Phase 2 - TMDB EDA.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "c23275fb",
   "metadata": {},
   "source": [
    "# **Phase 2 - TMDB EDA**"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2ed43d84",
   "metadata": {},
   "source": [
    "- Yvon Bilodeau\n",
    "- May 2022"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "77ddbac5",
   "metadata": {},
   "source": [
    "- How many movies had at least some valid financial information (values > 0 for budget OR revenue)?\n",
    "Excluding any movies with 0's for budget AND revenue from the remaining visualizations.\n",
    "- How many movies are there in each of the certification categories (G/PG/PG-13/R)?\n",
    "- What is the average revenue per certification category?\n",
    "- What is the average budget per certification category?"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9ca5ec63",
   "metadata": {},
   "source": [
    "## **Imports**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "e4a731ee",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Imports\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "from matplotlib.ticker import StrMethodFormatter\n",
    "price_fmt = StrMethodFormatter(\"${x:,.0f}\")\n",
    "sns.set_style('white')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f735d283",
   "metadata": {},
   "source": [
    "## **Data**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "6c3774d1",
   "metadata": {
    "scrolled": false
   },
   "outputs": [],
   "source": [
    "# Load in the csv.gz's of results for years 2000 and 2001\n",
    "year_2000_df = pd.read_csv(\"Data/final_tmdb_data_2000.csv.gz\")\n",
    "year_2001_df = pd.read_csv(\"Data/final_tmdb_data_2001.csv.gz\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "0455d201",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Combine years 2000 and 2001 into a single dataframe\n",
    "tmdb_results_combined_df = year_2000_df.append(year_2001_df)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "5d215c7d",
   "metadata": {},
   "outputs": [
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       "      <th></th>\n",
       "      <th>imdb_id</th>\n",
       "      <th>adult</th>\n",
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       "      <th>vote_average</th>\n",
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       "  </thead>\n",
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       "      <td>86.0</td>\n",
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       "      <td>110977.0</td>\n",
       "      <td>en</td>\n",
       "      <td>For the Cause</td>\n",
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       "      <td>0.0</td>\n",
       "      <td>100.0</td>\n",
       "      <td>[{'english_name': 'English', 'iso_639_1': 'en'...</td>\n",
       "      <td>Released</td>\n",
       "      <td>The ultimate showdown on a forbidden planet.</td>\n",
       "      <td>For the Cause</td>\n",
       "      <td>0.0</td>\n",
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       "      <td>7.0</td>\n",
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       "      <td>hi</td>\n",
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       "      <td>152.0</td>\n",
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       "      <td>0.0</td>\n",
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       "      <td>NaN</td>\n",
       "      <td>150000.0</td>\n",
       "      <td>[{'id': 18, 'name': 'Drama'}, {'id': 10749, 'n...</td>\n",
       "      <td>http://www.wkw-inthemoodforlove.com/</td>\n",
       "      <td>843.0</td>\n",
       "      <td>cn</td>\n",
       "      <td>花樣年華</td>\n",
       "      <td>...</td>\n",
       "      <td>12854953.0</td>\n",
       "      <td>99.0</td>\n",
       "      <td>[{'english_name': 'Cantonese', 'iso_639_1': 'c...</td>\n",
       "      <td>Released</td>\n",
       "      <td>Feel the heat, keep the feeling burning, let t...</td>\n",
       "      <td>In the Mood for Love</td>\n",
       "      <td>0.0</td>\n",
       "      <td>8.1</td>\n",
       "      <td>1859.0</td>\n",
       "      <td>PG</td>\n",
       "    </tr>\n",
       "    <tr>\n",
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       "      <td>885436.0</td>\n",
       "      <td>en</td>\n",
       "      <td>Guns Along The Bravo</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>85.0</td>\n",
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       "      <td>https://www.utahwolf.com/films/coming-soon-new...</td>\n",
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       "      <td>en</td>\n",
       "      <td>New Breed</td>\n",
       "      <td>...</td>\n",
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       "      <td>57.0</td>\n",
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       "      <td>Released</td>\n",
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       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NR</td>\n",
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       "    <tr>\n",
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       "      <td>NaN</td>\n",
       "      <td>0.0</td>\n",
       "      <td>[{'id': 28, 'name': 'Action'}]</td>\n",
