Final Pitch Notebook.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 16,
   "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>budget</th>\n",
       "      <th>genres</th>\n",
       "      <th>id</th>\n",
       "      <th>imdb_id</th>\n",
       "      <th>popularity</th>\n",
       "      <th>release_date</th>\n",
       "      <th>revenue</th>\n",
       "      <th>runtime</th>\n",
       "      <th>title</th>\n",
       "      <th>vote_average</th>\n",
       "      <th>vote_count</th>\n",
       "      <th>gross_profit</th>\n",
       "      <th>ROI (%)</th>\n",
       "      <th>qty_of_genres</th>\n",
       "      <th>weighted_budget</th>\n",
       "      <th>weighted_ROI</th>\n",
       "      <th>release_year</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>13200000</td>\n",
       "      <td>['Comedy', 'Drama', 'Romance']</td>\n",
       "      <td>19404</td>\n",
       "      <td>tt0112870</td>\n",
       "      <td>17.437</td>\n",
       "      <td>1995-10-20</td>\n",
       "      <td>100000000</td>\n",
       "      <td>190.0</td>\n",
       "      <td>Dilwale Dulhania Le Jayenge</td>\n",
       "      <td>8.8</td>\n",
       "      <td>2214</td>\n",
       "      <td>86800000.0</td>\n",
       "      <td>657.58</td>\n",
       "      <td>3</td>\n",
       "      <td>4400000.00</td>\n",
       "      <td>219.19</td>\n",
       "      <td>1995</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>25000000</td>\n",
       "      <td>['Drama', 'Crime']</td>\n",
       "      <td>278</td>\n",
       "      <td>tt0111161</td>\n",
       "      <td>35.028</td>\n",
       "      <td>1994-09-23</td>\n",
       "      <td>28341469</td>\n",
       "      <td>142.0</td>\n",
       "      <td>The Shawshank Redemption</td>\n",
       "      <td>8.7</td>\n",
       "      <td>15045</td>\n",
       "      <td>3341469.0</td>\n",
       "      <td>13.37</td>\n",
       "      <td>2</td>\n",
       "      <td>12500000.00</td>\n",
       "      <td>6.68</td>\n",
       "      <td>1994</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>6000000</td>\n",
       "      <td>['Drama', 'Crime']</td>\n",
       "      <td>238</td>\n",
       "      <td>tt0068646</td>\n",
       "      <td>29.433</td>\n",
       "      <td>1972-03-14</td>\n",
       "      <td>245066411</td>\n",
       "      <td>175.0</td>\n",
       "      <td>The Godfather</td>\n",
       "      <td>8.7</td>\n",
       "      <td>11486</td>\n",
       "      <td>239066411.0</td>\n",
       "      <td>3984.44</td>\n",
       "      <td>2</td>\n",
       "      <td>3000000.00</td>\n",
       "      <td>1992.22</td>\n",
       "      <td>1972</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>11363000</td>\n",
       "      <td>['Comedy', 'Thriller', 'Drama']</td>\n",
       "      <td>496243</td>\n",
       "      <td>tt6751668</td>\n",
