ott-platforms-analysis.ipynb

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    "# Movie analysis on OTT platforms \n",
    "> This notebook contain various plots and visuals justifying variation in movies on OTT platforms like Amazon Prime, Netflix, Hulu and Disney+. This notebook also demonstrates the type movies produced and their strengths in drawing viewers. Direct relationships have been drawn with the various other features like Rotten Tomatoes rating, Generes, etc. and all have been demonstrated in plots and have been axplained. "
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   "source": [
    "* ***Project name:*** OTT Platforms Analysis\n",
    "* ***Data link:*** [Click here](http://../input/movies-on-netflix-prime-video-hulu-and-disney)\n",
    "* ***Notebook owner:*** [Adipta Biswas](http://www.linkedin.com/in/adipta-biswas-adiptabiswas/)\n",
    "* ***Project type:*** ED Analysis"
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   "source": [
    "![OTT platforms](http://hackernoon.com/drafts/wg1pd33jc.png)"
   ]
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    "## Summary \n",
    "> The provided data has **16744 rows** and **16 columns**. There are two features **\"Age\"** and **\"Rotten Tomatoes\"**\n",
    "with **NULL** values  **>50%** of the available data points. There are **5** columns which are of **Integer** data-type, **6** of **Object** type and the rest are of **Float** type. The data set contains data ranging from **1900** to the year **2020**.\n",
    "\n",
    "> The Data consists of **4** major OTT platforms: **\"Netflix\"**, **\"Hulu\"**, **\"Prime videos\"** and **\"Disney+\"**. The columns: **\"IMDb\"** and **\"Rotten Tomatoes\"** are to be considered as an **Interval** data of type **Numeric**. Some of the columns like **\"Year\"** and **\"Age\"** need to **binned**. for further analysis.  "
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>ID</th>\n",
       "      <th>Title</th>\n",
       "      <th>Year</th>\n",
       "      <th>Age</th>\n",
       "      <th>IMDb</th>\n",
       "      <th>Rotten Tomatoes</th>\n",
       "      <th>Netflix</th>\n",
       "      <th>Hulu</th>\n",
       "      <th>Prime Video</th>\n",
       "      <th>Disney+</th>\n",
       "      <th>Type</th>\n",
       "      <th>Directors</th>\n",
       "      <th>Genres</th>\n",
       "      <th>Country</th>\n",
       "      <th>Language</th>\n",
       "      <th>Runtime</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>Inception</td>\n",
       "      <td>2010</td>\n",
       "      <td>13+</td>\n",
       "      <td>8.8</td>\n",
       "      <td>87%</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>Christopher Nolan</td>\n",
       "      <td>Action,Adventure,Sci-Fi,Thriller</td>\n",
       "      <td>United States,United Kingdom</td>\n",
       "      <td>English,Japanese,French</td>\n",
       "      <td>148.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>The Matrix</td>\n",
       "      <td>1999</td>\n",
       "      <td>18+</td>\n",
       "      <td>8.7</td>\n",
       "      <td>87%</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>Lana Wachowski,Lilly Wachowski</td>\n",
       "      <td>Action,Sci-Fi</td>\n",
       "      <td>United States</td>\n",
       "      <td>English</td>\n",
       "      <td>136.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>Avengers: Infinity War</td>\n",
       "      <td>2018</td>\n",
       "      <td>13+</td>\n",
       "      <td>8.5</td>\n",
       "      <td>84%</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>Anthony Russo,Joe Russo</td>\n",
