822, 0.838\n",
    "y1, y2 = 6400, 12000\n",
    "\n",
    "axins.set_xlim(x1, x2)\n",
    "axins.set_ylim(y1, y2)\n",
    "\n",
    "mark_inset(ax, axins, loc1=1, loc2=3, fc=\"none\", ec = \"0.4\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 193,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0, 0.5, 'Width')"
      ]
     },
     "execution_count": 193,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x432 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = plt.figure(figsize = (8, 6))\n",
    "\n",
    "x = d['length']\n",
    "y = d['width']\n",
    "c = d['price']\n",
    "\n",
    "ax = plt.scatter(x, y, s = 25, c = c)\n",
    "\n",
    "plt.xlabel('Length', labelpad = 8)\n",
    "plt.ylabel('Width', labelpad = 8)\n",
    "plt.title(\"Length vs Width and Color Represents the Changes of Price\")\n",
    "\n",
    "ax_new = fig.add_axes([0.2, 0.7, 0.2, 0.2])\n",
    "plt.scatter(x, y, s=5, c = c)\n",
    "plt.xlabel('Length')\n",
    "plt.ylabel('Width')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 163,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.patches.ConnectionPatch at 0x2d804635760>"
      ]
     },
     "execution_count": 163,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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3L4NXXqmRZNTO53lEkoSECC6n00lJSQmPPPII69at44MPPqC8vNzjnNdff53hw4fz9NNPs3jxYrZu3erx/P/93/8xbNiwEEYtzmXJklR3EupgtyssWZIanoAiUK81ouXLl6MoSm+nAJKkhAiEsrIysrOzycrKAmDq1Kns2bOHnJwc9znl5eV85zvfAWDYsGFUV1dTX19PamoqtbW17N27l+uvv56//OUvYSmD6M5s9j6Zt6fjg1Gvieiaa65x/7uyspJ33nmHq666iiFDhlBTU8N7773HjBkzgh6kEIOByWTCaDS6HxuNRo4ePepxTn5+Prt372bs2LGUlZVRXV2NyWQiNTWVrVu38v3vf5/W1tZe71NaWkppaSkAq1atIiMjI/CF6YVOpwv5PUOtcxnT0sDbgiFpaQz4n4Ovek1EV199tfvfP/nJT/jJT35Cbm6u+9i0adPYtGkTc+fODVqAQgwWnUekdujaIlFYWMjWrVtZunQpeXl5jBgxAo1Gw0cffURKSgrnn38+n332Wa/3KSgooKCgwP041FtaD4ZttDuX8Re/8OwjAtDpVH7xi1pqaqK7jyjkW4WXl5e7mww6ZGZmUlFREZBAhBjsjEYjtbW17se1tbWkpaV5nJOQkEBRURHgSlyLFy8mMzOTnTt38uGHH7Jv3z7a2tpobW3l2Wef9Rj1KsJjyhQbr7xSI6PmeuFzIho/fjwbN25k3rx5GI1Gampq+P3vf8/YsWODGZ8Qg8bIkSM5ffo0VVVVpKens3Pnzm6JpLm5mdjYWHQ6HTt27GDcuHEkJCTwve99j+9973sAfPbZZ7z55puShCLIlCk2du+uDncYEcvnRLRo0SJeeOEF7rvvPpxOJ1qtlssuu8z915kQwj9arZb58+ezcuVKnE4nM2bMIDc3l+3btwMwe/ZsKioq2LBhAxqNhpycHBYsWBDmqIXwn6J6a5juhdPpxGw2YzAY0Gh8Hv0dNqdOnQp3CEE1GNrbIfTlDFTbdzQI9WdkMPzODoYyQoj6iKqqqsjMzATOLvXTobr6bDWza9+REEII4ateE9EDDzzAtm3bAHptb+5YfUEIIYToq14TUUcSAvj5z3/O8OHDgx2PEEKIQcbnwQo///nPsVqtjB07lvHjx/O1r32N4cOH+7TyghBCCNETnxNRx0KLhw4d4uDBg7z99ts0NjYyduxYWVxRCCFEv/mciMA1KMHhcGC327Hb7ezfv5+GhoZgxSaEEGIQ8DkRPfPMMxw+fJj09HTGjx/PtGnT+OEPf0h8fHww4wsI/a5d3baetsmuskIIERF8ngh07NgxNBoN+fn55OfnM3z48KhJQhnz5qEvL0djNqMvL3c93rUr3KEJIYSgjxNa6+vrOXjwIAcPHuTw4cO0tbUxbty4iJ7dbcvNRd9lTxcAW04O1bt3hyGiwBosE+dkQmvwyITWwBsMZYTAfU76tDRCamoqQ4cOJTs7myFDhlBfX8++ffsCEkiwaL2tv97LcSGEEKHVp+Hbn3/+OfHx8YwfP55LL72UH/zgB5x33nnBjM9vDoMBjZek4zAYwhCNEEKIrnxORJdffjm33367e8mfaFG/fj0Z8+ah2O3uY6pOR/369WGMSgghRAefm+auvvrqqEtCALYpU6h55RVsOTk4DQZsOTmux0EcNafftYshl19O9rhxDLn8chkYIYQQvejTPCJ/7d+/ny1btuB0Opk5cyaFhYUez7e0tPDss89SW1uLw+Hguuuuc29F/n//93/s2LEDVVWZOXMm3/rWt3y+r23KlJANTOgYpddRA9OYzWTMmxf05CeEENEqZPs4OJ1OSkpKeOSRR1i3bh0ffPAB5V1Gs/3tb38jJyeHNWvW8Nhjj7Ft2zbsdjsnTpxgx44dPPXUU6xZs4a9e/dy+vTpUIXeJ6lLlng0AwIodjupS5aEKSIhhIhsIUtEZWVlZGdnk5WVhU6nY+rUqezZs8fjHEVRsFgsqKqKxWIhKSkJjUZDRUUFo0ePJjY2Fq1Wy7hx4/jPf/4TqtD7REbpCSFE34Ssac5kMmE0Gt2PjUYjR48e9Tjn2muvZfXq1dx99920trby4x//GI1GQ25uLi+//DKNjY3ExMSwb98+Ro4c6fU+paWllJaWArBq1SoyMjKCVyhv0tLAW9JJSwtKLDqdLvRlDIPBUk4hBqOQJSJv82a7rtz98ccfk5+fz/Lly6msrOSJJ55g7Nix5OTkMGfOHJ588kni4uLIz8/vcXfYgoICCgoK3I9DPalM/4tfeB2lV/uLX2ALQiyDZeKcTGgVYuAKWSIyGo3U1ta6H9fW1pKWluZxzjvvvENhYSGKopCdnU1mZianTp1i1KhRXHPNNVxzzTUA/Pa3v/WoXUWK+JISUlasAIcDJ4BOhyM7W9a2E0KIXoSsj2jkyJGcPn2aqqoq7HY7O3fuZNKkSR7nZGRkcODAAcC1nNCpU6fcQ8Y7VvmuqanhP//5D9/4xjdCFbpP4ktKSF2+HI3DgYLrB6vY7TTddZckISGE6EWf1prz1969e3nppZdwOp3MmDGD66+/nu3btwMwe/ZsTCYTGzdupK6uDoA5c+Ywffp0AJYvX05jYyM6nY5bb72ViRMn+nTPUK2jlZ2Xh8bh6HbcqdVy5sSJoN1XmuaCYzA1zclac4E3GMoIgfuchDQRhUOoPmTnDRuGt71qVeB0RUXQ7jtYfuElEQWPJKLAGwxlhDAteip6pmq1fTouhBDCRRJRgDQUF9O1aqm2HxdCCNGzkC7xM5C13nEHACkrVqA4HKhaLQ3Fxe7jQvjiXMtgNTU1sWnTJiorK9Hr9SxcuJC8vDza2tooLi7GbrfjcDiYMmUKc+fODU8hhOgjSUQB1HrHHZJ4RL91LIP16KOPYjQaefjhh5k0aRI5OTnuc15//XWGDx/O0qVLqaiooKSkhOXLl6PX6ykuLiYuLg673c7y5cu56KKLGDNmTBhLJIRvpGlOiAjhyzJY5eXl7hGjw4YNo7q6mvr6ehRFIS4uDgCHw4HD4eg2YVyISCWJSIgI4W0ZLJPJ5HFOfn4+u9tXki8rK6O6utp9jtPpZOnSpdx5551MnDiR0aNHhy74ENm1S8/llw9h3LhsLr98CLt26cMdkocTJ7QsXpzK7Nk6Fi9O5cQJGazkC2maEyJC+LIMVmFhIVu3bmXp0qXk5eUxYsQI93JXGo2GNWvW0NzczNNPP82JEyfIy8vr9prhXo+xv+sGvv8+zJunx253/UzMZg3z5mXw1ls22qcbhtXx43DLLXq++KLjPUvg44/j+b//szFiRFhDi3iSiISIEL4sg5WQkEBRURHgSlyLFy/utmFlYmIi48ePZ//+/V4TUbjXY+zvHJvbbx/iTkId7HaF229X2L27OlDh9dvDD6fyxRcxHse++ELh4YftbNhQH56ggkzmEQkxwPiyDFZzczP29gV1d+zYwbhx40hISMBsNtPc3AxAW1sbBw4cYNiwYSEvQzCZzd6buXo6HmpnzniPo7IyMuKLZIO+RqTftYvUJUvQms04DIaIW6A00uMTgaPVapk/fz4rV650L4OVm5vrsQxWRUUFGzZsQKPRkJOTw4IFCwCoq6vjueeew+l0oqoqV1xxBZdeemk4ixNwBoMDs7n7384GQ/eltcIhO9t7HFlZkRFfJBvUS/x03dYbXFs2RMq23r7EN1iWEpElfoInWpb42bVLz7x5GR7Nczqdyiuv1DBlii2QIfbLiRNabropna++OjuAIj/fxssvm8jLG5jJSJrmAiDSt/WO9PiECKUpU2y88koNOTk2DAYnOTm2iElCAHl5Dl5+2cR3vtPCVVc5+c53WgZ0EgqkQd00F+nbekd6fEKE2pQptogYmNCTvDwHGzbUt9f66sMdTtQY1DUih8HQp+OhFunxCSFEIAzqRFS/fj2qzrNSqOp01K9fH6aIPEV6fEIIEQiDOhHZpkxxdfzn5OA0GLDl5ETMQAWI/PiEECIQBnUfEbi+7Kvbl0yJRJEenxBC+GtQ14iEEEKEnyQiIYQQYSWJSIhBTlaIFuEmiUiIQe6mm9IlGYmwkkQUAWL/9CeyRo3ivLw8skaNIvZPfwp3SGIQ+eorPatXJ4c7DDGIDfpRc+EW+6c/kV5URMfqWdrWVtKLijAB1jlzwhmaGERkhWgRTlIjCrPU+++n64bOSvtxIUJFVogW4SQ1ojDTtLX16bgQgZafb2PZssZznvfoo0ls2ZKE608lldtvb+LJJ5uCHl8wnDihZfXqZM6c0ZKc7ASgsVFDdraDZcsaI2qh0l279CxZkorZrMVgcLB+fX3QFnoN13ssiSjMnDExaFtbvR4XIhR8WSHa9QWVDO76u9L+mKhLRt62a+hs7159xKya3XXri47t0YOx6ng432Npmguz+rVr6bohlNp+XIhQ8OUL9+xfyZ0p7cejy+rVyT0mIYiswRtLlqR63R59yZLUgN8rnO+xJKIws86Zg2njRhzx8ahaLY74eEwbN8pABRFhun5Bnet45OppS+/OImXwRmi3Rw/feyxNcxHAOmcOlZJ4RERT8f6FFH0bPPe0pXdnkTJ4I7Tbo4fvPZYakRDinG6/vYnuX0hq+/HosmxZI/n5Pfev+Dp4IxTWr69Hp/P8uet0KuvX1wf8XuF8j6VGJIQ4p47O6oEwaq5jS+/Vq5OprNSSlOQaNdfUpCErK7JGzXVsjx6KUXPhfI8VVVWjr27dB6dOnQp3CEHl2pK4JtxhBF2oyzl06NCQ3SvcQv0ZGQy/s4OhjBC4z4k0zQkhhAgraZoTQrh1nugZiZM7xcAkiUgIAXif6BlJkzvFwCVNc0IIwPtEz0ia3CkGrpDWiPbv38+WLVtwOp3MnDmTwsJCj+dbWlp49tlnqa2txeFwcN111zFjxgwA/vKXv/CPf/wDRVHIzc2lqKiIGFkGRwww5/qMNDU1sWnTJiorK9Hr9SxcuJC8vDxqamp47rnnqK+vR1EUCgoK+O///u8+3buniZ6RMrlTDFwhqxE5nU5KSkp45JFHWLduHR988AHl5eUe5/ztb38jJyeHNWvW8Nhjj7Ft2zbsdjsmk4m33nqLVatWsXbtWpxOJzt37gxV6EKEhC+fkddff53hw4fz9NNPs3jxYrZu3QqAVqvlBz/4AevWrWPlypW8/fbb3a49l54mekbK5E4xcIUsEZWVlZGdnU1WVhY6nY6pU6eyZ88ej3MURcFisaCqKhaLhaSkJDQaV4hOp5O2tjYcDgdtbW2kpaX1fsOBPSpdBFsYfn98+YyUl5czceJEAIYNG0Z1dTX19fWkpaVx/vnnAxAfH8+wYcMwmUznvGfnYnqb6BlJkztFZAnkRyRkTXMmkwmj0eh+bDQaOXr0qMc51157LatXr+buu++mtbWVH//4x2g0GtLT07nuuutYuHAhMTExXHjhhVx44YVe71NaWkppaSlfO3yYH0ydytB77wV9zwscDgSDZc5LSMv5+OPw6KOgCV03qi+fkfz8fHbv3s3YsWMpKyujuroak8lEamqq+5yqqiqOHz/OqFGjvN6n4zNSV5fOzJnLmDvX9XMdOhS+/LLr2Xogy//CdTEYfmcHchl37YLf/hZ+8hPICsCvR8g+Zd7mzSqK57pGH3/8Mfn5+Tz//POsWbOGkpISWlpaaGpqYs+ePTz33HM8//zzWCwW3n//fa/3KSgoYNWqVfzg9dd5+uhR+PGPYf/+YBQpIjz00EPhDiEkQl7OadPg7bdDektfPiOFhYU0NzezdOlS3nrrLUaMGOFuNQCwWCysXbuW2267jYSEBK/36fiMXH31MiZMCGwZfDEYfmcHahlPnoQHH4Rjx+CZZ2DdusCUM2SJyGg0Ultb635cW1vbrXntnXfe4fLLL0dRFLKzs8nMzOTUqVMcOHCAzMxMDAYDOp2Oyy+/nCNHjpzznjXp6bB+PXzwAfz85yCbzQlfzZgB//hHSG/py2ckISGBoqIi1qxZw+LFizGbzWRmZgJgt9tZu3YtV155JZdffvk57/f553DBBYEtgxiYmptdX6G/+x0sXw633BLYxoKQJaKRI0dy+vRpqqqqsNvt7Ny5k0mTJnmck5GRwYEDBwCor6/n1KlTZGZmkpGRwdGjR7FaraiqyoEDBxg2bJhvN9ZqYdEiuOEGuP9++OijQBdNDESKAhMnwiefhOyWvnxGmpubsdvtAOzYsYNx48aRkJCAqqps3ryZYcOG8e1vf9un+zmdro+HED1xOuE3v3G1VH/ve7BsGSQmBv4+Iesj0mq1zJ8/n5UrV+J0OpkxYwa5ubls374dgNmzZ3PDDTewceNG7r//fgBuueUWDAYDBoOBKVOm8OCDD6LVahk+fDgFBQXnvKfHOaNGuWpH/+//uZpc7r8fYmODUtZQ8uXnMBCEpZzz5rk+gV//ekhu58tnpKKigg0bNqDRaMjJyWHBggUAHD58mPfff5+8vDyWLl0KwM0338wll1zi9V4OhyvXhsNg+J0dCGXcuRNeeQVuvhm+/33v5wSqnAN+0VOvjh+HdetcP93LLgt3NCKSPf206/ckOzvckQTUwYOurtPvfS/ckYhI89VX8NxzcNFFcNNNoRmvMzgTEbjqnCUlUFnpqh3Fx4c7IhGJamrghRdggHU+b9sGV1wBo0eHOxIRKZqaYMOGs70ZPYx1CYrBu9acRgM//KEr/T/4oCv1T50a7qhEpMnIcPXUtrYOqD9Wysp6bm4Rg0tHP9DBg7B4MeTkhD6GqKwR+bNUkNdrVRW2boUTJ2Dp0tD+KdCL/pYzEMu9hIo/7yW4Jjo/9NBDpKenB2/I7Oefw7/+BXfeGZzXD4Of/hSeeCKwr+nPe9nc3MzmzZs5efIkiqKwcOFCxowZE9gAA2QgLVX2r3/B73/vGgXXuZeiv0tN+XKtV2qUcTgc6uLFi9UzZ86oNptNfeCBB9STJ096nPPaa6+pv/71r1VVVdWGhgb1tttuU20227mvPXFCVe+5R1Xffz+URfLKn3KaTCb12LFjqqqqaktLi3rPPfd0uzYS+FPGDm+++ab6zDPPqD/72c+CG+zSparqcAT3HiHS1qaqxcWBfU1/38tf/vKXamlpqaqqqmqz2dSmpqbABhgg/pSztrZWLSoqUq1Wq6qqqrp27Vr1nXfeCXURVFVV1ePHVfWBB1T1d79TVafT8zlfyrht2zb11VdfVVVVVcvLy9UVK1b4fK03Ubf6tj9LBZ3z2txc1yyt48ehuNjVJBMm/pSzv8u9hJq/yz7V1tayd+9eZs6cGfxgr7025BNcg+XgQfja1wL7mv68ly0tLRw6dIhrrrkGAJ1OR2IwxggHQMiXKguwxkZ46in4wx9cA0Jvuqn76El/lpry5Vpvoi4ReVsGpeuX7LXXXktFRQV33303999/P7fffjsajcana1EUuPVWuPtu1xIv774bzOL0yJ9ydnau5V7Cyd8ybt26le9///vdVh8IijBMcA2WDz+EyZMD+5r+vJdVVVUYDAY2btzIsmXL2Lx5MxaLJbABBog/5ey8VNldd91FQkJCj0uVBZrT6ep9eOopuO02eOCBnrs8fSljx1JTgMdSUz59x3oRdYlI9WOpIF+udRs6FH7xC6iocDWoN4Z24Ud/ytnBl+VewsmfMn700UekpKS4a35BpygwYQK0T7iOZl9+Cfn5gX1Nf95Lh8PB8ePHmT17NqtXryY2NpY33ngjsAEGiD/l7MtSZYH0/vuulc4mTICf/cz11dYbX8rY01JTffqO7STqEpE/SwX5cq0HRXH14i1a5GqqKy0NeHl64k85oe/LvYSDP2U8fPgwH374IYsWLeKZZ57h008/5dlnnw1uwDfdBC+/HNx7hEigK5H+fi6NRiOj28eST5kyhePHjwc2wAAJx1Jl/fXFF66az5kzrh6HLot09Mifpab6/B3bLuoSkT9LBflyrVfZ2bB2LZhMruVmzeZgFM2DP+VU+7HcSzj4U8bvfe97bN68meeee457772XCRMmcM899wQ34NhYSEtzfbKjlNUanMXo/XkvU1NTMRqN7j+iDhw4QE44xhD7IGxLlfWB2QxPPglvvOEaGTl3bt/+8PBnqan+fsdG5fDtvXv38tJLL7mXQbn++us9lkExmUxs3LiRuro6AObMmcP06dN7vLZPqqpg9WqYNQv+678CWq6u+lvOzz//nOXLl5OXl+euFve23Es4+fNedvjss8948803Q7PicU0N/OpX8PDDwb9XEHz4IZSXgy8javvKn/fyyy+/ZPPmzdjtdjIzMykqKiIpKSnwQQaAP+V89dVX2blzp3upsgULFqAP0F8GDge89JJrjtiPfgTnndf/1zpXGY8cOdJtqamO96s/37FRmYgiwmuvuT7VDz4InfaCEYPAT38KjzwSlRNcN2+G666DIPwhLsLo3Xfh9dfhf/8XIvDvzXOKuqa5iNGxmvdTT8Ff/xruaEQo3XIL/H//X7ij6JeKinN3VovoceyY62uottbVDxSNSQgkEfknI8PVTGezuWpGEThXRwTB2LFw+LBrTGwUCteq2yJwGhpc/UBvvgkrV7r+Lo7m93XwrjUXSIWFMH26a+eoqVNhzpxwRySCrWOC6ze/Ge5IfNbaCnFx4Y5C+MPhgBdfdA3B/9GPBs6i8FIjCpT0dFci0mpd69XV1IQ7IhFM11wTdRNc9+93Le0votOOHXDffa7JyCtXDpwkBJKIAu/b33YN8V671jWgQQxMUTjB9cMPfZ9LIiLH0aOufqDGRlc/0ED8Y0ISUTCkprqmMCcmun6DqqrCHZEIhptugt/9LtxR+KyqCrKywh2F8FV9vWs9uLfeco2JKiyM7n6g3kgfUTBde61r97HVq13bTfd1ZpmIbJ0nuA6kdhIRVna7qx/o5ElXP1BmZrgjCj6pEQVbSoqrQTc93VU7iuJZ+cKL2293rSYZ4ZqaXBV0Edn+/nfXsjxTprhWRRgMSQikRhQ6s2a5frtWr4Zx4+Dmm6V2NBBEyQ6u+/ZF7xyTweDwYXj+ebj6ali3bvB9NcjKCuHwzjvw5z+7RtfJ7MLoFwU7uK5b59rdpNMK/SIC1NXBs8+6GkzuvhvCuFlrWEmNKBxmzHCNwVyzBkaOhB/8YPD9CTSQjB0LJSWuCa6ayGztNpkkCUUSux1eeMG10sU998CQIeGOKLwi81MzGCQlwYoVMHw43HuvayVKEb0G0A6uIrjeftvVDzRtmqsfaLAnIRgETXMdS8tHioyMDGq6THZVWltJ3LQJx7BhtEb4yDpv8UeboJRBVTE8+STmn/40sK/bg76UoaFB4Xe/S2DBguYgR9U3g+13qaxMx29+k8A3vmGloMAaER9zf9+DoQHqWpAaUQRQ4+Npuu8+7Oefj2H5crQVFeEOSfSVomC74AJ0hw6FO5JuDhzQM3GiLdxhDFp1dQpr1ybzz3/G8MgjZmbNiowkFElC1ke0ceNG9u7dS0pKCmvXru32vKqqbNmyhX379hEbG0tRUZF7G+j9+/ezZcsWnE4nM2fOpDAYm6lEANvkydgmTCDp+edxZmbSIiProkrrnDkk/+IXNI4bF+5QPBw4oOeWW1rOfaIICEudnZPbW2mucVJ6OB3bkDjuXtRMenp0LpIbCiGrEV199dU88sgjPT6/b98+zpw5w7PPPstdd93FCy+8AIDT6aSkpIRHHnmEdevW8cEHH1A+kPtT4uNpuvdebGPHumpHJ06EOyLhq9hYnKmpaCJsJY3GRg0Gw4BugY8Yljo7n240U7o9hs1vDiGfBmZpTpKgtIU7tIgWskQ0fvz4Xndc/PDDD5k+fTqKojBmzBiam5upq6ujrKyM7OxssrKy0Ol0TJ06lT179oQq7LCxXXIJ5kcfJf5PfyLh17+O2i0HBpvWefNIePXVcIchwuSf2xz86v1sUBRuv+IM+RltOGwqJ7e3hju0iBYxw7dNJhMZGRnux0ajEZPJhMlkwthp3KnRaOTo0aM9vk5paSmlpaUArFq1yuM1I4FOp+tbTCtWoOzdS/JTT+H40Y9cw73DqM/xRyDdxx8zxOEI2utrTp8m/siRoO65sL8iG4fj3MOt6usBNJw4EXn7P2Rna6P/d6n981BTA889p6Xl8zp+ON2ETgtwdlKQYtH7XNbashY+XH+G1jo78Wk6Ji3JxjgqIaBxt9TaOPpnE8fqThOXpmH0/6STYAzMluX9ETGJyNvgPUVRejzek4KCAgoKCtyPI21UTr9GqeTlwbJlJP3qVzgTE2m59dawzVcZCCOdhjgc1Lu+oYNCe8UV6N94A8u11wbtHo5U38rw0Ud6cnJU6uvtQYulv+z2lKj/XTIYMli/vgWTScv8+U3UbDdjOtSG03H2O0p1qiTGqT6VteFLK/9ZXofToaIoGpqrrWy/5wsuezyNlOGxAYm5o/nQYVOJjYul5gsrpz9pYEKRgbi0vqWEATdqzmg0erxRtbW1pKWlYTQaqa2t7XZ80ImJoWnRItomTXL1HR07Fu6IRA8ceXloy8shAmZGHDumY9SoyEtCwVb1SQs7fniGt28+zY4fnqHqk8AO1lBV+PvfY/nJT7RMm9bG/fc3kpamkjs7Hq1eQXW63nvVqaLVK+TO9m35p0MvNLqTEICiaHA6VA690Biw2E9ub8VhU1E0rmSpaJSwNx9GTCKaNGkS77//PqqqcuTIERISEkhLS2PkyJGcPn2aqqoq7HY7O3fuZNIg3lTFPmEC5uJi4rZvJ7GkxLVlo4g4bZdeiv6jj8IdBhaLMuh2Za36pIU9xQ20VqvYLdBarbKnuCFgyejzz3U89pgBnQ7WrHEwevTZRB+XpmNCkYH0cTEkZGpJHxfTp5qGtd7pTkIdFEWDtT5wfcTWOqc7CbnvoVGw1oWvHzpkTXPPPPMMBw8epLGxkQULFjB37lzsdtcbOHv2bC6++GL27t3LPffcQ0xMDEVFRQBotVrmz5/PypUrcTqdzJgxg9zc3FCFHZn0epoXLkR36BApy5fTfNtt2EePDndUohPbRReRWFKCbRD/0RQuB35pRlXPznxQFFcN5sAvzcz8Vf/7WmprNZSUJJKd7eDRR83o9QDJ3c6LS9Mxel73476ITdVgqbN5JCNVdRKbGrj+m9g0Dc1n7B7JSHWqxKaFr14SskR077339vq8oijc2cOikZdccgmXyNLB3djHjaPhscdIfPFFYt95h+b580EXMd1+g5uiYM/PR3v8OI4RI8ISgsmkIS1t8I22tDep3abfKYrreH+0tcGvf51IQ4PCXXc1kZoavCbXcXcmt/cRuWpGqupEo1UYd2f/Eps3ubPjaSiz4bD1r/kwGCKmaU70k15P8913Y73qKlKKi9F9/nm4IxLtrFddRdx774Xt/keP6jyajQYLXZLSrXtOVV3H+0JV4e2343jqKQNXXNzMdcNOU/5yPUdfacRSF5yfa8rwWNfAhBF6YlMVUkboAzpQATybD5PO0/e5+TAY5M/nAcJ+wQU0rFhB4tatxL77Ls133EF724EIl5gYnElJKCYTanp6yG//xRc6brhh8K2oMPFHBvYUN7ib5zr+P/FHBp9f4+BBHS+/nMDMmVYeWmJyjzJTNArNZ+w0lNmYUGSAIIw+Txkey5QnA5d4vOloPoyUUbBSIxpIdDqa77wTa0EBKY89hu6zz8Id0aBnmTWLuPZ5baFmsw3O/W0yv57A5BUpxA9R0MVB/BCFyStSyPz6ufuHamo0rFqVzN69MSxfbuaqq6wROcpsoJEa0QBkHzWKhscfJ2HbNuLee4+mO+8cnN9IEUBNSUFpbQWrFWKD+1eux33DP3I8ZDrWdrPWOYlN05A7O57Mryf0aWCC1QrbtiXS1KSwcGETKSlnf4CROMpsoJFENFBptbTcfjvaL77A8PjjtM6bh23ixHBHNShZZ8wg7p13gjrBtauaGg0ZGd2/KK1mO5W7rNgaVfTJCllTYok1RO/XQOfJmV2bzXzp81BV+Nvf4vjPf2L4/vebGTmy+3SISBxlNtDIT3KAc5x/PubHH0e/dy9Jv/yl608/EVLhmOB65IiOMWM8O9StZjvHft+M+bgNi8mB+biNY79vxmqO3gEN/jSbffqpjuJiA0lJToqLzV6TEOD3JFVxbtH7p5DwnUZDy//+L9ovv8TwxBO0fve72C66KNxRDSodE1xDNa/oyy91XHaZ50CFyl1WnHbPL22nXaVyl5W82aH9KrCa7Xy8pZK6iiZ3c1pfRm01fGnl0AuNNByzgaKQmKshJtF1/bmazaqrXfOB8vIcFBeb0Wp7v1fHKLOuzX/hHGU20MhPchBxDB+O+fHHSfjtb4l97z2a7r47qAtzirNsF11E4gsvhCwRORzdB03aGlWvfR22xtB2KHXUzHRZDmx2R5+b0zqvx+a0g8Om0nDEQcoYiEnU9dhsZrG4+oFaWhSKipr6tDWGP5NUxblJ09xgo9HQ8v3v03r99RhWroyIZWgGBUXBPnw42uPHg36rnloA9clnm5fc5zpdfUWh5K1m1pdRaJ3XY9PEKGjah2g3n3R6bTZTVfjrX+NYvdrArFkW7r23b0lIBJ8kokHKkZvr6js6coSkdeugVYaiBpv1qquIDcEE1zNnNGRnd+/vyJoSi0bn2deh0bkGLIRSTzUzX0