Youtube api analysis.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "b8cfa4d5-ae67-4864-a16b-55ec0f76a890",
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "\n",
    "\n",
    "# Data visualization libraries\n",
    "import matplotlib.pyplot as plt\n",
    "import matplotlib.ticker as ticker\n",
    "import seaborn as sns\n",
    "sns.set(style=\"darkgrid\", color_codes=True)\n",
    "\n",
    "# Google API\n",
    "from googleapiclient.discovery import build"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2bffbd1d-55e5-4501-b0a6-d602bf1707c7",
   "metadata": {},
   "source": [
    "## Data creation with Youtube API\n",
   "Requested an authorization credential (API key) for your project.\r\n",
    "Enabled YouTube API for your application in the Developers Console.\r\n",
    "Obtained the channel IDs of the desired channels from their YouTube URLs.\r\n",
    "Implemented functions to retrieve channel statistics using the YouTube API."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "4b2e8c79-d1c1-4197-a061-1af1106a6d65",
   "metadata": {},
   "outputs": [],
   "source": [
    "api_key = 'AIzaSyB-4NIQtecQPbRX7TWKphThkb9_Brh2wL4' \n",
    "\n",
    "channel_ids = ['UC0GmdVKZhMM3Rmielp4oVAA', # Stefanovic\n",
    "               'UCCezIgC97PvUuR4_gbFUs5g', # Corey Schafer\n",
    "               'UCDybamfye5An6p-j1t2YMsg', # Mo Chen\n",
    "               'UCtoNXlIegvxkvf5Ji8S57Ag', # Lore So What\n",
    "               'UCzL_0nIe8B4-7ShhVPfJkgw', # DatascienceDoJo\n",
    "               'UCLLw7jmFsvfIVaUFsLs8mlQ', # Luke Barousse \n",
    "               'UCiT9RITQ9PW6BhXK0y2jaeg', # Ken Jee\n",
    "               'UC7cs8q-gJRlGwj4A8OmCmXg', # Alex the analyst\n",
    "               'UC2UXDak6o7rBm23k3Vv5dww', # Tina Huang\n",
    "              ]\n",
    "\n",
    "youtube = build('youtube', 'v3', developerKey=api_key)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "1051d355-e35d-4e4b-9398-390db5ea4be7",
   "metadata": {},
   "source": [
    "# Function to get Channel Statistics"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "33ebd28f-0fa3-4b3d-bab1-c670d7e32b2a",
   "metadata": {},
   "outputs": [],
   "source": [
    "def get_channel_stats(youtube, channel_ids):\n",
    "    \"\"\"\n",
    "    Get channel statistics: title, subscriber count, view count, video count, upload playlist\n",
    "    Params:\n",
    "    \n",
    "    youtube: the build object from googleapiclient.discovery\n",
    "    channels_ids: list of channel IDs\n",
    "    \n",
    "    Returns:\n",
    "    Dataframe containing the channel statistics for all channels in the provided list: title, subscriber count, view count, video count, upload playlist\n",
    "    \n",
    "    \"\"\"\n",
    "    all_data = []\n",
    "    request = youtube.channels().list(\n",
    "                part='snippet,contentDetails,statistics',\n",
    "                id=','.join(channel_ids))\n",
    "    response = request.execute() \n",
    "    \n",
    "    for i in range(len(response['items'])):\n",
    "        data = dict(channelName = response['items'][i]['snippet']['title'],\n",
    "                    subscribers = response['items'][i]['statistics']['subscriberCount'],\n",
    "                    views = response['items'][i]['statistics']['viewCount'],\n",
    "                    totalVideos = response['items'][i]['statistics']['videoCount'],\n",
    "                    playlistId = response['items'][i]['contentDetails']['relatedPlaylists']['uploads'])\n",
    "        all_data.append(data)\n",
    "    \n",
    "    return pd.DataFrame(all_data)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "id": "c5b8b30e-ca50-4709-9a08-a6c59d8d071c",
   "metadata": {},
   "outputs": [],
   "source": [
    "channel_data = get_channel_stats(youtube, channel_ids)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "id": "9877e0a8-0d19-48b9-a8a4-c973e9e26f2a",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "channelName    object\n",
       "subscribers    object\n",
       "views          object\n",
       "totalVideos    object\n",
       "playlistId     object\n",
       "dtype: object"
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "channel_data.dtypes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "id": "19fe9f7b-0ae6-4eca-89b6-053002d9f2d7",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "channelName    object\n",