       "      <td>Action,Adventure,Sci-Fi</td>\n",
       "      <td>United States</td>\n",
       "      <td>English</td>\n",
       "      <td>149.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>Back to the Future</td>\n",
       "      <td>1985</td>\n",
       "      <td>7+</td>\n",
       "      <td>8.5</td>\n",
       "      <td>96%</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>Robert Zemeckis</td>\n",
       "      <td>Adventure,Comedy,Sci-Fi</td>\n",
       "      <td>United States</td>\n",
       "      <td>English</td>\n",
       "      <td>116.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>The Good, the Bad and the Ugly</td>\n",
       "      <td>1966</td>\n",
       "      <td>18+</td>\n",
       "      <td>8.8</td>\n",
       "      <td>97%</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>Sergio Leone</td>\n",
       "      <td>Western</td>\n",
       "      <td>Italy,Spain,West Germany</td>\n",
       "      <td>Italian</td>\n",
       "      <td>161.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>6</td>\n",
       "      <td>Spider-Man: Into the Spider-Verse</td>\n",
       "      <td>2018</td>\n",
       "      <td>7+</td>\n",
       "      <td>8.4</td>\n",
       "      <td>97%</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>Bob Persichetti,Peter Ramsey,Rodney Rothman</td>\n",
       "      <td>Animation,Action,Adventure,Family,Sci-Fi</td>\n",
       "      <td>United States</td>\n",
       "      <td>English,Spanish</td>\n",
       "      <td>117.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>7</td>\n",
       "      <td>The Pianist</td>\n",
       "      <td>2002</td>\n",
       "      <td>18+</td>\n",
       "      <td>8.5</td>\n",
       "      <td>95%</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>Roman Polanski</td>\n",
       "      <td>Biography,Drama,Music,War</td>\n",
       "      <td>United Kingdom,France,Poland,Germany</td>\n",
       "      <td>English,German,Russian</td>\n",
       "      <td>150.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>8</td>\n",
       "      <td>Django Unchained</td>\n",
       "      <td>2012</td>\n",
       "      <td>18+</td>\n",
       "      <td>8.4</td>\n",
       "      <td>87%</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>Quentin Tarantino</td>\n",
       "      <td>Drama,Western</td>\n",
       "      <td>United States</td>\n",
       "      <td>English,German,French,Italian</td>\n",
       "      <td>165.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>9</td>\n",
       "      <td>Raiders of the Lost Ark</td>\n",
       "      <td>1981</td>\n",
       "      <td>7+</td>\n",
       "      <td>8.4</td>\n",
       "      <td>95%</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>Steven Spielberg</td>\n",
       "      <td>Action,Adventure</td>\n",
       "      <td>United States</td>\n",
       "      <td>English,German,Hebrew,Spanish,Arabic,Nepali</td>\n",
       "      <td>115.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>10</td>\n",
       "      <td>Inglourious Basterds</td>\n",
       "      <td>2009</td>\n",
       "      <td>18+</td>\n",
       "      <td>8.3</td>\n",
       "      <td>89%</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>Quentin Tarantino</td>\n",
       "      <td>Adventure,Drama,War</td>\n",
       "      <td>Germany,United States</td>\n",
       "      <td>English,German,French,Italian</td>\n",
       "      <td>153.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>"