       "      <td>http://www.hkcinemagic.com/en/movie.asp?id=6627</td>\n",
       "      <td>201706.0</td>\n",
       "      <td>cn</td>\n",
       "      <td>致命密函</td>\n",
       "      <td>...</td>\n",
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       "      <td>[{'english_name': 'Cantonese', 'iso_639_1': 'c...</td>\n",
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       "      <td>NaN</td>\n",
       "      <td>Chinese Heroes</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3.0</td>\n",
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      "text/plain": [
       "        imdb_id  adult                     backdrop_path  \\\n",
       "0             0    NaN                               NaN   \n",
       "1     tt0113026    0.0  /vMFs7nw6P0bIV1jDsQpxAieAVnH.jpg   \n",
       "2     tt0113092    0.0                               NaN   \n",
       "3     tt0116391    0.0                               NaN   \n",
       "4     tt0118694    0.0  /n4GJFGzsc7NinI1VeGDXIcQjtU2.jpg   \n",
       "...         ...    ...                               ...   \n",
       "1272  tt7797670    0.0                               NaN   \n",
       "1273  tt7797790    0.0                               NaN   \n",
       "1274  tt8665056    0.0                               NaN   \n",
       "1275  tt8795764    0.0                               NaN   \n",
       "1276  tt9071078    0.0                               NaN   \n",
       "\n",
       "     belongs_to_collection      budget  \\\n",
       "0                      NaN         NaN   \n",
       "1                      NaN  10000000.0   \n",
       "2                      NaN         0.0   \n",
       "3                      NaN         0.0   \n",
       "4                      NaN    150000.0   \n",
       "...                    ...         ...   \n",
       "1272                   NaN         0.0   \n",
       "1273                   NaN         0.0   \n",
       "1274                   NaN         0.0   \n",
       "1275                   NaN         0.0   \n",
       "1276                   NaN         0.0   \n",
       "\n",
       "                                                 genres  \\\n",
       "0                                                   NaN   \n",
       "1     [{'id': 35, 'name': 'Comedy'}, {'id': 10402, '...   \n",
       "2              [{'id': 878, 'name': 'Science Fiction'}]   \n",
       "3     [{'id': 18, 'name': 'Drama'}, {'id': 28, 'name...   \n",
       "4     [{'id': 18, 'name': 'Drama'}, {'id': 10749, 'n...   \n",
       "...                                                 ...   \n",
       "1272                     [{'id': 27, 'name': 'Horror'}]   \n",
       "1273                     [{'id': 27, 'name': 'Horror'}]   \n",
       "1274                    [{'id': 37, 'name': 'Western'}]   \n",
       "1275                     [{'id': 27, 'name': 'Horror'}]   \n",
       "1276                     [{'id': 28, 'name': 'Action'}]   \n",
       "\n",
       "                                               homepage        id  \\\n",
       "0                                                   NaN       NaN   \n",
       "1                                                   NaN   62127.0   \n",
       "2                                                   NaN  110977.0   \n",
       "3                                                   NaN  442869.0   \n",
       "4                  http://www.wkw-inthemoodforlove.com/     843.0   \n",
       "...                                                 ...       ...   \n",
       "1272                                                NaN  956214.0   \n",
       "1273                                                NaN  956219.0   \n",
       "1274  http://skeletoncreekproductions.com/p-movie-br...  885436.0   \n",
       "1275  https://www.utahwolf.com/films/coming-soon-new...  871624.0   \n",
       "1276    http://www.hkcinemagic.com/en/movie.asp?id=6627  201706.0   \n",
       "\n",
       "     original_language                              original_title  ...  \\\n",
       "0                  NaN                                         NaN  ...   \n",
       "1                   en                             The Fantasticks  ...   \n",
       "2                   en                               For the Cause  ...   \n",
       "3                   hi                                        Gang  ...   \n",
       "4                   cn                                        花樣年華  ...   \n",
       "...                ...                                         ...  ...   \n",
       "1272                en  Edmund Kemper Part 2: La Mort C'est La Vie  ...   \n",
       "1273                en         Edmund Kemper Part 3: La mort sévit  ...   \n",
       "1274                en                        Guns Along The Bravo  ...   \n",
       "1275                en                                   New Breed  ...   \n",
       "1276                cn                                        致命密函  ...   \n",
       "\n",
       "         revenue  runtime                                   spoken_languages  \\\n",
       "0            NaN      NaN                                                NaN   \n",
       "1            0.0     86.0  [{'english_name': 'English', 'iso_639_1': 'en'...   \n",