       "      <td>176.819</td>\n",
       "      <td>2019-05-30</td>\n",
       "      <td>201055038</td>\n",
       "      <td>132.0</td>\n",
       "      <td>Parasite</td>\n",
       "      <td>8.6</td>\n",
       "      <td>4751</td>\n",
       "      <td>189692038.0</td>\n",
       "      <td>1669.38</td>\n",
       "      <td>3</td>\n",
       "      <td>3787666.67</td>\n",
       "      <td>556.46</td>\n",
       "      <td>2019</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>22000000</td>\n",
       "      <td>['Drama', 'History', 'War']</td>\n",
       "      <td>424</td>\n",
       "      <td>tt0108052</td>\n",
       "      <td>19.641</td>\n",
       "      <td>1993-11-30</td>\n",
       "      <td>321365567</td>\n",
       "      <td>195.0</td>\n",
       "      <td>Schindler's List</td>\n",
       "      <td>8.6</td>\n",
       "      <td>9163</td>\n",
       "      <td>299365567.0</td>\n",
       "      <td>1360.75</td>\n",
       "      <td>3</td>\n",
       "      <td>7333333.33</td>\n",
       "      <td>453.58</td>\n",
       "      <td>1993</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     budget                           genres      id    imdb_id  popularity release_date    revenue  ...  vote_count gross_profit  ROI (%)  qty_of_genres  weighted_budget  weighted_ROI  release_year\n",
       "0  13200000   ['Comedy', 'Drama', 'Romance']   19404  tt0112870      17.437   1995-10-20  100000000  ...        2214   86800000.0   657.58              3       4400000.00        219.19          1995\n",
       "1  25000000               ['Drama', 'Crime']     278  tt0111161      35.028   1994-09-23   28341469  ...       15045    3341469.0    13.37              2      12500000.00          6.68          1994\n",
       "2   6000000               ['Drama', 'Crime']     238  tt0068646      29.433   1972-03-14  245066411  ...       11486  239066411.0  3984.44              2       3000000.00       1992.22          1972\n",
       "3  11363000  ['Comedy', 'Thriller', 'Drama']  496243  tt6751668     176.819   2019-05-30  201055038  ...        4751  189692038.0  1669.38              3       3787666.67        556.46          2019\n",
       "4  22000000      ['Drama', 'History', 'War']     424  tt0108052      19.641   1993-11-30  321365567  ...        9163  299365567.0  1360.75              3       7333333.33        453.58          1993\n",
       "\n",
       "[5 rows x 17 columns]"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#import libraries\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "%matplotlib inline\n",
    "import seaborn as sns\n",
    "\n",
    "df_profits = pd.read_csv('final_data.csv')\n",
    "df_profits.drop(columns='Unnamed: 0', inplace=True)\n",
    "df_profits.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Number of genres in total, many more comedy and drama movies\n",