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   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "from scipy import stats\n",
    "%matplotlib inline\n",
    "import matplotlib.pyplot as plt\n",
    "from IPython.display import HTML\n",
    "\n",
    "main_df = pd.read_csv(\"../input/movies-on-netflix-prime-video-hulu-and-disney/MoviesOnStreamingPlatforms_updated.csv\")\n",
    "list_of_columns = [list(main_df.columns)] # Define columns\n",
    "main_df.drop(columns = \"Unnamed: 0\", inplace = True)\n",
    "main_df_show = main_df.head(10)\n",
    "HTML(main_df_show.to_html(escape=False))"
   ]
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    "## Analysis and observations\n",
    "> **(There were a lot of missing points in the data set. An analysis has been done excluding those point)**\n",
    "\n",
    "> * As per the available data, the **\"Prime video\"** has the *highest* number movies followed by **\"Netflix\"**. **\"Disney+\"** has the *lowest* number of movies casted.\n",
    "> *  *Most* of the movies produced were **\"Drama\"** followed by **\"Comedy\"**. Almost *negligible* number of movies produced were of **\"Game-Show\"** genre.\n",
    "> * The number of movies released under the genres **\"Reality-TV\"**, **\"Talk-Show\"**, **\"Film-Noire\"** and **\"News\"** were a lot *less* as compared to other genres.\n",
    "> * The number of movies produced throughout under **\"Musical\"** and **\"Short\"** genres were almost *similar*.\n",
    "> * As there were a large number of missing data, after removing those values it is seen that *most* of the movies prduced had **\"Rotten Tomatoes\"** rating **>81%** followed by **61% - 80%**. The *least* number of movies produced had **<20%**. \n",
    "> * *Most* of the movies released were of age group **18+**. The *least* number of movies produced were of age group **16+**.\n",
    "> * *Majority* of the movies were released between **2000 and 2020**. The least number of movies released were between **1900 and 1900**.\n",
    "> * According to the data, it is seen that the *frequency* of **movie production** *increased* along with an *increase* in **Year**. They both exhibit a positive correlation. \n",
    "> * *Majority* of the movies has an **IMDb** rating ranging between **5-6** followed by **7-8**. \n",
    "> * The *least* number of movies got an IMDb rating between **9-10**. \n",
    "> * On the basis of given data, we can say that majority of the movies in these 4 OTT platforms are *average* or *more than average* **IMDb** rated. "
   ]
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     "text": [
      "Year -> int64\n",
      "Age -> object\n",
      "IMDb -> float64\n",
      "Rotten Tomatoes -> object\n",
      "Netflix -> int64\n",
      "Hulu -> int64\n",
      "Prime Video -> int64\n",
      "Disney+ -> int64\n",
      "Directors -> object\n",
      "Genres -> object\n",
      "Country -> object\n",
      "Language -> object\n",
      "Runtime -> float64\n"
     ]
    }
   ],
   "source": [
    "df = main_df\n",
    "df.drop(columns = \"ID\", inplace = True)\n",
    "df.drop(columns = \"Type\", inplace = True)\n",
    "\n",
    "def cols(df_col):\n",
    "    for c in df_col:\n",
    "        if c != \"Title\":\n",
    "            print(\"{} -> {}\".format(c, df[c].dtype))\n",
    "cols(df.columns.to_list())\n",
    "\n",
    "df[\"Runtime\"] = df[\"Runtime\"].apply(lambda x: x//60)"
   ]
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     "text": [
      "\"NA values in %ge\"\n",
      "\n",
      "Year -> 0.0%\n",
      "\n",
      "Age -> 56.08%\n",
      "\n",