       "2            0.0    100.0  [{'english_name': 'English', 'iso_639_1': 'en'...   \n",
       "3            0.0    152.0  [{'english_name': 'Hindi', 'iso_639_1': 'hi', ...   \n",
       "4     12854953.0     99.0  [{'english_name': 'Cantonese', 'iso_639_1': 'c...   \n",
       "...          ...      ...                                                ...   \n",
       "1272         0.0     91.0                                                 []   \n",
       "1273         0.0     72.0  [{'english_name': 'French', 'iso_639_1': 'fr',...   \n",
       "1274         0.0     85.0                                                 []   \n",
       "1275         0.0     57.0  [{'english_name': 'English', 'iso_639_1': 'en'...   \n",
       "1276         0.0     90.0  [{'english_name': 'Cantonese', 'iso_639_1': 'c...   \n",
       "\n",
       "        status                                            tagline  \\\n",
       "0          NaN                                                NaN   \n",
       "1     Released      Try to remember the first time magic happened   \n",
       "2     Released       The ultimate showdown on a forbidden planet.   \n",
       "3     Released                                                NaN   \n",
       "4     Released  Feel the heat, keep the feeling burning, let t...   \n",
       "...        ...                                                ...   \n",
       "1272  Released                                                NaN   \n",
       "1273  Released                                                NaN   \n",
       "1274  Released  Evil came to the Southwest until three blazing...   \n",
       "1275  Released                                                NaN   \n",
       "1276  Released                                                NaN   \n",
       "\n",
       "                                           title  video  vote_average  \\\n",
       "0                                            NaN    NaN           NaN   \n",
       "1                                The Fantasticks    0.0           5.4   \n",
       "2                                  For the Cause    0.0           4.4   \n",
       "3                                           Gang    0.0           0.0   \n",
       "4                           In the Mood for Love    0.0           8.1   \n",
       "...                                          ...    ...           ...   \n",
       "1272  Edmund Kemper Part 2: La Mort C'est La Vie    0.0           0.0   \n",
       "1273         Edmund Kemper Part 3: La mort sévit    0.0           0.0   \n",
       "1274                        Guns Along The Bravo    0.0           0.0   \n",
       "1275                                   New Breed    0.0           0.0   \n",
       "1276                              Chinese Heroes    0.0           3.0   \n",
       "\n",
       "     vote_count certification  \n",
       "0           NaN           NaN  \n",
       "1          21.0           NaN  \n",
       "2           7.0           NaN  \n",
       "3           0.0           NaN  \n",
       "4        1859.0            PG  \n",
       "...         ...           ...  \n",
       "1272        0.0           NaN  \n",
       "1273        0.0           NaN  \n",
       "1274        0.0           NaN  \n",
       "1275        0.0            NR  \n",
       "1276        2.0           NaN  \n",
       "\n",
       "[2474 rows x 26 columns]"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Display the tail and head of the combines dataframe\n",
    "tmdb_results_combined_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "46912090",
   "metadata": {
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "# Save a final merged .csv.gz of all of the tmdb api data \n",
    "tmdb_results_combined_df.to_csv(\"Data/tmdb_results_combined.csv.gz\", \n",
    "                                compression=\"gzip\", \n",
    "                                index=False)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e700823e",
   "metadata": {},
   "source": [
    "### **How many movies had at least some valid financial information (values > 0 for budget OR revenue)?**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "896db471",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Financial information filter\n",
    "fin_filter = (tmdb_results_combined_df['budget'] > 0) | (tmdb_results_combined_df['revenue'] > 0)\n",
    "# Create a dataframe of movies with either a positive budget or revenue\n",
    "tmdb_results_combined_with_fin_res_df = tmdb_results_combined_df.loc[fin_filter].copy()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "c87ec43e",
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "615 movies had at least some valid financial information.\n"
     ]
    }
   ],
   "source": [
    "# Report the number of movies with either a positive budget or revenue \n",
    "fin_movie_count=len(tmdb_results_combined_with_fin_res_df)\n",
    "print(f'{fin_movie_count} movies had at least some valid financial information.')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "dca9353d",
   "metadata": {},
   "source": [