    "fig, ax = plt.subplots(figsize=(10,5))\n",
    "plt.xticks(rotation=45)\n",
    "plt.bar(genre_and_count.keys(), genre_and_count.values());"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [],
   "source": [
    "#Preprocess rows in genres so that we can show each genre\n",
    "\n",
    "import ast #one example\n",
    "from tqdm import tqdm # progress bar\n",
    "\n",
    "#Fix data type of Genre Column\n",
    "df['genres'][0]\n",
    "res = ast.literal_eval(df['genres'][0]) \n",
    "\n",
    "df_profits = df_profits.reset_index(drop=True)\n",
    "\n",
    "res_list = [] #loop through\n",
    "for i in df_profits['genres']:\n",
    "    res = ast.literal_eval(i)\n",
    "    res_list.append(res)\n",
    "\n",
    "df_profits['genres'] = res_list"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x576 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# count of all genres\n",
    "genre_and_count ={}\n",
    "for genres in df_profits.genres:\n",
    "    for genre in genres:\n",
    "        genre_and_count[genre] = genre_and_count.get(genre, 1) + 1 \n",
    "\n",
    "#sum the weighted budget for each genre to average it by the number of individual genres in next cell\n",
    "genre_wbudget ={} \n",
    "for index in df_profits.index:\n",
    "    for genre in df_profits['genres'][index]:\n",
    "        budget = df_profits['weighted_budget'][index] \n",
    "        genre_wbudget[genre] = genre_wbudget.get(genre,0) + budget\n",
    "genre_wbudget\n",
    "\n",
    "# get average of the weighted budget by genre count\n",
    "genre_and_weight_budget = {}\n",
    "for genre, budget in genre_wbudget.items():\n",
    "    genre_and_weight_budget.update({genre:budget / genre_and_count[genre]})\n",
    "genre_and_weight_budget \n",
    "\n",
    "plt.figure(figsize=(12,8));\n",
    "plt.bar(genre_and_weight_budget.keys(),genre_and_weight_budget.values());\n",
    "plt.title('Genres and their weighted average budget');\n",
    "plt.xlabel('Genres');\n",
    "plt.ylabel('Average Budget');\n",
    "plt.xticks(rotation=45)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x576 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# trying to link genre to the ROI\n",
    "genre_roi_sum = {}\n",
    "for index in df_profits.index:\n",
    "    for genre in df_profits['genres'][index]:\n",
    "        roi = df_profits['weighted_ROI'][index] \n",
    "        genre_roi_sum[genre] = genre_roi_sum.get(genre,0) + roi    \n",
    "genre_weighted_roi = {}\n",
    "for genre, roi in genre_roi_sum.items():\n",
    "    genre_weighted_roi.update({genre: roi / genre_and_count[genre]})\n",
    "plt.figure(figsize=(12,8));\n",
    "plt.bar(genre_weighted_roi.keys(),genre_weighted_roi.values());\n",
    "plt.title('Genres and their weighted average ROI');\n",
    "plt.xlabel('Genres');\n",
    "plt.ylabel('Average ROI');\n",