      "IMDb -> 3.41%\n",
      "\n",
      "Rotten Tomatoes -> 69.19%\n",
      "\n",
      "Netflix -> 0.0%\n",
      "\n",
      "Hulu -> 0.0%\n",
      "\n",
      "Prime Video -> 0.0%\n",
      "\n",
      "Disney+ -> 0.0%\n",
      "\n",
      "Genres -> 1.64%\n",
      "\n",
      "Country -> 2.6%\n",
      "\n",
      "Language -> 3.58%\n",
      "\n",
      "Runtime -> 3.54%\n",
      "\n"
     ]
    }
   ],
   "source": [
    "def vals(cols):\n",
    "    print(\"\\\"NA values in %ge\\\"\\n\")\n",
    "    for c in cols:\n",
    "        if c not in [\"Title\", \"Directors\"]:\n",
    "            print(\"{} -> {}%\\n\".format(c, round(100*(df[c].isna().sum()/len(df)),2)))\n",
    "vals(df.columns.to_list())"
   ]
  },
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      "/opt/conda/lib/python3.7/site-packages/ipykernel_launcher.py:12: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  if sys.path[0] == '':\n",
      "/opt/conda/lib/python3.7/site-packages/ipykernel_launcher.py:27: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "/opt/conda/lib/python3.7/site-packages/pandas/core/indexing.py:670: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  iloc._setitem_with_indexer(indexer, value)\n",
      "/opt/conda/lib/python3.7/site-packages/ipykernel_launcher.py:41: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n"
     ]
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   "source": [
    "df[\"Year\"] = df[\"Year\"].astype(int)\n",
    "df[\"Year_Bin\"] = df[\"Year\"].apply(lambda x: \"1919-1900\" if x >= 1900 and x <= 1919 else \"1939-1920\" \n",
    "                                  if x >= 1920 and x <= 1939 else \"1959 - 1940\" if x >= 1940 and x <= 1959\n",
    "                                  else \"1979-1960\" if x >= 1960 and x <= 1979 else \"1999-1980\" if x >= 1980 \n",
    "                                  and x <= 1999 else \"2020-2000\")\n",
    "\n",
    "df[\"Rotten Tomatoes\"] = df[\"Rotten Tomatoes\"].fillna(\"NA\")\n",
    "df[\"Rotten Tomatoes\"] = df[\"Rotten Tomatoes\"].apply(lambda x: x.strip(\"%\"))\n",
    "\n",
    "for row in df[\"Rotten Tomatoes\"]:\n",
    "    if row != \"NA\":\n",
    "        df[\"Rotten Tomatoes\"][row] = int(row)\n",
    "\n",
    "df_tomatoes = df[\"Rotten Tomatoes\"]\n",
    "df_tomatoes.replace(\"NA\", np.nan, inplace = True)\n",
    "df_tomatoes.dropna(inplace = True)\n",
    "\n",
    "df_tomatoes = df_tomatoes.astype(int)\n",
    "df_tomatoes = df_tomatoes.apply(lambda x: \"<20%\" if x >= 0 and x < 20 else \"20%-40%\" \n",
    "                                if x >= 20 and x <= 40 else \"41%60%\" if x >= 41 and x <= 60\n",
    "                                else \"61%-80%\" if x >= 61 and x <= 80 else \">81%\")\n",
    "\n",
    "df[\"IMDb\"] = df[\"IMDb\"].fillna(\"NA\")\n",
    "\n",
    "for row in df[\"IMDb\"]:\n",
    "    if row != \"NA\":\n",
    "        df[\"IMDb\"][row] = float(row)\n",
    "\n",
    "df_imdb = df[\"IMDb\"]\n",
    "df_imdb.replace(\"NA\", np.nan, inplace = True)\n",
    "df_imdb.dropna(inplace = True)\n",
    "\n",
    "df_imdb = df_imdb.astype(float)\n",
    "df_imdb = df_imdb.apply(lambda x: \"<2\" if x >= 0.0 and x < 3.0 else \"3-4\" \n",
    "                                if x >= 3.0 and x < 5.0 else \"5-6\" if x >= 5.0 and x < 7.0\n",
    "                                else \"7-8\" if x >= 7.0 and x < 9 else \">9\")\n",
    "\n",
    "df_chan = df[[\"Netflix\", \"Hulu\", \"Prime Video\", \"Disney+\"]]\n",
    "\n",
    "def dfchan(dfcol):\n",
    "    df_chan[dfcol] = df_chan[dfcol].apply(lambda x: dfcol if x == 1 else \"NA\")\n",