    "### **How many movies are there in each of the certification categories (G/PG/PG-13/R)?**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "aea8e86a",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "R        226\n",
       "PG-13    130\n",
       "PG        35\n",
       "NR        17\n",
       "G         14\n",
       "Name: certification, dtype: int64"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Display the value counts for each certification category\n",
    "tmdb_results_combined_with_fin_res_df['certification'].value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "f3a1183a",
   "metadata": {
    "scrolled": true
   },
   "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>mean</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>certification</th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>G</th>\n",
       "      <td>1.237085e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>PG</th>\n",
       "      <td>1.111773e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>PG-13</th>\n",
       "      <td>9.957933e+07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>R</th>\n",
       "      <td>3.324591e+07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NR</th>\n",
       "      <td>8.887611e+06</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                       mean\n",
       "certification              \n",
       "G              1.237085e+08\n",
       "PG             1.111773e+08\n",
       "PG-13          9.957933e+07\n",
       "R              3.324591e+07\n",
       "NR             8.887611e+06"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "rev_mean_df = tmdb_results_combined_with_fin_res_df.groupby('certification')\\\n",
    "            ['revenue'].agg(['mean']).sort_values('mean', ascending=False).copy()\n",
    "rev_mean_df['mean'] = round(rev_mean_df['mean'],3)\n",
    "rev_mean_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "77c0b4da",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots(figsize=(8,4))\n",
    "sns.barplot(data=rev_mean_df, x='mean', y=rev_mean_df.index, \n",
    "            orient='h', \n",
    "            palette='viridis'); \n",
    "plt.title('Average Movie Revenue', fontsize = 18, weight='bold')\n",
    "plt.xlabel('Dollars', fontsize = 14, weight='bold')\n",
    "plt.ylabel('Certification', fontsize = 14, weight='bold');\n",
    "plt.xticks(fontsize = 10, weight='bold')\n",
    "plt.yticks(fontsize = 10, weight='bold');\n",
    "ax.xaxis.set_major_formatter(price_fmt)\n",
    "\n",
    "plt.tight_layout()\n",
    "plt.show;"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c23b1163",
   "metadata": {},
   "source": [
    "### **What is the average budget per certification category?**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "7ac5c73f",
   "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>mean</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>certification</th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>PG</th>\n",
       "      <td>4.497857e+07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>PG-13</th>\n",
       "      <td>4.348391e+07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>G</th>\n",
       "      <td>4.085714e+07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>R</th>\n",
       "      <td>2.028827e+07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NR</th>\n",
       "      <td>6.388241e+06</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                       mean\n",
       "certification              \n",
       "PG             4.497857e+07\n",
       "PG-13          4.348391e+07\n",
       "G              4.085714e+07\n",
       "R              2.028827e+07\n",
       "NR             6.388241e+06"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Grouping the dataframe based on certification and extracting the average budget per certification\n",
    "bud_mean_df = tmdb_results_combined_with_fin_res_df.groupby('certification')\\\n",
    "            ['budget'].agg(['mean']).sort_values('mean', ascending=False).copy()\n",
    "bud_mean_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "76768996",
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots(figsize=(8,4))\n",
    "sns.barplot(data=bud_mean_df, x='mean', y=bud_mean_df.index, \n",
    "            orient='h', \n",
    "            palette='viridis'); \n",
    "plt.title('Average Movie Budget', fontsize = 18, weight='bold')\n",
    "plt.xlabel('Dollars', fontsize = 14, weight='bold')\n",
    "plt.ylabel('Certification', fontsize = 14, weight='bold');\n",
    "plt.xticks(fontsize = 10, weight='bold')\n",
    "plt.yticks(fontsize = 10, weight='bold');\n",
    "ax.xaxis.set_major_formatter(price_fmt)\n",
    "\n",
    "plt.tight_layout()\n",
    "plt.show;"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python (dojo-env)",
   "language": "python",
   "name": "dojo-env"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.12"
  },
  "toc": {
   "base_numbering": 1,
   "nav_menu": {},
   "number_sections": true,
   "sideBar": true,
   "skip_h1_title": false,
   "title_cell": "Table of Contents",
   "title_sidebar": "Contents",
   "toc_cell": false,
   "toc_position": {},
   "toc_section_display": true,
   "toc_window_display": false
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}