    "plt.xticks(rotation=45)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAj8AAAE+CAYAAABiGHEPAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAALEgAACxIB0t1+/AAAADh0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uMy4yLjAsIGh0dHA6Ly9tYXRwbG90bGliLm9yZy8GearUAAAW1ElEQVR4nO3dfZClVX0n8O9hBgPyEnkJlBnMdtyJRbkRo04lrKWkQTC8OGViYIsKGzCoWWotQCWgwRFHRTdiYNUJW64QIiRs2AJZBRcxsECx6/uMioCgtjq4jCbKgEFeNjp69o/7NHbfvt1zu2d67vScz6eqq2+fe55zfvc8/XR/+7nP7VtqrQEAaMVuoy4AAGBHEn4AgKYIPwBAU4QfAKApwg8A0BThBwBoyvL5dD7wwAPr2NjYIpUCALD9bNiw4aFa66/0t88r/IyNjWX9+vXbryoAgEVSSnlgULunvQCApgg/AEBThB8AoCnCDwDQFOEHAGiK8AMANEX4AQCaIvwAAE0RfgCApgg/AEBThB8AoCnCDwDQFOEHAGiK8AMANEX4AQCaIvwAAE0RfgCApgg/AEBThB8AoCnCDwDQFOEHAGiK8AMANEX4AQCaIvwAAE1ZPuoCAGC+1q1bl4mJiVGXMbRNmzYlSVasWDHiSpKVK1fmzDPPHHUZIyX8ALDkTExM5Cv33JefPX3/UZcylGVP/HOS5B//ZbS/dpc98fBI599ZCD8ALEk/e/r+efLQ40ddxlD2vP+mJBl5vZN1tM41PwBAU4QfAKApwg8A0BThBwBoivADADRF+AEAmiL8AABNEX4AgKYIPwBAU4QfAKApwg8A0BThBwBoivADADRF+AEAmiL8AABNEX4AgKYIPwBAU4QfAKApwg8A0BThBwBoivADADRF+AEAmiL8AABNEX4AgKYIPwBAU4QfAKApwg8A0BThBwBoivADADRF+AEAmiL8AABNEX4AgKYIPwBAU4QfAKApwg8A0BThBwBoivADADRF+AEAmiL8AABNEX4AgKYIPwBAU4QfAKApwg8A0BThBwBoivADADRF+AEAmiL8AABNEX4AgKYIPwBAU4QfAKApwg8A0BThBwBoivADNGHdunVZt27dqMuA5u0Mx+Lykc4OsINMTEyMugQgO8ex6MwPANAU4QcAaIrwAwA0RfgBAJoi/AAATRF+AICmCD8AQFOEHwCgKcIPANAU4QcAaIrwAwA0RfgBAJoi/AAATRF+AICmCD8AQFOEHwCgKcIPANAU4QcAaIrwAwA0RfgBAJoi/AAATRF+AICmCD8AQFOEHwCgKcIPANAU4QcAaIrwAwA0RfgBAJoi/AAATRF+AICmCD8AQFOEHwCgKcIPANAU4QcAaIrwAwA0RfgBAJoi/AAATRF+AICmCD8AQFOEHwCgKcIPANAU4QcAaIrwAwA0RfgBAJoi/AAATRF+AICmCD8AQFOEHwCgKcIPANCUnSr8bN68OWeddVY2b968JOccdqxtmbN/24mJiZxwwgmZmJiY95yDth3Ur79t2Ppvu+22jI+P5/bbb5932/r163PUUUdlw4YNs44/qP5BbcOMNaiGYftdffXVGR8fzzXXXDNnHf3bDtpu0PiXXXZZxsfHc8UVV8zZb5i2j3/84xkfH8+NN944Z/3vfe97Mz4+nosvvviptg9+8IMZHx/PpZdeOme/YeY8//zzMz4+ngsuuGDOtkGPadCcr33tazM+Pp4zzjhj1j4Ak3aq8HPllVfm7rvvzlVXXbUk5xx2rG2Zs3/bCy+8MI8//nguvPDCec85aNtB/frbhq3/Pe95T5Lk3e9+97zb1q5dm5///Od5+9vfPuv4g+of1DbMWINqGLbfZZddliT50Ic+NGcd/dsO2m7Q+FdffXWSTFvvha7t+9///iTJJZdcMmf9n/zkJ5NkWmC5/vrrkyTXXnvtnP2GmfMzn/lMkuTOO++cs23QYxo052TIvP/++2ftAzBp+agLmLR58+bcfPPNqbXm5ptvzqmnnpoDDjhgycw57FjbMmf/ti996UuzcePGJMnGjRszMTGRlStXDjXnI488MmPb/fbbb0a/JNPaVq9ePVT9t912W7Zs2ZIk2bJlS26//fbUWodq22efffLYY48lSR577LFs2LAhL3rRi6aNPzExMaP+ydtT2370ox9tdaxBtR555JFDPabvfe970/pcc801WbVq1Yw6vvvd707b9l3veteM7Q466KAZ4/ef0bviiisyNja2oLW96KKLUmtNktRac+ONN+bRRx+dUccDDzwwre3iiy/O7rvvPq3t0ksvfWpdp/Z7wQteMG3O973vfTPm/OxnPzttuwsuuOCpbaa2jY+Pz3hMX/jCF2bMed99901re8UrXjGjzznnnBOASWXyB9MwVq1aVdevX78ohVxyySW56aabsmXLlixfvjwnnHBC3vjGNy7KXIsx57Bjbcuc/dvuscce034BjY2N5SMf+chQc951111P/YKe3Pawww6b0a/WOq3tkEMOyYMPPrjV+o8++uhpv9CWL+/l7GHa+h/X3nvvnU984hPTxn/1q189o/4kM9oeeuihrY41qNZbb711qMfU/0t7ct7+OibXbC794802/qB+ydbXtl8pJfM5/ocxW80LmXPY9RjGHXfckRNPPDFPPvnkwD8QWHomJiby45/UPP5bJ4+6lKHsef9NSZInDz1+pHXs9ZVrss/TykiPg4mJiey555657rrrFn2uUsqGWuuq/vatPu1VSvnTUsr