    "for col in df_chan.columns:\n",
    "    dfchan(col)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "_cell_guid": "60272ce4-f933-4aaa-bc96-463e82a4ded9",
    "_kg_hide-input": true,
    "_kg_hide-output": true,
    "_uuid": "cfb09b5e-b455-4757-b098-32f43e33f0cd",
    "execution": {
     "iopub.execute_input": "2020-12-12T13:57:32.663265Z",
     "iopub.status.busy": "2020-12-12T13:57:32.647618Z",
     "iopub.status.idle": "2020-12-12T13:57:32.689620Z",
     "shell.execute_reply": "2020-12-12T13:57:32.688829Z"
    },
    "papermill": {
     "duration": 0.071401,
     "end_time": "2020-12-12T13:57:32.689746",
     "exception": false,
     "start_time": "2020-12-12T13:57:32.618345",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "Netflix_Count = 0\n",
    "Other_Netflix_Count = 0\n",
    "for row in df_chan[\"Netflix\"].to_list():\n",
    "    if row == \"Netflix\":\n",
    "        Netflix_Count += 1\n",
    "    elif row == \"NA\":\n",
    "        Other_Netflix_Count += 1\n",
    "    else:\n",
    "        continue\n",
    "        \n",
    "Hulu_Count = 0\n",
    "Other_Hulu_Count = 0\n",
    "for row in df_chan[\"Hulu\"].to_list():\n",
    "    if row == \"Hulu\":\n",
    "        Hulu_Count += 1\n",
    "    elif row == \"NA\":\n",
    "        Other_Hulu_Count += 1\n",
    "    else:\n",
    "        continue\n",
    "        \n",
    "Prime_Video_Count = 0\n",
    "Other_Prime_Video_Count = 0\n",
    "for row in df_chan[\"Prime Video\"].to_list():\n",
    "    if row == \"Prime Video\":\n",
    "        Prime_Video_Count += 1\n",
    "    elif row == \"NA\":\n",
    "        Other_Prime_Video_Count += 1\n",
    "    else:\n",
    "        continue\n",
    "        \n",
    "Disney_Count = 0\n",
    "Other_Disney_Count = 0\n",
    "for row in df_chan[\"Disney+\"].to_list():\n",
    "    if row == \"Disney+\":\n",
    "        Disney_Count += 1\n",
    "    elif row == \"NA\":\n",
    "        Other_Disney_Count += 1\n",
    "    else:\n",
    "        continue\n",
    "        \n",
    "genre_col = df[\"Genres\"]\n",
    "genre_col.dropna(inplace = True)\n",
    "genre_col = [i.split(\",\") for i in genre_col]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "_cell_guid": "2251d858-3ec3-458e-90da-5d1924a7cc8d",
    "_kg_hide-input": true,
    "_kg_hide-output": true,
    "_uuid": "4eb994a1-c7db-4ec5-bd57-b95c8efb34a9",
    "execution": {
     "iopub.execute_input": "2020-12-12T13:57:32.756713Z",
     "iopub.status.busy": "2020-12-12T13:57:32.740940Z",
     "iopub.status.idle": "2020-12-12T13:57:32.817821Z",
     "shell.execute_reply": "2020-12-12T13:57:32.817190Z"
    },
    "papermill": {
     "duration": 0.107126,
     "end_time": "2020-12-12T13:57:32.817955",
     "exception": false,
     "start_time": "2020-12-12T13:57:32.710829",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Genre Frequency -> {'Action': 2683, 'Adventure': 1778, 'Sci-Fi': 1228, 'Thriller': 3354, 'Comedy': 4637, 'Western': 499, 'Animation': 711, 'Family': 1514, 'Biography': 821, 'Drama': 7227, 'Music': 667, 'War': 539, 'Crime': 1833, 'Fantasy': 1089, 'Romance': 2359, 'History': 715, 'Mystery': 1274, 'Horror': 2201, 'Sport': 404, 'Documentary': 2546, 'Musical': 401, 'News': 105, 'Short': 386, 'Reality-TV': 22, 'Talk-Show': 19, 'Game-Show': 7, 'Film-Noir': 79}\n",
      "\n",
      "Channel Frequency -> {'Netflix': 3560, 'Hulu': 903, 'Prime Video': 12354, 'Disney+': 564}\n"
     ]
    }
   ],
   "source": [
    "# Genre frequency\n",
    "genre_freq_dict, genre_freq_key_ls = {}, []\n",
    "for row in genre_col:\n",