ehdV6PTVEUtAkKWj2gqt0mZx44oKe42EBqqpPly82MGCFrM0YiaZobzBSFlptvRltRgeFnP8Ny3XW0TZ4c7qgGrpgY1KQklLo61CCuIH/0qN7rigqxBh0jb0wM+6g5fbJCa033mpmvo9C6rsemKAqaGJWUEXp381llpYYXX0xkxAi7T/1AIrykRiRwDBuGecUKtF98QfLatSgtg282fqhYCgqI+/vfg3qPEye05OV5/8s/1qAjb3YiI29IIm92YliGbnurmfVlFNq4O5PRaBVU1VWD6rwem8UCzz+fyMsvJ7B4cRM33dQqSSgKSI1IuCgKrfPmoTl9muRVq7B885u0XXFFuKMacNTU1KBPcHU6iegv346aWWadvV+j5jrWYzv0QiPWetfK1GPvSOb9Ayns2xbD//5vM/n54W2C6xjV54pPw7g7kwO6XtxAIzUi4cF53nmu2tHp0ySvWYPS3BzukAacjgmuweB00m3l6UgUa9Bx4e1ZTFiQwuh5yX0eCu1ajy2DqzZkEn/jefxiyxAyMlz9QJGQhP6zvI6G4zas9SoNx22ux1/KHL6eSCIS3SkKrddfT/Ott5K8Zg0x//pXuCMaUII5wfXUKS3Dhg2ODvkzZzQ89VQyn3+uo7jYzBVXtIU7JCA0u6wONJKIRI+cWVmYi4vR1NaS/POfozTKBylQgrWD65EjA3/rh9ZW2Lw5kVdfTeCee5qYNy+y+oFCscvqQCOJSPROUbDMmUPz/Pkk/+IXKEHuaB8sbBddRMy+fQF/3fLygVsjUlX405/iWLvWwLe+ZeGee5pISoq8+UCxqRr3QIoOrl1W5eu2J/KTET5xDhmCubgYzGaSf/YzFLM53CFFtyBOcNUMwE/1vn2u+UDZ2U4efdRMbm7kJtveRvUJ72TUnOgT9YYbaJ4wgeT167FOnYp15sxwhxS1rFddRcJvf0tLgLYSdziiPwl98XYDh55vQbWDogPjjQb+cTyb0aPtPPaYOSrK521Un4ya650kItFnTqMR809/Stxbb5G8ciVNixahpqaGO6zoExODmpgYsAmuJ09qI7qmcC5fvN3AwQ2uOWxtToV3Tmei/gIWPFrBhDm+764aCUKxy+pAEgV/X4hIZfnmN2lauJDkDRuI3b493OFEJcusWQGb4Hr0qI7Ro20Bea1wOPR8C04VdpvSefPUUCal1XFtdiVfvSRTCAY6SUTCL2p6OuZHHwXA8OSTKCZTmCOKLh4TXP10+rSW886L3pFZx+oTebU8F2OMlRtyKjDGuoZjqwN7EKAgxE1z+/fvZ8uWLTidTmbOnElhYaHH801NTWzatInKykr0ej0LFy4kLy8PgEWLFhEXF4dGo0Gr1bJq1apQhi7OwTp7Nm2XXUbSxo3YLr4Yyze/Ge6QooZ1xgzi3n0Xy3/9l9+vFamTWb/6h5kTb56d55N3XQxckwJARYWGLVuSsNqtzM05SZf1UFGipAOh/INGPt3QhMMC2jiYsDiJnG/IAAVfhOwtdjqdlJSU8Oijj2I0Gnn44YeZNGkSOTk57nNef/11hg8fztKlS6moqKCkpITly5e7ny8uLsZgiK624sFETU2l8ZFHiN2xA8Pjj9O0aBFOozHcYfWb1eygcpeFtkaVmGSFrClxxBoCP2HFkZdH3Ntvu8Yn9zOT2O2Ru6xP1yQEcOLNNnaNPMPfvkpFUeC++xo5M9nCwQ3drx93d0KIIu2/8g8a2f/zJlABBexNuB4/iCQjH4Ssaa6srIzs7GyysrLQ6XRMnTqVPXv2eJxTXl7OxIkTARg2bBjV1dXU19eHKkQRINaZM2m8914S/9//I+7NN8MdTr9YzQ6O/b4J83F7+7bado79vgmrOTiDAdomTfJrguuXX+oYPjwy27C6JiGASkssK5fH8J3vtLJoURMJCSrn/1cK4xcnoOgBBRQ9jF+cwPn/lRL6oPvo0w1nkxC0/19tPy7OKWQ1IpPJhLHTX8dGo5GjR496nJOfn8/u3bsZO3YsZWVlVFdXYzKZSG0fkbVy5UoAZs2aRUFBgdf7lJaWUlpaCsCqVavIyMgIQmn6T6fTRVxMfeFz/BkZsHYtcdu3k7J6NY7774esrOAH6ANtRYX7d6onR96vRaPo0MaeraGoTpWG/TDmf3q/tl+uvhrNhg04e/i97kqr1XqUoaJC4aLxdqreb8VqdhBr0JJ3VQpxKZHQrlXT7UhWnJXL0uu48MKJHsczbsngsltCFZf/Oj4PDuvps0mogwIOKxH9eY+U76OQ/ZaqXtbVUro0QxQWFrJ161aWLl1KXl4eI0aMQNM+ceCJJ54gPT2dhoYGnnzySYYOHcr48eO7vWZBQYFHkqqp6f4hCKeMjIyIi6kv+hz/JZegjB5N0tNPYxs7Fsv//E/YOzKGOBznrGmbq1uxOxzg6H6849qmU20cf6OFtkYnMckaRhQmkDQ0pt9xxWZnY9+/H8fw4ec815HqWYZjR+LIOFqJ3erE1qDisDk5+UEDF/xvkl8xBVsoPwuWOjsnt7dirXP2ecXvnnR8HrSxYLfhmYxU0MZG3ndQZ/5+Hw0dOjQgcYSsac5oNFJbW+t+XFtbS1qXuRMJCQkUFRWxZs0aFi9ejNlsJjMzE4D09HQAUlJSmDx5MmVlZaEKXfhJTU6m8cEHcaanY3jsMTSVleEO6ZxikhXoOgDN2X4cVxL6dHMjTafs2JpUmk7Z2x/3f+FN61VXEfvuu/26trnCgd3qpPWMA1uLE9Wu0Nbs5PBLTVjN4W2yM4z1/jVz3hTf9h8KBEudnU83mjEdaqOlyoHpUBufbjRjqQvMz2bC4iR3cxzgbqabsDgpIK8/0IUsEY0cOZLTp09TVVWF3W5n586dTJo0yeOc5uZm7HbXL8aOHTsYN24cCQkJWCwWWtu3srZYLHzyySfu0XQierRdeSWNy5aRuG0b8a+9FpTVpwMla0ocGh1nk5ETNDrXcYDjb7SgOlV3rV5RXBu9HX/Dj00FO01w7Yu2NtDYXTUh13iHszHZ25xU7grM9gNNp9o4sLGej35u4sDGep+T7tibDcRne9aC47MVrnw0PyBx+eLk9lYctrNblCsaBYdN5eT21oC8fs43krnowSR0SaBoQZcEFz0oo+Z8FbKmOa1Wy/z581m5ciVOp5MZM2aQm5vL9vaJkLNnz6aiooINGzag0WjIyclhwYIFADQ0NPD0008D4HA4mDZtGhdddFGoQhcBpCYm0rh0KTH//jeG4mKaFi7Eed554Q6rm1iDlpE3JvU4aq6t0dmtaVlRFNoa/ZvHY5k1i7jt22mdO9fna44f15E3rA1HVdeYVLR6DbZG/xN+06k2Pttsbt/vSKGt0c5nm818bYHhnE1/sQYdExemdNuiPMGopyVErVbWOqc7CXVQNArWusDNu8r5RrIknn4KaU/mJZdcwiWXXOJxbPbs2e5/jxkzhmeffbbbdVlZWaxZsybo8YnQabviCmwXXkji5s04cnJovfHGsPcddRVr0JI3O9HrczHJGtoa7R5f/KqqEpPs3xjq/uzgevSojknfbOPU7zS02TqSkYqCQkyKBn2y/z/X42+0uJMQuP7vbK8BTiw6dx+Ua4vy8A2ciE3T0HzG7pGMVKdKbJrM6Y8E8i6IsFETEmi67z4cI0ZgKC5GU1ER7pB8NqIwAUWjuAfhqKqr2WdEof9zXqxXX01cH/qKTCYN5w3XcMH/JhGTqEHRqejiNcRna9HFuWof/gpWDTBUcmfHo9W7mk/BlYS0eoXc2aHrpxI9i4SxnWKQa5s8mbYJE0javBnHeefROm9exNWOukoaGsOEBcmdRs1p/R4118GRn0/c9u19nuCaNDSGCYsM3ZrAYg3+f8yDVQPs6vAf6zi61eLu7B99WxwXXO//grBxaTomFBkCPmpOBIa8CyIyxMfT9OMfo//oIwzLl9N81104cnPDHVWvkobG+NQs1R8dE1xtXQb0dGWxQGzs2T6gYDWBjShMaO8jcg3QUFUVjYaA1AA7HP5jHUe3WM4eUGl/XBewZDR6nvThRCJpmhMRxXbppZh/8hPi//hHEn7zG3BGR9NPoPm6g+sXX+gYOTL4w7OThsa0D0zQoU9SSBqq82mgQl8c3Wrp03ExcEiNSESeuDialixBv3+/q3Z0550+TfIcUBQFe34+2i+/7LXsR47oufpq37+o+zMJ12q2u5v7UkbpA9bc101Pg/sid5S/CBCpEYmIZbvoIsw//Snxf/kLCS+9NOhqR9arrz7nBFezWSE11bdv6o4h2J0n4boe9zwfyGq2c+z3zZiP29rX3LNx7PfNwZkk20t3WMOXgZkLJSKTJCIR2WJjaVq8GNsll5Dy05+i/eKLcEcUOl4muFrNDk5sb+bAb6o4sb0Zu9X35Ox9CDa9TsKt3GXFafecCOq0qwGbJNvZ6NvivD+hwKEXGgN+PxE5pGlORAXbxIk0XHABSS+8gDM+npZbb43cfQ8CoPzfTXz5Rwt6y6WM+OsbtN19I0O+Fs+x3zfhtENLrJ3GJgcNh1r554/PLp2Vd10M+dd43yqltyHYVrOdU+9ZaChz7fBqGKVn2FVx2BpVrxNBOybJ+trU520/oto8PbuersFa7yQ2VcO4O5M5+qoFOm/IqnGN2LPWD67a8GAjiUhEj5gYmoqK0H32GSnLl9N8++3YR40Kd1QBV/7vJo6/6ur3adMZ0NotfPWymZoxFmz1CqoDmmPb+KI2BqOtFTp977u+7M1ek1FPQ7B18RqO/K6J5nJ7+zGwmBy0nLKTOFTnWsqoy0RQfbLi82oLPe1H9Na/v0DRqSiKBkudjf8sr8MwVKG10nXsbIxOYlP1fv1MRWSTpjkRdexf+xoNjz1GbGkpiS+84NoVLgqU/7uJfy2t4Z8/ruFfS2so/7f3vWq+/KPn4IOThqnkmnfSWAbWBpW2RpXWWjsnKuPIjus+UMHb/j/gGmqt0eAxCVejgYShWiw1HcuMK+3Ds6G1xoEKaHSeE0E1Otf8JF+b+nqKx95yNuEoiganQ0XRaNFoFVTV2R6jE41WYdydMux6IJNEJKKTXk/zggVYp00jpbgY3eHD4Y6oVx21HLU9Z6p2OP6qxSMZdSwqqnbJq42xw0huOwWqiuoAnOC0gcWhJV7re5NVT0OwNYrG9bqdRgsoiqvmpbbByBsTMYzQE5euxTBCz8gbE4k16AK+2oKiaHBaVC57PI2UEXpiUxVSRuhdj4f7vzqEiFzSNCeimn3sWBpWrCDxxReJffddmu+4A3SB+7UO1HbhXWs5nY/nXJHk3laio+bRVVXiRLKaD1CV8vX2pNE/3ibhmpJtKFrAdnaLUVVVUbQK+mSlx0mygV5toaMJLmV4LFOelMQzmEiNSEQ/nY7mu+7Ces01rtrRwYMBedlAbhfetZbT9bjHthJevserEiYwpOVTNO05pNWhIU7rPY686/o2yTRrSixxGR03VV1JSIH4DG2v69T11NTXdbWFnuLRJUgTnHCRRCQGDPvo0TQ8/jix//43iZs2gc3m1+tV7rLgtHP2U6IBp911vK+UHippHcc7N3Pp4z2TkaKD5NEKLYYcDNZyFD1UWuMYmuA5UAF6HzXXk1iDjjE3J5F1WRxxRi3xRi2Zl8Ux+uakXieu+rraQv41hm7JKO+6GL75/PnSBCcAaZoTA41WS/Mdd6A9doyUxx6j+eabsU+Y0K+XqiuzYC5T3QtwxmVDfJqetn7s7zP8+jj3SLiux6F7M5c+3rWeW9JQHROLUrGaHZT95kpy9/2BpmE3cqY6jslZ9aTm61A0rgEFHX03/RFr0DHiur7vJurrenv51xjIv8bzmHFUAlOezOjzPcXAI4lIDEiOkSNpePxxEn79a+Lee4+mH/4QYnxvsqr8uBnz0U4JRwXLaUC1Ycj3/Nh07kdqKLfQ8uXZ586bpWfUf6eQc4XrS/7LP7oGLCg6VxLqOD6iMMHdR9SxqGjHthJf/sPMyTfbAAWjNZ6E2AYS8hPIv7QFZxsBXWVbiHCQ31wxcGm1tNx2G9rjxzE8/jitc+di+/rXfbr02Cvet5C2VJ3dLhzO9iM57WA+Y8NR73n+6b/bOP33GjSxoE8BvQHamgAnfPW6herdNkbPTexxW4mazy3tScjlq5TpDD/0Hpqxt/arBiNEJJJEJAY8x4gRmB9/nITf/Ma1dtt///c5r3H2sPyaouAxaq5zP1LXJOTxelawVp19rLb/1/SVgwMbG5lYlOy1mWvfGrPH4zadgQZ7LNbDDYD0p4iBQRKRGBw0GlpuvRXtiRPEHz0KQ4YAPS9Ro4kBh5dKkaZL615bo+r3kB97i+eW251j8uaE4Rt8nQrgfP9uLESEkFFzYlBx5OXB6NEA7rk7nVejdj1uY+Q871tIdz0ek6xAAJZB60g6XWPyJjY+EX1C30bGCRHJJBGJQctj7g7tqwk4XbWTrAsTOW+W5/pm583Sk3VhosexrClxaHSAE7Sp/QxEdY2a8xZTT1sjXDC3vzcTIvKEtGlu//79bNmyBafTycyZMyksLPR4vqmpiU2bNlFZWYler2fhwoXk5eX5dK0QfdXbEjWmoxbO/MMGGle/kKrCmX/YSB9tIX302cEKsQYtI29MonKXhbgMLWc+taDW9z2WjkmgXWPSJyrYmtVum8Mdea2esj+7amhdk6MQ0SZkNSKn00lJSQmPPPII69at44MPPqC8vNzjnNdff53hw4fz9NNPs3jxYrZu3erztUL0VUyyxr0qQAfXEjUayl5pRlVdSQjOJqOyV5q7vU6sQUve7ERG3ZDEtOIMRsyN63ECqzeJuYp7Eqi3mHQJkDpax5jbzjYLqnZXH9aRra1Uftw9JiGiic+J6KWXXuLLL7/s943KysrIzs4mKysLnU7H1KlT2bNnj8c55eXlTJw4EYBhw4ZRXV1NfX29T9cK0VcjChNQNIrHEjUdc3ccLSpdKksoCjhazj2ZNeeKJKatyeCyFWkYJ+hJG6snbbyepOEKiha08aBPUtAluuYADZsZx4GN9Xz0cxM2ixNVxWtMPQ0p7+m4ENHC57/bHA4HK1euxGAwcOWVV3LllVdiNBp9vpHJZPI432g0cvToUY9z8vPz2b17N2PHjqWsrIzq6mpMJpNP13YoLS2ltLQUgFWrVpGREVkzt3U6XcTF1BfRHj+AtqKC1NRUUlMhaamBQ7+rxdpoJzZZx7ibjaTmxvF5YgsOq93zTzUn6BN1pKam+najVEi5M4UT7zVgNTuINWhJnRvHsTfr3ffLvSaJg78x4XQ43RNZNRqFhCE6nDY8YtpvM3u9jdOG7zFFEJ1OG/W/S9H+eYiU+H1ORPPnz+e2225j3759/POf/+SPf/wjo0ePZvr06Vx++eXExfWwzW+7rs0NQLf2+cLCQrZu3crSpUvJy8tjxIgRaDTdmyq8XduhoKCAgoIC9+OamhpfihcyGRkZERdTX3SNv+qTFg780oy9SUWXpDDxRwYyv57QyyuEx6e/qeXLV1yTgzJaDrtXPCAZxt3VuY/FQn29hfPnxnHw+SZU59lmOUWB8+fGUV9f36d7Z07XcnbxOJvH/Q5srMNhd7iTELTXgnQqF92T6hGTRg8OL4unavT0OaZIYLenRPVnAQbe57mvhg4dGpA4+jRYQaPRcOmll3LppZdy8uRJnn32WTZu3MgLL7zAN77xDebOnUt6errXa41GI7W1Z7c0rq2tJS0tzeOchIQEioqKANeHcfHixWRmZtLW1nbOa0XoVX3Swp7iBveXtK1VZU9xA5NXEFHJqHMS6nD67zagwZWMvEgfHcf4u119Qo4WFW2Cwqh5iR4DFQKhL3v6jJwXz5Gt3ZvhehpqLkS06NNghZaWFv7xj3+wYsUKiouLGTVqFCtWrGDdunXExcXx1FNP9XjtyJEjOX36NFVVVdjtdnbu3MmkSZM8zmlubsbevtvmjh07GDduHAkJCT5dK0LvwC/NXjv0D/zSswmp6pMW/j7/NH+9/jRvzT3NvvUmLHWh21W1axLqcPrvNg5srKfpVPfnm061UfF3C1q9QlKOjvHzkwOehKD3ARNdZV2YyJjb4tHGu9aq08bDmNtk1JyIfj7XiNauXcvHH3/MuHHjmDVrFpMnT0avPzvP4tZbb+W2227r8XqtVsv8+fNZuXIlTqeTGTNmkJuby/bt2wGYPXs2FRUVbNiwAY1GQ05ODgsWLOj12sEsEprE7E3eO/TtnSZiVn3Swn9+2uCe9OmwQUWpleaKOiY9nEZcWt9nEFjq7Jzc3oq1zklsmobc2fE9vs65El7HJNYJC5LdI9eaTrWx7xkztO8i0XLGyb5nzFx8b/ctDvzV22Kn3mRdmOj6L3VUVDbHCeGNonrrgPHiz3/+M9OnT++1U9RqtRIbG1nrX506dSrk92z40sqhFxqx1juJTdUw7s5k9z4rgWhT7tok1vH/yStSgp6MOsdfOv8MlmrVNelSAUXjiiV+iMLMX2UDsOOHZ2itPLuVAgAqKDEwZm4So+f1bSM0S52dTzeacdhcX9iqU0WrV5hQZOiWjDrOPbPL6lmGlkPuf+uTPLdbAPjPz2o81oXrEJsJlz0c+I7dnpYZ6s2x1JlRn4iuuUb6iMIt6vqI/ud//uec50RaEgqHhi+t/Gd5HU6HiqJosNTZ+M/yuoBu+tVbk9jMX4WmVmSpsxObDpZq3Ct4tm+2ycQfnV1+xl076lxzUgAHWOvOvTZO19qPrdXpTkIAikbBYVM5ub3VI6kd/mMdR7ecewM7W4sKTmj40k7TqTaShsZ4TUJwdtHS/iSO3vi6p48QA5Us8RNgh15odCchAEXR4HSoHHqhMWD38KVJLNhObm+l4aT3+x1+rcH9b11Se6CdT1UBLcSm9f7r11GjMR1qo6XKgelQG6f/ZcVp97yvolE8kpqvSQhwNxmqdtzrzPWmt/XphBD9I6tvB5i13ulOQh0URYO1PgArY7bTJSnYWj2Tkap2+tIPgo6aSZnFihrXRvMZO7R4P7dhLxx9pRFtqhNrXaflaTrlj5SROnJn9z7a6+T21m61H0Wr0lrtIGnY2Z+x6lQ9ktrRrT0nobghCtozrlpU58VKdfFn15nTxLq2bfBm39NmVzliQB/juT6d1GqE6B+pEQVYbKoGVfVMOqrq6isKlIk/Mrib41yv76oRdW4SC6TONZOm0zZMh9owfdrDN3W7k/9s4uCGlu5f6DoYVhDr00AFa53TnYQ6JGTqUB2u5AO4+4g8klovFUNFo2HSkmw0Wlz9WlrQJSgomrPDpkfd3EuC7HjtNrC1uR70NNxaCOEbSUQBNu7OZDRaxZ2MVNWJRqsw7s6+dcr3JvPrCUxekUL8EAVdnGtwQDAHKnStmTjtKrYeakMdWk52etA+mAFAFwcXL0n3abRcbJrGnXDcL6WFodPiSB8XQ0KmlvRxMd0HKvRSMTxvWiyZ4xIxDNehS3DVhDoqsB3Dpj2GSZ/dA8/j3wC0eV4nhOgfaZoLsJThsVz2eFqnUXN6j1FzgZL59YSQDUzoWjOx1LT/9a/B61482mRweOsSU8DhY9cNQO7seBrKbN1GyI2Yk9hrIht9W5zXPqKEXIXz5yRCY8M5h013DJMG+PcjNTjak46iOTsoAzjncGshxLlJIgqClOGxTHly4IwgjE3T0HzGfrZG1Obqn0o8T4vF7PBIOtpkMI6Npeoja/ckpYK2D3NC49J0TCgy+DxnqMMF16cBda6+ovYKVfrFGi75sdF1baNrpNqEBcmdRr9pexz9pk1QsFvb++SUTslIA0lDdX6PmhNisJNEJM6pc80EQNEDbRA/REviUNevkN3ioK1OJT7L1X6VkAstX3V6kfZ5RBMWJ/Xp3nFpuj7PNQJXMrrg+t7P8XXY9Kh5ia515zrmbeFqpht/d1JQVlsQYrCRhm1xTh01k/RxMSSdpyf7ijgMo/TuPhPVqRKTqOXiB1PcfTe5VyYxfnECuqT2AQFJcNGDSeR8I3B9ZaHiWncuidg0BW0MxKYpkoSECCCpEQmfdNRMOmZi97TMTte+sPP/y/uiotEmfXQclz0qiUeIYJBEJPqlv01mQgjRlSQiISKM1eygcpeFtkaVmGSFrClxxBq6jh0XYuCQRCREBLGaHRz7fRNOO6ABSw00nWxi5I1JkozEgCWDFYSIIJW7LO4kBK7/O+2u40IMVJKIhIggbY1q90+lpv24EAOUJCIhIkhMstJ9IrCz/bgQA5QkIiEiSNaUODQ6ziYjJ2h0ruNCDFQyWEGIfgrG6LZYg5aRNybJqDkxqEgiEqIfgjm6LdagJW92YmACFSIKSNOcEP0go9uECBxJREL0g4xuEyJwJBEJ0Q8yuk2IwAlpH9H+/fvZsmULTqeTmTNnUlhY6PF8S0sLzz77LLW1tTgcDq677jpmzJgBwKJFi4iLi0Oj0aDValm1alUoQxfCQ9aUOJpOnu0jktFtQvRfyBKR0+mkpKSERx99FKPRyMMPP8ykSZPIyclxn/O3v/2NnJwcHnroIcxmM0uWLOHKK69Ep3OFWVxcjMFgCFXIQvRIRrcJETghS0RlZWVkZ2eTlZUFwNSpU9mzZ49HIlIUBYvFgqqqWCwWkpKS0Gik9VBEJhndJkRghCwRmUwmjEaj+7HRaOTo0aMe51x77bWsXr2au+++m9bWVn784x97JKKVK1cCMGvWLAoKCrzep7S0lNLSUgBWrVpFRkZGoIviF51OF3Ex9UW0xw+graggNTU13GH4RavVRn0ZdDpt1P8uRfvnIVLiD1kiUtXuo4kUxbNj9+OPPyY/P5/ly5dTWVnJE088wdixY0lISOCJJ54gPT2dhoYGnnzySYYOHcr48eO7vWZBQYFHkqqpqQl8YfzQsbFctIr2+AGGOBzU19eHOwy/OFKjvwx2e0rU/y5F++fB3/iHDh0akDhC1u5lNBqpra11P66trSUtLc3jnHfeeYfLL78cRVHIzs4mMzOTU6dOAZCeng5ASkoKkydPpqysLFShCyGECKKQJaKRI0dy+vRpqqqqsNvt7Ny5k0mTJnmck5GRwYEDBwCor6/n1KlTZGZmYrFYaG1tBcBisfDJJ5+Ql5cXqtCFEEIEUcia5rRaLfPnz2flypU4nU5mzJhBbm4u27dvB2D27NnccMMNbNy4kfvvvx+AW265BYPBQGVlJU8//TQADoeDadOmcdFFF4UqdCGEEEGkqN46bwaQjqY9X1nq7Jzc3oq1zklsmobc2fHEpQUuXw/2NuVIMOTEiajvXzmWOjPqy3DNNdJHFG6R0kcki552Yqmz8+lGMw6biqJRaD5jp6HMxoQiQ0CTkRBCiLNkkk4nJ7e3upMQgKJRcNhUTm5vDXNkQggxcEki6sRa53QnoQ6KRsFa13VRMSGEEIEiiaiT2DQNqtOzy0x1qsSmyY9JCCGCRb5hO8mdHY9Wr7iTkepU0eoVcmfHhzkyIYQYuKQHvpO4NB0TigxBHTUnhBDCk3zDdhGXpmP0vORwhyGEEIOGNM0JIYQIK0lEQgghwkoSkRBCiLCSRCSEECKsJBEJIYQIK0lEQgghwkoSkRBCiLCSRCSEECKsJBEJIYQIK0lEQgghwkoSkRBCiLCSRCSEECKsJBEJIYQIK0lEQgghwiqk20Ds37+fLVu24HQ6mTlzJoWFhR7Pt7S08Oyzz1JbW4vD4eC6665jxowZPl0rhBAiOoWsRuR0OikpKeGRRx5h3bp1fPDBB5SXl3uc87e//Y2cnBzWrFnDY489xrZt27Db7T5dK4QQIjqFLBGVlZWRnZ1NVlYWOp2OqVOnsmfPHo9zFEXBYrGgqioWi4WkpCQ0Go1P1wohhIhOIUtEJpMJo9Hofmw0GjGZTB7nXHvttVRUVHD33Xdz//33c/vtt6PRaHy6VgghRHQKWR+RqqrdjimK4vH4448/Jj8/n+XLl1NZWckTTzzB2LFjfbq2Q2lpKaWlpQCsWrWKjIyMAEQfODqdLuJi6otojx9Am51Nit0e7jD8cplOi92eEu4w/DIQfpeivQyREn/IEpHRaKS2ttb9uLa2lrS0NI9z3nnnHQoLC1EUhezsbDIzMzl16pRP13YoKCigoKDA/bimpibAJfFPRkZGxMXUF9EeP0gZIoWUIfz8jX/o0KEBiSNkTXMjR47k9OnTVFVVYbfb2blzJ5MmTfI4JyMjgwMHDgBQX1/PqVOnyMzM9OlaIYQQ0SlkNSKtVsv8+fNZuXIlTqeTGTNmkJuby/bt2wGYPXs2N9xwAxs3buT+++8H4JZbbsFgMAB4vVYIIUT0U1RvHTADyKlTp8IdgofBXpWPBFKGyCBlCL9B1zQnhBBCeDPga0RCCCEim9SIQuyhhx4Kdwh+ifb4QcoQKaQM4Rcp8UsiEkIIEVaSiIQQQoSVJKIQ6zzZNhpFe/wgZYgUUobwi5T4ZbCCEEKIsJIakRBCiLCSRCSEECKsQrpD60B2rh1k//znP/PPf/4TcG0SWF5eTklJCUlJSRGz+6w/ZVi0aBFxcXFoNBq0Wi2rVq0KQwmifxdgf+KPlvegqamJTZs2UVlZiV6vZ+HCheTl5fl0baj4U4ZIeB82btzI3r17SUlJYe3atd2eV1WVLVu2sG/fPmJjYykqKuL8888HwvQeqMJvDodDXbx4sXrmzBnVZrOpDzzwgHry5Mkez9+zZ4/62GOP9evaYPGnDKqqqkVFRWpDQ0MoQu2RL2V47bXX1F//+teqqqpqQ0ODetttt6k2my0i3gd/4lfV6HkPtm3bpr766quqqqpqeXm5umLFCp+vjfQyqGpkvA+fffaZeuzYMfW+++7z+vxHH32krly5UnU6nerhw4fVhx9+WFXV8L0H0jQXAH3dQfaDDz7gG9/4Rr+uDRZ/yhApon0XYH/ijxS+lKG8vJyJEycCMGzYMKqrq6mvr4+I98DfMkSK8ePHk5SU1OPzH374IdOnT0dRFMaMGUNzczN1dXVhew8i5zc4ivVlB1mr1cr+/fuZMmVKn68NJn/K0GHlypU8+OCD7o0JQy3adwH2J/4O0fAe5Ofns3v3bsD1pV9dXY3JZIqI9wD8K0OHcL8P52IymTw2xOsoY7jeA+kjCgC1DzvIfvTRR1xwwQXuv1b6cm0w+VMGgCeeeIL09HQaGhp48sknGTp0KOPHjw9avN74UoZA7AIcLP7En5CQEDXvQWFhIVu3bmXp0qXk5eUxYsQINBpNRLwH4F8ZIDI+C+fSUxnD9R5IIgqAvuwg+8EHHzBt2rR+XRtM/pQBID09HYCUlBQmT55MWVlZyD98odoFOFj8iX/UqFFR8x4kJCRQVFQEuL4QFy9eTGZmJm1tbWF/D8C/MkBkfBbOxWg0emz/0FFGu90elvdAmuYCwNcdZFtaWjh48KDHc5Gy+6w/ZbBYLLS2trr//cknn7hHEIVStO8C7E/80fQeNDc3Y7fbAdixYwfjxo0jISEhIt4Df8sQKe/DuUyaNIn3338fVVU5cuQICQkJpKWlhe09kJUVAmTv3r289NJL7h1kr7/+eo/dZwHeffdd9u/fz7333nvOa8Ohv2WorKzk6aefBsDhcDBt2rSILYPJZGLjxo3U1dUBMGfOHKZPn97jtdESfzS9B0eOHGHDhg1oNBpycnJYsGCBu5k3Et4Df8oQKe/DM888w8GDB2lsbCQlJYW5c+e6E+fs2bNRVZWSkhI+/vhjYmJiKCoqYuTIkT2WPdgkEQkhhAgraZoTQggRVpKIhBBChJUkIiGEEGEliUgIIURYSSISQggRVpKIhBBChJUkIiGEEGEliUgIIURYSSISIsR++9vf8te//jVgr/fcc8/x8ssvA/Dwww9z8uTJgL22EKEgiUiIADh+/Dg//elP+f73v8/DDz/ssaBkZ2azmffee49Zs2YFJY7rrruOV155JSivLUSwSCISwk+1tbX87Gc/Y86cObz44otkZWXx