6Usr6H/7wh4tTXZJbb7112l95t9xyy6LNtRhzDjvWtszZv23/X95Tf+Fubc7+vhs3bhzYr79t48aNQ9Xf/0tqy5YtQ7f1P67+rwc91o0bNw5sG2asQTUMMmy/QXUM80t7W+oYpq3f9g4+g2rbljmHXQ+A+drq01611g8n+XDSO/OzWIUcffTR084wHHPMMYs11aLMOexY2zJn/7aDzvwMO+cwZ36OOeaYrZ75ma3+hZ6dmO3MT79BZ1eS4c78DFvrMP2c+Zm7tm2Zc3ue+UmSFStWJEk+8IEPLHgMdh5nn312Nnz7n0ZdxpLz8z32zcpnHzzS4+Dss88e2dyTdpoLnk877bTstluvnGXLlj11vclSmXPYsbZlzv5t165dO+3+NWvWDD1nf981a9YM7NfftmbNmqHqP//886d9/da3vnXotv7H9Y53vGPG+IPqH9Q2zFiDahhkUL/Xve5109rOOOOMgXX0b/uyl71sxnaDxj/llFOmtZ166qkLXtvjj59+uv1Nb3rTwPqPO+64aW2rV6/Oq171qmltJ5100sB+/XOecMIJM+Z88YtfPK3tiCOOGNg26DENmrP/9H1/wF29enUAptppws8BBxyQY489NqWUHHvssYt+sfP2nnPYsbZlzv5tV61a9dQZj7GxsVmfwx0058qVK2dsO6hff9vKlSuHqv+oo4566uzD8uXLc+SRRw7dtmrVqqd+ge29994zLlBOMrD+QW3DjDWohmEfU384OfnkkwfW0b/t2972thnbDRq/P5ycfvrpC17b8847L6WUJL0zMKtXrx5Y/5vf/OZpbeecc07OOuusaW2vf/3rB/brn/Pcc8+dMefkK7gmvfOd7xzYNugxDZrz8ssvn9bWf02Xi52BfjtN+El6Zyie97zn7ZCzPosx57Bjbcuc/duuWbMme+2116xnfeaac9C2g/r1tw1b/+Rf7lPPpAzbtnbt2uy2224Dz9TMVf+gtmHGGlTDsP0mA8rk/5iZrY7+bQdtN2j8yYAydb0XurZveMMbkvTOwMxV/+QZlqlnTSbP/px00klz9htmzskzPUccccScbYMe06A5J4P/oYceOmsfgEk7zau9ABbT5HUGrvnZNUxe8zPqV08Na2d5tdee99+UF+0k1/zsiBoW/GovAIBdifADADRF+AEAmiL8AABNEX4AgKYIPwBAU4QfAKApwg8A0BThBwBoivADADRF+AEAmiL8AABNEX4AgKYIPwBAU4QfAKApwg8A0BThBwBoivADADRF+AEAmiL8AABNEX4AgKYIPwBAU4QfAKApwg8A0BThBwBoivADADRF+AEAmiL8AABNEX4AgKYIPwBAU4QfAKApwg8A0BThBwBoivADADRF+AEAmiL8AABNEX4AgKYIPwBAU4QfAKApwg8A0BThBwBoivADADRF+AEAmiL8AABNEX4AgKYIPwBAU4QfAKApwg8A0JTloy4AYEdYuXLlqEsAsnMci8IP0IQzzzxz1CUA2TmORU97AQBNEX4AgKYIPwBAU4QfAKApwg8A0BThBwBoivADADRF+AEAmiL8AABNEX4AgKYIPwBAU4QfAKApwg8A0BThBwBoivADADRF+AEAmiL8AABNEX4AgKYIPwBAU4QfAKApwg8A0BThBwBoivADADRF+AEAmiL8AABNEX4AgKYIPwBAU4QfAKApwg8A0BThBwBoivADADRF+AEAmiL8AABNEX4AgKYIPwBAU4QfAKApwg8A0BThBwBoivADADRF+AEAmiL8AABNEX4AgKYIPwBAU4QfAKApwg8A0BThBwBoivADADRF+AEAmiL8AABNEX4AgKYIPwBAU4QfAKApy0ddAAAsxLInHs6e99806jKGsuyJzUky8nqXPfFwkoNHWsPOQPgBYMlZuXLlqEuYl02btiRJVqwYdfA4eMmt3WIQfgBYcs4888xRl8AS5pofAKApwg8A0BThBwBoivADADRF+AEAmiL8AABNEX4AgKYIPwBAU4QfAKApwg8A0BThBwBoivADADRF+AEAmiL8AABNEX4AgKYIPwBAU4QfAKApwg8A0BThBwBoivADADRF+AEAmiL8AABNEX4AgKYIPwBAU4QfAKAppdY6fOdSfpjkgcUrZ4c4MMlDoy6icfbBaFn/0bMPRs8+GK0dtf7/qtb6K/2N8wo/u4JSyvpa66pR19Ey+2C0rP/o2QejZx+M1qjX39NeAEBThB8AoCkthp8Pj7oA7IMRs/6jZx+Mnn0wWiNd/+au+QEA2tbimR8AoGG7RPgppVxRSvlBKeWeKW3PL6V8tpRydynlxlLKvl37MaWUDV37hlLKUVO2eVHXPlFK+WAppYzi8Sw181n/Kff/WinlsVLKn01pO7aU8vVu/d+yIx/DUjfffVBKOay7797u/j26dsfAAs3z59DupZQru/b7Sil/PmUbx8EClFKeVUq5vZTyte77+uyuff9Syi2llG92n/fr2kv3PT5RSvlqKeWFU8Y6rev/zVLKaaN6TEvJAtb/lG7d7y6lfKaU8vwpYy3+MVBrXfIfSY5I8sIk90xp+2KS3+1un57kXd3tFyT51e72bybZNGWbLyQ5PElJ8skkx436sS2Fj/ms/5T7r0tybZI/675eluRbSZ6d5GlJ7kry3FE/tqXyMc9jYHmSryZ5fvf1AUmWdbcdAztmH/xRkmu6209PsjHJmONgm9b/mUle2N3eJ8k3kjw3yUVJ3tK1vyXJe7vbx3ff46X7nv98175/km93n/frbu836se3s38sYP1fPLmuSY6bsv475BjYJc781FrvTPJwX/NzktzZ3b4lyR92fb9ca/1e135vkj1LKb9USnlmkn1rrZ+rvT1wVZLfX/zql775rH+SlFJ+P8l30lv/Sb+dZKLW+u1a60+SXJPklYtW9C5mnvvg5Um+Wmu9q9t2c631Z46BbTPPfVCT7FVKWZ5kzyQ/SfJoHAcLVmv9fq31S93tHye5L8mK9Nbvyq7blfnF9/Qrk1xVez6X5BndMfB7SW6ptT5ca30kvf127A58KEvSfNe/1vqZbn2T5HNJDulu75BjYJcIP7O4N79YsJOSPGtAnz9M8qVa67+kt5MenHLfg10bCzNw/Uspeyd5c5J39PVfkeT/Tvna+m+72Y6B5ySppZRPlVK+VEo5r2t3DGx/s+2D65I8nuT7Sb6b5C9rrQ/HcbBdlFLG0jvL//kkB9dav9/d9Y9JDu5uz7bW9sE2GnL9p3pNemfhkh20/rty+Dk9yX8spWxI7xTcT6beWUr5N0nem+Q/jKC2Fsy2/muT/Oda62OjKqwhs+2D5UlekuSU7vMflFJeNpoSd3mz7YPfTvKzJL+a5NeTnFNKefZoSty1dH9gfTTJG2qtj069rzuj6SXOi2i+619KOTK98PPmHVZkej8Ed0m11vvTO72fUspzkpwweV8p5ZAk/yPJqbXWb3XNm/KL027pbm/aMdXueuZY/99JcmIp5aIkz0jy81LK/0uyIdPPzln/bTTHPngwyZ211oe6+25K71qVv4tjYLuaYx/8UZKba60/TfKDUsqnk6xK7y9ex8EClVJ2T+8X79W11uu75n8qpTyz1vr97mmtH3TtmzJ4rTclGe9rv2Mx695VzHP9U0o5LMnl6V1buLlrnm2/bFe77JmfUspB3efdkqxJ8qHu62ck+Z/pXYD16cn+3Wm5R0sph3evcDk1ycd3eOG7iNnWv9b60lrrWK11LMn7k7yn1vpX6V0Y+hullF8vpTwtyclJbhhJ8buI2fZBkk8leV4p5endNSe/m+RrjoHtb4598N0kR3X37ZXeBbf3x3GwYN337F8nua/WesmUu25IMvmKrdPyi+/pG5Kc2r3q6/Ak/9wdA59K8vJSyn7dK5Ne3rUxh/mufynl15Jcn+SPa63fmNJ/xxwDo75CfHt8JPn79J47/2l6f9W+JsnZ6V1t/o0kf5Ff/EPHNek91/6VKR8HdfetSnJPelea/9XkNj623/r3bbc23au9uq+P7/p/K8lbR/24ltLHfPdBkn+f3vUo9yS5aEq7Y2AH7IMke6f3asd7k3wtyblTxnEcLGz9X5LeUypfnfKz/fj0Xs34v5J8M8mtSfbv+pckl3brfHeSVVPGOj3JRPfxJ6N+bEvhYwHrf3mSR6b0XT9lrEU/BvyHZwCgKbvs014AAIMIPwBAU4QfAKApwg8A0BThBwBoivADADRF+AHmpZTirUmAJU34AWbo/uttEz8fuv9yDTSkiR9uwNaVUsZKKV8vpVyV3n95flsp5YullK+WUt4xyzbnDupTSvlYKWVDKeXeUsqfdm3LSikfKaXcU0q5u5Tyxq79X5dSbu76/+9SyqGzzLVPKeU73fsHpZSy7+TXs41RSlldSvl8KeXLpZRbSykHd+1rSyl/272n1t9ux2UElgB/8QBT/UZ677+zb5IT03v38ZLkhlLKEbXWOyc7llJe3vUf1Of0WuvDpZQ9k3yxlPLRJGNJVtRaf7Pb/hndUB9Ockat9ZullN9J8l/Sve/VVLXWH5dS7kjvzUE/lt57/lxfa/1pKWW2Mf5PksNrrbWU8tok5yU5pxvyuUleUmt9cjusG7CECD/AVA/UWj9XSvnL9N7Q8ctd+97pBZ07p/R9+Rx9ziql/EHX/qyu/etJnl1KWZfemwv/Qyll7yQvTnJt730RkyS/NEd9l6cXYD6W5E+SvG4rYxyS5L937yb9tCTfmTLWDYIPtEn4AaZ6vPtckvynWut/naPvwD6llPEkRyf5t7XWJ7qzNXvUWh8ppTw/ye8lOSPJv0vyhiQ/qrX+1jDF1Vo/3T09N55kWa31nlLKvnOMsS7JJbXWG7pt1g54rEBjXPMDDPKpJKd3Z1VSSllRSjloyD6/nOSRLvgcmuTw7v4Dk+xWa/1okjVJXlhrfTTJd0opJ3V9SheQ5nJVkv+W5G+SZCtj/HKSTd3t0xa0EsAuR/gBZqi1/kN6AeOzpZS7k1yXZJ8h+9ycZHkp5b4kf5Hkc90mK5LcUUr5SpK/S/LnXfspSV5TSrkryb1JXrmV8q5Osl+Sv5/SNtsYa9N7OmxDkoeGXgBgl1ZqraOuAWBopZQTk7yy1vrHo64FWJpc8wMsGd3F0sclOX7UtQBLl/AD7HRKKW9NclJf87W11jNHUQ+wa/G0FwDQFBc8AwBNEX4AgKYIPwBAU4QfAKApwg8A0JT/D4qXz8TmlmnrAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 720x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# most of our data is between 2000 and 2017\n",
    "import datetime\n",
    "\n",
    "plt.subplots(figsize=(10,5))\n",
    "\n",
    "df_profits['release_date'] = pd.to_datetime(df_profits['release_date'])\n",
    "\n",
    "df_profits['release_year'] = df_profits['release_date'].map(lambda x: x.year)\n",
    "\n",
    "sns.boxplot(df_profits['release_year']);"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "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>release_month</th>\n",