    "    for _row in row:\n",
    "        if _row not in genre_freq_key_ls:\n",
    "            genre_freq_key_ls.append(_row)\n",
    "            genre_freq_dict[_row] = 1\n",
    "        else:\n",
    "            counter = genre_freq_dict[_row]\n",
    "            genre_freq_dict[_row] = counter + 1\n",
    "print(\"Genre Frequency ->\", genre_freq_dict)\n",
    "\n",
    "# Channel frequency\n",
    "channel_freq_dict, channel_freq_key_ls = {}, []\n",
    "channel_ls = [\"Netflix\", \"Hulu\", \"Prime Video\", \"Disney+\"]\n",
    "for channel in channel_ls:\n",
    "    for _row in df[channel]:\n",
    "        if int(_row) == 1:\n",
    "            if channel not in channel_freq_key_ls:\n",
    "                channel_freq_key_ls.append(channel)\n",
    "                channel_freq_dict[channel] = 1\n",
    "            else:\n",
    "                counter = channel_freq_dict[channel]\n",
    "                channel_freq_dict[channel] = counter + 1\n",
    "print()\n",
    "print(\"Channel Frequency ->\", channel_freq_dict)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "_cell_guid": "9635b537-f775-4a9a-bbba-71b819c22836",
    "_uuid": "0ca19a74-f121-47e1-b881-954005026fbb",
    "papermill": {
     "duration": 0.021629,
     "end_time": "2020-12-12T13:57:32.861154",
     "exception": false,
     "start_time": "2020-12-12T13:57:32.839525",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "### Visuals and Analysis"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "_cell_guid": "6d727880-ee29-4d43-abc9-b71ce118480c",
    "_kg_hide-input": true,
    "_uuid": "a3577837-f2b5-4806-b3b9-865f35979791",
    "execution": {
     "iopub.execute_input": "2020-12-12T13:57:32.910739Z",
     "iopub.status.busy": "2020-12-12T13:57:32.910003Z",
     "iopub.status.idle": "2020-12-12T13:57:33.154658Z",
     "shell.execute_reply": "2020-12-12T13:57:33.155285Z"
    },
    "papermill": {
     "duration": 0.272867,
     "end_time": "2020-12-12T13:57:33.155445",
     "exception": false,
     "start_time": "2020-12-12T13:57:32.882578",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0, 0.5, 'No. of movies')"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "df['Year_Bin'].hist(grid=False, xlabelsize=8, ylabelsize=12, color = \"brown\")\n",
    "plt.xlabel(\"Release year\", fontsize=15)\n",
    "plt.ylabel(\"No. of movies\",fontsize=15)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "_cell_guid": "ea38c829-bac2-4978-bf83-32410d23e61e",
    "_uuid": "c088521f-f586-4556-a8af-2f4cd77ca04a",
    "papermill": {
     "duration": 0.022754,
     "end_time": "2020-12-12T13:57:33.201349",
     "exception": false,
     "start_time": "2020-12-12T13:57:33.178595",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "* Maximum movies were released between 2000 and 2020\n",
    "* Minimum movies were released between 1900 and 1900\n",
    "* The frequency of movie production increases along with an increase in year"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "_cell_guid": "f70973ec-7f7a-45ef-ace8-dc94cb021aac",
    "_kg_hide-input": true,
    "_uuid": "da19d9b4-13ce-4643-a05d-c6151fab54b5",
    "execution": {
     "iopub.execute_input": "2020-12-12T13:57:33.261209Z",
     "iopub.status.busy": "2020-12-12T13:57:33.260050Z",
     "iopub.status.idle": "2020-12-12T13:57:33.523625Z",
     "shell.execute_reply": "2020-12-12T13:57:33.522928Z"
    },
    "papermill": {
     "duration": 0.299307,
     "end_time": "2020-12-12T13:57:33.523751",
     "exception": false,