2muveT333Xff5eKLLyYmJqbbcw6Hw+9YJk2axGeffeZei06IaCDbQAjhp23btjFz5kz3KsVTp07lD3/4g9dz9+3bx4wZM9yPFy1axKxZs/jXv/7FqVOn+PWvf82bb77Jjh07aGhowGg0cvPNN3PZZZe5rzl+/DibN2/m9OnTXHzxxR77xcTExHD++efz8ccfc/XVVwenwEIEmNSIhPBDS0sLH374ITNnznQfU1UVvV7v9fwTJ04wdOhQj2MffPABDz30EFu3bkWr1ZKVlcWKFSvYunUrN954I7/85S/dNRy73c6aNWu48sorefHFF7niiivcO4V2GDZsGF999VWASypE8EiNSAg/fPrpp9jtdh544AH3MZvNxuTJk72e39LSQnx8vMexb37zmx7bNl9xxRXuf0+dOpXXX3+dsrIyJk+ezJEjR3A4HHzrW99CURSmTJnCX/7yF4/Xi4+Pl6Y5EVUkEQnhh6qqKiZNmsTSpUvdx372s59x0UUXeT0/MTHRvXFah85JCOC9997jL3/5C9XV1YBrg7XGxkYA6urqSE9P92iO63p9a2sriYmJ/S6TEKEmTXNC+MFutxMbG+t+XFVVxbFjx3rc1TI/P5/Tp0/3+HrV1dU8//zz3HHHHbz44ots3bqV3NxcOrYNS0tLw2Qy0Xkbsc5bOwNUVFSQn5/vT7GECClJREL4YeTIkRw8eBCTyURNTQ3r16/npptucu842tXFF1/MwYMHe3w9q9WKoigYDAYA3nnnHY95QWPGjEGj0fDWW2/hcDjYvXs3ZWVl7udtNhtffPEFX//61wNUQiGCT5rmhPDDhAkTuPTSS1myZAnJycnMmTOHgoKCHs+fPn06y5Yto62tzesQ7pycHL797W/zk5/8BI1Gw/Tp07ngggvcz+t0Oh544AGef/55Xn75ZS6++GKPEXUffvghX/va10hPTw9sQYUIItkqXIgQ++1vf0tKSgrf+ta3Av7ajzzyCAsWLCAvLy/gry1EsEgiEkIIEVbSRySEECKsJBEJIYQIK0lEQgghwkoSkRBCiLCSRCSEECKsJBEJIYQIK0lEQgghwur/Bw2IvNkLL9CfAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 432x360 with 3 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from matplotlib.patches import ConnectionPatch\n",
    "\n",
    "fig = plt.figure(figsize=(6, 5))\n",
    "plt.subplots_adjust(bottom = 0., left = 0, top = 1., right = 1)\n",
    "\n",
    "sub1 = fig.add_subplot(2,2,1) # two rows, two columns, fist cell\n",
    "sub1.scatter(d['length'], d['width'], color = 'red')\n",
    "sub1.set_xlim(0.80, 0.85)\n",
    "sub1.set_ylim(0.88, 0.91)\n",
    "sub1.set_ylabel('width', labelpad = 5)\n",
    "\n",
    "sub2 = fig.add_subplot(2, 2, 2)\n",
    "sub2.scatter(d['length'], d['width'], color = 'blue')\n",
    "sub2.set_xlim(0.85, 0.90)\n",
    "sub2.set_ylim(.92, 0.96)\n",
    "\n",
    "sub3 = fig.add_subplot(2,2,(3,4)) # two rows, two colums, combined third and fourth cell\n",
    "sub3.scatter(d['length'], d['width'], color = 'darkorchid', alpha = .7)\n",
    "#sub3.set_xlim(0.80, 0.85)\n",
    "#sub3.set_ylim(0.88, 0.91)\n",
    "sub3.set_xlabel(r'$\\theta$ (rad)', labelpad = 5)\n",
    "sub3.set_ylabel('y', labelpad = 5)\n",
    "\n",
    "sub3.fill_between((0.80, 0.85), 0.8, 1, facecolor= \"red\", alpha = 0.2)\n",
    "sub3.fill_between((0.85, 0.90), 0.8, 1, facecolor= \"blue\", alpha = 0.2)\n",
    "\n",
    "con1 = ConnectionPatch(xyA = (0.8, 0.88), coordsA=sub1.transData,\n",
    "                       xyB=(0.80, 0.91), coordsB=sub3.transData, color = 'red')\n",
    "fig.add_artist(con1)\n",
    "\n",
    "con2 = ConnectionPatch(xyA = (0.85, 0.88), coordsA=sub1.transData,\n",
    "                       xyB=(0.85, 0.91), coordsB=sub3.transData, color = 'red')\n",
    "fig.add_artist(con2)\n",
    "\n",
    "con3 = ConnectionPatch(xyA = (0.85, 0.92), coordsA=sub2.transData,\n",
    "                       xyB=(0.85, 0.91), coordsB=sub3.transData, color = 'blue')\n",
    "fig.add_artist(con3)\n",
    "\n",
    "con4 = ConnectionPatch(xyA = (0.90, 0.92), coordsA=sub2.transData,\n",
    "                       xyB=(0.90, 0.95), coordsB=sub3.transData, color = 'blue')\n",
    "fig.add_artist(con4)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 164,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['symboling', 'normalized-losses', 'make', 'aspiration', 'num-of-doors',\n",
       "       'body-style', 'drive-wheels', 'engine-location', 'wheel-base', 'length',\n",
       "       'width', 'height', 'curb-weight', 'engine-type', 'num-of-cylinders',\n",
       "       'engine-size', 'fuel-system', 'bore', 'stroke', 'compression-ratio',\n",
       "       'horsepower', 'peak-rpm', 'city-mpg', 'highway-mpg', 'price',\n",
       "       'city-L/100km', 'horsepower-binned', 'diesel', 'gas'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 164,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "d.columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 172,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.patches.ConnectionPatch at 0x2d805a44be0>"
      ]
     },
     "execution_count": 172,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x360 with 3 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from matplotlib.patches import ConnectionPatch\n",
    "\n",
    "fig = plt.figure(figsize=(6, 5))\n",
    "plt.subplots_adjust(bottom = 0., left = 0, top = 1., right = 1)\n",
    "\n",
    "sub1 = fig.add_subplot(2,2,1) # two rows, two columns, fist cell\n",
    "sub1.scatter(d['length'], d['width'], color = 'red')\n",
    "sub1.set_xlim(0.80, 0.85)\n",
    "sub1.set_ylim(0.88, 0.91)\n",