       "subscribers    object\n",
       "views          object\n",
       "totalVideos    object\n",
       "playlistId     object\n",
       "Subscribers     int64\n",
       "Views           int64\n",
       "TotalVideos     int64\n",
       "dtype: object"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#converting object to integer\n",
    "channel_data['Subscribers']= pd.to_numeric(channel_data['subscribers'])\n",
    "channel_data['Views']= pd.to_numeric(channel_data['views'])\n",
    "channel_data['TotalVideos']= pd.to_numeric(channel_data['totalVideos'])\n",
    "channel_data.dtypes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "id": "f061a5a2-ed88-46af-8c98-4aec1ecca798",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\sloru\\AppData\\Local\\Temp\\ipykernel_9204\\336799715.py:4: UserWarning: \n",
      "The palette list has fewer values (4) than needed (9) and will cycle, which may produce an uninterpretable plot.\n",
      "  ax = sns.barplot(x='channelName', y='subscribers', data=channel_data, hue='channelName', palette=custom_colors, legend=False)\n"
     ]
    },
    {
     "data": {
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",
      "text/plain": [
       "<Figure size 700x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.set(rc={'figure.figsize': (7, 5)})\n",
    "sns.set(style=\"whitegrid\")\n",
    "custom_colors = ['skyblue', 'lightcoral', 'lightgreen', 'yellow']\n",
    "ax = sns.barplot(x='channelName', y='subscribers', data=channel_data, hue='channelName', palette=custom_colors, legend=False)\n",
    "\n",
    "# Reverse the y-axis\n",
    "ax.invert_yaxis()\n",
    "\n",
    "plt.xticks(rotation=45, ha=\"right\")  # Adjust the rotation angle as needed\n",
    "\n",
    "# Show the plot\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "id": "823e0262-854c-4d0e-914c-d3fb8db2667e",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\sloru\\AppData\\Local\\Temp\\ipykernel_2460\\712928513.py:4: UserWarning: set_ticklabels() should only be used with a fixed number of ticks, i.e. after set_ticks() or using a FixedLocator.\n",
      "  plot = ax.set_xticklabels(ax.get_xticklabels(),rotation = 90)\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x800 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "ax = sns.barplot(x='channelName', y='views', data=channel_data.sort_values('views', ascending=False),hue='channelName', palette=custom_colors, legend=False)\n",
    "custom_colors = ['skyblue', 'lightcoral', 'lightgreen', 'yellow','red', 'pink', 'blue','green','orange']\n",
    "ax.yaxis.set_major_formatter(ticker.FuncFormatter(lambda x, pos: '{:,.0f}'.format(x/1000) + 'K'))\n",
    "plot = ax.set_xticklabels(ax.get_xticklabels(),rotation = 90)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 85,
   "id": "d22520f1-51a9-4283-84fc-db89a9fe243a",
   "metadata": {},
   "outputs": [],
   "source": [
    "#Sentdex and Corey Schafer top both metrics. Notably, some channels differ – Ken Jee has more subscribers but slightly fewer views than Luke Barousse.."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d2c44416-261f-4f94-b583-1fd4fac660cf",
   "metadata": {},
   "source": [
    "### Funtion to get video ids"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "id": "fb0c9210-ca8d-4c7a-b321-90a1af599c34",
   "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>channelName</th>\n",
       "      <th>subscribers</th>\n",
       "      <th>views</th>\n",
       "      <th>totalVideos</th>\n",
       "      <th>playlistId</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Ken Jee</td>\n",
       "      <td>256000</td>\n",
       "      <td>8800395</td>\n",
       "      <td>286</td>\n",
       "      <td>UUiT9RITQ9PW6BhXK0y2jaeg</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Alex The Analyst</td>\n",
       "      <td>678000</td>\n",
       "      <td>29014766</td>\n",
       "      <td>279</td>\n",
       "      <td>UU7cs8q-gJRlGwj4A8OmCmXg</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Luke Barousse</td>\n",
       "      <td>405000</td>\n",
       "      <td>19876198</td>\n",
       "      <td>151</td>\n",
       "      <td>UULLw7jmFsvfIVaUFsLs8mlQ</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Data Science Dojo</td>\n",
       "      <td>102000</td>\n",
       "      <td>5785161</td>\n",
       "      <td>468</td>\n",
       "      <td>UUzL_0nIe8B4-7ShhVPfJkgw</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Mo Chen</td>\n",
       "      <td>80200</td>\n",
       "      <td>2536985</td>\n",
       "      <td>85</td>\n",
       "      <td>UUDybamfye5An6p-j1t2YMsg</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>Tina Huang</td>\n",
       "      <td>602000</td>\n",
       "      <td>27874257</td>\n",
       "      <td>180</td>\n",
       "      <td>UU2UXDak6o7rBm23k3Vv5dww</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>Stefanovic</td>\n",
       "      <td>264000</td>\n",
       "      <td>9457105</td>\n",
       "      <td>81</td>\n",
       "      <td>UU0GmdVKZhMM3Rmielp4oVAA</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>Lore So What</td>\n",
       "      <td>19800</td>\n",
       "      <td>917571</td>\n",
       "      <td>91</td>\n",
       "      <td>UUtoNXlIegvxkvf5Ji8S57Ag</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>Corey Schafer</td>\n",
       "      <td>1250000</td>\n",
       "      <td>92144301</td>\n",
       "      <td>232</td>\n",
       "      <td>UUCezIgC97PvUuR4_gbFUs5g</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "         channelName subscribers     views totalVideos  \\\n",
       "0            Ken Jee      256000   8800395         286   \n",
       "1   Alex The Analyst      678000  29014766         279   \n",
       "2      Luke Barousse      405000  19876198         151   \n",
       "3  Data Science Dojo      102000   5785161         468   \n",
       "4            Mo Chen       80200   2536985          85   \n",
       "5         Tina Huang      602000  27874257         180   \n",
       "6         Stefanovic      264000   9457105          81   \n",
       "7       Lore So What       19800    917571          91   \n",
       "8      Corey Schafer     1250000  92144301         232   \n",
       "\n",
       "                 playlistId  \n",
       "0  UUiT9RITQ9PW6BhXK0y2jaeg  \n",
       "1  UU7cs8q-gJRlGwj4A8OmCmXg  \n",
       "2  UULLw7jmFsvfIVaUFsLs8mlQ  \n",
       "3  UUzL_0nIe8B4-7ShhVPfJkgw  \n",
       "4  UUDybamfye5An6p-j1t2YMsg  \n",
       "5  UU2UXDak6o7rBm23k3Vv5dww  \n",
       "6  UU0GmdVKZhMM3Rmielp4oVAA  \n",
       "7  UUtoNXlIegvxkvf5Ji8S57Ag  \n",
       "8  UUCezIgC97PvUuR4_gbFUs5g  "
      ]
     },
     "execution_count": 47,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "channel_data\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "id": "55b1030c-41a6-45fc-a37c-d9741ffd0595",
   "metadata": {},
   "outputs": [],
   "source": [
    "playlist_id = channel_data.loc[channel_data['channelName'] == 'Corey Schafer', 'playlistId'].iloc[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "id": "11c36d1a-1e2f-4a4a-bd7d-2da1258060d7",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'UUCezIgC97PvUuR4_gbFUs5g'"
      ]
     },
     "execution_count": 49,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "playlist_id"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "id": "fc062de3-a7a0-49d2-8298-9666947d10dc",
   "metadata": {},
   "outputs": [],
   "source": [
    "#getting video ids\n",
    "def get_video_ids(youtube, playlist_id):\n",
    "    #Get list of video IDs of all videos in the given playlist\n",
    "        \n",
    "    request = youtube.playlistItems().list(\n",
    "                part='contentDetails',\n",
    "                playlistId = playlist_id,\n",
    "                maxResults = 50)\n",
    "    response = request.execute()\n",
    "\n",
    "    video_ids= []\n",
    "    \n",
    "    for i in range(len(response['items'])):\n",
    "        video_ids.append(response['items'][i]['contentDetails']['videoId'])\n",
    "\n",
    "    next_page_token = response.get('nextPageToken')\n",
    "    more_pages = True\n",
    "    \n",
    "    while more_pages:\n",
    "        if next_page_token is None:\n",
    "           more_pages = False\n",
    "        else:\n",
    "            request = youtube.playlistItems().list(\n",
    "                       part='contentDetails',\n",
    "                       playlistId = playlist_id,\n",