     "start_time": "2020-12-12T13:57:33.224444",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0, 0.5, 'No. of movies')"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "df['Age'].hist(grid=False, xlabelsize=12, ylabelsize=12, color = \"lime\")\n",
    "plt.xlabel(\"Age restriction group\", fontsize=15)\n",
    "plt.ylabel(\"No. of movies\",fontsize=15)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "_cell_guid": "2f3b2bb0-2d8b-48c9-b901-7ea2f31b8794",
    "_uuid": "f4744c9b-9d18-483c-a2d2-5d2f3ee35e96",
    "papermill": {
     "duration": 0.023908,
     "end_time": "2020-12-12T13:57:33.574026",
     "exception": false,
     "start_time": "2020-12-12T13:57:33.550118",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "* Most of the movies released were 18+\n",
    "* The least number of movies produced are 16+"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "_cell_guid": "d8a3e733-519a-4d62-850e-ae48a62043f1",
    "_kg_hide-input": true,
    "_uuid": "15333d5d-c421-49a7-a3d1-c686d8e770d0",
    "execution": {
     "iopub.execute_input": "2020-12-12T13:57:33.635262Z",
     "iopub.status.busy": "2020-12-12T13:57:33.634409Z",
     "iopub.status.idle": "2020-12-12T13:57:33.799549Z",
     "shell.execute_reply": "2020-12-12T13:57:33.798750Z"
    },
    "papermill": {
     "duration": 0.201231,
     "end_time": "2020-12-12T13:57:33.799680",
     "exception": false,
     "start_time": "2020-12-12T13:57:33.598449",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0, 0.5, 'No. of movies')"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "df_tomatoes.hist(grid=False, xlabelsize=12, ylabelsize=12, color = \"red\")\n",
    "plt.xlabel(\"Rotten Tomatoes\", fontsize=15)\n",
    "plt.ylabel(\"No. of movies\",fontsize=15)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "_cell_guid": "b7a378da-5058-4332-9b0a-a7ca8874b7ea",
    "_uuid": "259e1771-a6c4-46de-b09f-72aa5bd2f67e",
    "papermill": {
     "duration": 0.025936,
     "end_time": "2020-12-12T13:57:33.851743",
     "exception": false,
     "start_time": "2020-12-12T13:57:33.825807",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "* Most of the movies prduced had Rotten Tomatoes rating more than 81% followed by 61% - 80%\n",
    "* The least number of movies produced had Rotten Tomatoes rating less than 20%"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2020-12-12T13:57:33.917613Z",
     "iopub.status.busy": "2020-12-12T13:57:33.916493Z",
     "iopub.status.idle": "2020-12-12T13:57:34.073265Z",
     "shell.execute_reply": "2020-12-12T13:57:34.072510Z"
    },
    "papermill": {
     "duration": 0.195023,
     "end_time": "2020-12-12T13:57:34.073390",
     "exception": false,
     "start_time": "2020-12-12T13:57:33.878367",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0, 0.5, 'No. of movies')"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "df_imdb.hist(grid=False, xlabelsize=12, ylabelsize=12, color = \"blue\")\n",
    "plt.xlabel(\"IMDb\", fontsize=15)\n",
    "plt.ylabel(\"No. of movies\",fontsize=15)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "papermill": {
     "duration": 0.027275,
     "end_time": "2020-12-12T13:57:34.128943",
     "exception": false,
     "start_time": "2020-12-12T13:57:34.101668",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "* Majority of the movies had an IMDb rating between 5-6\n",
    "* The least number of movies had rating more or equal to 9\n",
    "* The second highest peak in rating ranges between 7-8, followed by 3-5"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "_cell_guid": "3310da67-56c1-4f64-a3a2-a2e54f87fc1c",
    "_kg_hide-input": true,