    "sub1.set_ylabel('width', labelpad = 5)\n",
    "\n",
    "sub2 = fig.add_subplot(2, 2, 2)\n",
    "sub2.scatter(d['length'], d['width'], color = 'blue')\n",
    "sub2.set_xlim(0.85, 0.90)\n",
    "sub2.set_ylim(.92, 0.96)\n",
    "\n",
    "sub3 = fig.add_subplot(2,2,(3,4)) # two rows, two colums, combined third and fourth cell\n",
    "sub3.scatter(d['length'], d['width'], color = 'darkorchid', alpha = .7)\n",
    "#sub3.set_xlim(0.80, 0.85)\n",
    "#sub3.set_ylim(0.88, 0.91)\n",
    "sub3.set_xlabel(r'$\\theta$ (rad)', labelpad = 5)\n",
    "sub3.set_ylabel('y', labelpad = 5)\n",
    "\n",
    "sub3.fill_between((0.80, 0.85), 0.8, 1, facecolor= \"red\", alpha = 0.2)\n",
    "sub3.fill_between((0.85, 0.90), 0.8, 1, facecolor= \"blue\", alpha = 0.2)\n",
    "\n",
    "con1 = ConnectionPatch(xyA = (0.8, 0.88), coordsA=sub1.transData,\n",
    "                       xyB=(0.80, 0.91), coordsB=sub3.transData, color = 'red')\n",
    "fig.add_artist(con1)\n",
    "\n",
    "con2 = ConnectionPatch(xyA = (0.85, 0.88), coordsA=sub1.transData,\n",
    "                       xyB=(0.85, 0.91), coordsB=sub3.transData, color = 'red')\n",
    "fig.add_artist(con2)\n",
    "\n",
    "con3 = ConnectionPatch(xyA = (0.85, 0.92), coordsA=sub2.transData,\n",
    "                       xyB=(0.85, 0.91), coordsB=sub3.transData, color = 'blue')\n",
    "fig.add_artist(con3)\n",
    "\n",
    "con4 = ConnectionPatch(xyA = (0.90, 0.92), coordsA=sub2.transData,\n",
    "                       xyB=(0.90, 0.95), coordsB=sub3.transData, color = 'blue')\n",
    "fig.add_artist(con4)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 170,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.collections.PathCollection at 0x2d805900700>"
      ]
     },
     "execution_count": 170,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.scatter(d['horsepower'], d['price'], color = 'darkorchid', alpha = .7)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 171,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.collections.PathCollection at 0x2d80595d7c0>"
      ]
     },
     "execution_count": 171,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.scatter(d['city-mpg'], d['highway-mpg'], color = 'darkorchid', alpha = .7)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 185,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.patches.ConnectionPatch at 0x2d8075fddf0>"
      ]
     },
     "execution_count": 185,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x360 with 3 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from matplotlib.patches import ConnectionPatch\n",
    "\n",
    "fig = plt.figure(figsize=(8, 5))\n",
    "#plt.subplots_adjust(bottom = 0., left = 0, top = 0, right = 1)\n",
    "\n",
    "plot1 = fig.add_subplot(2,2,1) # two rows, two columns, fist cell\n",
    "plot1.scatter(d['city-mpg'], d['highway-mpg'], color = 'red')\n",
    "plot1.set_xlim(15, 20)\n",
    "plot1.set_ylim(17, 25)\n",
    "plot1.set_ylabel('highway-mpg', labelpad = 5)\n",
    "\n",
    "plot2 = fig.add_subplot(2, 2, 2)\n",
    "plot2.scatter(d['city-mpg'], d['highway-mpg'], color = 'blue')\n",
    "plot2.set_xlim(25, 30)\n",
    "plot2.set_ylim(25, 35)\n",
    "\n",
    "plot3 = fig.add_subplot(2,2,(3,4)) # two rows, two colums, combined third and fourth cell\n",
    "plot3.scatter(d['city-mpg'], d['highway-mpg'], color = 'darkorchid', alpha = .7)\n",
    "plot3.set_xlabel('city-mpg', labelpad = 5)\n",
    "plot3.set_ylabel('highway-mpg', labelpad = 5)\n",
    "\n",
    "plot3.fill_between((15, 20), 10, 60, facecolor= \"red\", alpha = 0.2)\n",
    "plot3.fill_between((25, 30), 10, 60, facecolor= \"blue\", alpha = 0.2)\n",
    "\n",
    "\n",
    "conn1 = ConnectionPatch(xyA = (15, 17), coordsA=plot1.transData,\n",
    "                       xyB=(15, 20), coordsB=plot3.transData, color = 'red')\n",
    "fig.add_artist(conn1)\n",
    "\n",
    "conn2 = ConnectionPatch(xyA = (20, 17), coordsA=plot1.transData,\n",
    "                       xyB=(20, 20), coordsB=plot3.transData, color = 'red')\n",
    "fig.add_artist(conn2)\n",
    "\n",
    "conn3 = ConnectionPatch(xyA = (25, 25), coordsA=plot2.transData,\n",
    "                       xyB=(25, 30), coordsB=plot3.transData, color = 'blue')\n",
    "fig.add_artist(conn3)\n",
    "\n",
    "conn4 = ConnectionPatch(xyA = (30, 25), coordsA=plot2.transData,\n",
    "                       xyB=(30, 30), coordsB=plot3.transData, color = 'blue')\n",
    "fig.add_artist(conn4)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "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"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}