    "                       maxResults = 50,\n",
    "                        pageToken = next_page_token)\n",
    "            response = request.execute()\n",
    "\n",
    "            for i in range(len(response['items'])):\n",
    "                video_ids.append(response['items'][i]['contentDetails']['videoId'])\n",
    "            \n",
    "            next_page_token = response.get('nextPageToken')\n",
    "        \n",
    "    return (video_ids)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "id": "8875e576-5946-4765-9464-4da0725a6adb",
   "metadata": {},
   "outputs": [],
   "source": [
    "video_ids= get_video_ids(youtube, playlist_id)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 95,
   "id": "a4c59029-47ee-4dc7-8a8f-ced95d105b9f",
   "metadata": {},
   "outputs": [
    {
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     },
     "execution_count": 95,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "video_ids"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "222fefdb-7ded-4ff8-9e21-299d372afab9",
   "metadata": {},
   "source": [
    "# Function to get video details"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "id": "70341a5f-a239-4a04-ac9a-b8dfd1d60479",
   "metadata": {},
   "outputs": [],
   "source": [
    "def get_video_details(youtube,video_ids):\n",
    " #   Get video statistics of all videos with given IDs\n",
    "    all_video_info = []\n",
    "    \n",
    "    for i in range(0, len(video_ids), 50):\n",
    "      request = youtube.videos().list(\n",
    "            part=\"snippet,statistics\",\n",
    "            id=','.join(video_ids[i:i+50]))\n",
    "      response = request.execute() \n",
    "    \n",
    "      for video in response['items']:\n",
    "          video_info = dict(Title= video['snippet']['title'],  \n",
    "                              Published_date = video['snippet']['publishedAt'], \n",
    "                              Views = video ['statistics']['viewCount'], \n",
    "                              Likes = video['statistics']['likeCount'], \n",
    "                              Favorite = video['statistics']['favoriteCount'], \n",
    "                              Comments = video['statistics']['commentCount'],\n",
    "                            )\n",
    "          all_video_info.append(video_info)\n",
    "   \n",
    "    return all_video_info"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "id": "77e19f61-edaf-4f53-99e0-1a51579486c1",
   "metadata": {},
   "outputs": [],
   "source": [
    "video_details = get_video_details(youtube,video_ids)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "id": "1b49ec23-d8af-457e-8bc5-ed88613d2468",
   "metadata": {},
   "outputs": [],
   "source": [
    "video_data = pd.DataFrame(video_details)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "id": "c4e653dc-8f66-4e3a-aec6-5d0ee3d64ba4",
   "metadata": {},
   "outputs": [],
   "source": [
    "video_data['Published_date'] = pd.to_datetime(video_data['Published_date']).dt.date  #only date no timestamps\n",
    "video_data['Views'] = pd.to_numeric(video_data['Views'])\n",
    "video_data['Likes'] = pd.to_numeric(video_data['Likes'])\n",
    "video_data['Favorite'] = pd.to_numeric(video_data['Favorite'])\n",
    "video_data['Comments'] = pd.to_numeric(video_data['Comments'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "id": "ea1c4ca3-1e8f-42d4-ade6-a40eb623993c",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Title             object\n",
       "Published_date    object\n",
       "Views              int64\n",
       "Likes              int64\n",
       "Favorite           int64\n",
       "Comments           int64\n",
       "dtype: object"
      ]
     },
     "execution_count": 56,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "video_data.dtypes"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "64262a17-3366-4c62-a2d5-bd3809fb6347",
   "metadata": {},
   "source": [
    "# Top 10 videos by Corey Schafer\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "id": "ad03cb6f-123f-4c89-a114-50aff2a38386",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<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>Title</th>\n",
       "      <th>Published_date</th>\n",
       "      <th>Views</th>\n",
       "      <th>Likes</th>\n",