    "_uuid": "d1b60d3e-5dfc-4ea8-829c-40b757348d01",
    "execution": {
     "iopub.execute_input": "2020-12-12T13:57:34.201681Z",
     "iopub.status.busy": "2020-12-12T13:57:34.199985Z",
     "iopub.status.idle": "2020-12-12T13:57:34.487965Z",
     "shell.execute_reply": "2020-12-12T13:57:34.488579Z"
    },
    "papermill": {
     "duration": 0.332214,
     "end_time": "2020-12-12T13:57:34.488736",
     "exception": false,
     "start_time": "2020-12-12T13:57:34.156522",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "x_ax = [k for k in genre_freq_dict.keys()]\n",
    "y_ax = [k for k in genre_freq_dict.values()]\n",
    "fig = plt.figure()\n",
    "ax = fig.add_axes([0,0,1,1])\n",
    "genre = x_ax\n",
    "freq = y_ax\n",
    "ax.bar(genre,freq, color = \"purple\")\n",
    "plt.xticks(rotation='vertical')\n",
    "plt.xticks(size = 12)\n",
    "plt.yticks(size = 12)\n",
    "ax.set_ylabel('No. of movies', size = 15)\n",
    "ax.set_title('No. of movies vs. Genres', size = 15)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "_cell_guid": "3dd98053-5c0c-43f0-9209-ac5f4867e975",
    "_uuid": "2017552f-566b-47bf-8796-371d4dcfa35f",
    "papermill": {
     "duration": 0.028512,
     "end_time": "2020-12-12T13:57:34.546296",
     "exception": false,
     "start_time": "2020-12-12T13:57:34.517784",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "* Maximum number of movies produced were \"Drama\" followed by \"Comedy\" genre\n",
    "* Almost negligible number of movies produced were of \"Game-Show\" genre\n",
    "* The number of movies released under \"Reality-TV\", \"Talk-Show\", \"Film-Noire\" and \"News\" genres were a lot less as compared to other genres\n",
    "* The number of movies produced throughout under \"Musical\" and \"Short\" genres were almost similar"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "_cell_guid": "5d2f033d-19e2-4389-903c-62a97ee88b7a",
    "_kg_hide-input": true,
    "_uuid": "fbbfe0fa-843f-45e4-800e-f757e4553955",
    "execution": {
     "iopub.execute_input": "2020-12-12T13:57:34.614638Z",
     "iopub.status.busy": "2020-12-12T13:57:34.613502Z",
     "iopub.status.idle": "2020-12-12T13:57:34.759801Z",
     "shell.execute_reply": "2020-12-12T13:57:34.759089Z"
    },
    "papermill": {
     "duration": 0.184838,
     "end_time": "2020-12-12T13:57:34.759931",
     "exception": false,
     "start_time": "2020-12-12T13:57:34.575093",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "x_aax = [k for k in channel_freq_dict.keys()]\n",
    "y_aax = [k for k in channel_freq_dict.values()]\n",
    "fig = plt.figure()\n",
    "ax = fig.add_axes([0,0,1,1])\n",
    "channel = x_aax\n",
    "freq = y_aax\n",
    "ax.bar(channel,freq, color = \"orange\")\n",
    "plt.xticks(rotation='horizontal')\n",
    "plt.xticks(size = 12)\n",
    "plt.yticks(size = 12)\n",
    "ax.set_ylabel('No. of movies', size = 15)\n",
    "ax.set_title('No. of movies vs. OTT platforms', size = 15)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "_cell_guid": "c514db52-9b87-4fbc-be54-e9439583a963",
    "_uuid": "34aed283-da22-4adf-99f3-78b1ea2f5e83",
    "papermill": {
     "duration": 0.02953,
     "end_time": "2020-12-12T13:57:34.819405",
     "exception": false,
     "start_time": "2020-12-12T13:57:34.789875",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "* Prime Video had the highest number of movies in it as an OTT platform\n",
    "* Disney+ had the lowest number of movies as compared to the other streaming service"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
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