       "      <th>gross_profit</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>4.318331e+07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>6.030782e+07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>7.765422e+07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>8.725812e+07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>1.334785e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>6</td>\n",
       "      <td>1.410546e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>7</td>\n",
       "      <td>1.076186e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>8</td>\n",
       "      <td>4.811661e+07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>9</td>\n",
       "      <td>3.879670e+07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>10</td>\n",
       "      <td>6.203410e+07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>11</td>\n",
       "      <td>1.163250e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>12</td>\n",
       "      <td>1.062264e+08</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    release_month  gross_profit\n",
       "0               1  4.318331e+07\n",
       "1               2  6.030782e+07\n",
       "2               3  7.765422e+07\n",
       "3               4  8.725812e+07\n",
       "4               5  1.334785e+08\n",
       "5               6  1.410546e+08\n",
       "6               7  1.076186e+08\n",
       "7               8  4.811661e+07\n",
       "8               9  3.879670e+07\n",
       "9              10  6.203410e+07\n",
       "10             11  1.163250e+08\n",
       "11             12  1.062264e+08"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Creating pandas datetime from the release date string\n",
    "df_profits['release_date'] = pd.to_datetime(df_profits['release_date'])\n",
    "\n",
    "# Adding column for the month of year it was released\n",
    "df_profits['release_month'] = pd.DatetimeIndex(df_profits['release_date']).month\n",
    "\n",
    "# creating table for the plot\n",
    "grouped_by_month = df_profits.groupby(['release_month']).mean().reset_index()\n",
    "month_and_gp =grouped_by_month[['release_month','gross_profit']]\n",
    "month_and_gp"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 936x720 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(13,10));\n",
    "months = ['Jan','Feb','Mar','Apr','May','Jun','Jul','Aug','Sep','Oct','Nov','Dec']\n",
    "plt.bar(x=months,height=month_and_gp['gross_profit']);\n",
    "plt.xlabel('Months')\n",
    "plt.ylabel('Mean Gross Profit (in hundred millions)')\n",
    "plt.title('Average Gross Profit by Months')\n",
    "plt.show()"
   ]
  }
 ],
 "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": "3.6.10"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}