       "      <th>Favorite</th>\n",
       "      <th>Comments</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>How to Use ChatGPT as a Powerful Tool for Prog...</td>\n",
       "      <td>2023-05-21</td>\n",
       "      <td>270729</td>\n",
       "      <td>7564</td>\n",
       "      <td>0</td>\n",
       "      <td>436</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Python Tutorial: Simulate the Powerball Lotter...</td>\n",
       "      <td>2023-01-09</td>\n",
       "      <td>136408</td>\n",
       "      <td>4257</td>\n",
       "      <td>0</td>\n",
       "      <td>772</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Python YouTube API Tutorial: Using OAuth to Ac...</td>\n",
       "      <td>2020-09-10</td>\n",
       "      <td>138854</td>\n",
       "      <td>2661</td>\n",
       "      <td>0</td>\n",
       "      <td>351</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Python YouTube API Tutorial: Sort a Playlist b...</td>\n",
       "      <td>2020-07-31</td>\n",
       "      <td>45716</td>\n",
       "      <td>1099</td>\n",
       "      <td>0</td>\n",
       "      <td>129</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Python YouTube API Tutorial: Calculating the D...</td>\n",
       "      <td>2020-06-10</td>\n",
       "      <td>55877</td>\n",
       "      <td>1598</td>\n",
       "      <td>0</td>\n",
       "      <td>177</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>228</th>\n",
       "      <td>Lab Puppy playing fetch in a lake</td>\n",
       "      <td>2014-04-25</td>\n",
       "      <td>13528</td>\n",
       "      <td>443</td>\n",
       "      <td>0</td>\n",
       "      <td>19</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>229</th>\n",
       "      <td>Lab Puppy playing fetch in a creek</td>\n",
       "      <td>2014-04-25</td>\n",
       "      <td>12859</td>\n",
       "      <td>285</td>\n",
       "      <td>0</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>230</th>\n",
       "      <td>If I'm running even 1 minute late for my dog's...</td>\n",
       "      <td>2014-04-25</td>\n",
       "      <td>75317</td>\n",
       "      <td>1647</td>\n",
       "      <td>0</td>\n",
       "      <td>72</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>231</th>\n",
       "      <td>Lab Puppy Diving in Snow</td>\n",
       "      <td>2014-03-22</td>\n",
       "      <td>27846</td>\n",
       "      <td>534</td>\n",
       "      <td>0</td>\n",
       "      <td>17</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>232</th>\n",
       "      <td>Lab puppy playing in bath tub</td>\n",
       "      <td>2014-01-20</td>\n",
       "      <td>26893</td>\n",
       "      <td>767</td>\n",
       "      <td>0</td>\n",
       "      <td>39</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>233 rows × 6 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                                                 Title Published_date   Views  \\\n",
       "0    How to Use ChatGPT as a Powerful Tool for Prog...     2023-05-21  270729   \n",
       "1    Python Tutorial: Simulate the Powerball Lotter...     2023-01-09  136408   \n",
       "2    Python YouTube API Tutorial: Using OAuth to Ac...     2020-09-10  138854   \n",
       "3    Python YouTube API Tutorial: Sort a Playlist b...     2020-07-31   45716   \n",
       "4    Python YouTube API Tutorial: Calculating the D...     2020-06-10   55877   \n",
       "..                                                 ...            ...     ...   \n",
       "228                  Lab Puppy playing fetch in a lake     2014-04-25   13528   \n",
       "229                 Lab Puppy playing fetch in a creek     2014-04-25   12859   \n",
       "230  If I'm running even 1 minute late for my dog's...     2014-04-25   75317   \n",
       "231                           Lab Puppy Diving in Snow     2014-03-22   27846   \n",
       "232                      Lab puppy playing in bath tub     2014-01-20   26893   \n",
       "\n",
       "     Likes  Favorite  Comments  \n",
       "0     7564         0       436  \n",
       "1     4257         0       772  \n",
       "2     2661         0       351  \n",
       "3     1099         0       129  \n",
       "4     1598         0       177  \n",
       "..     ...       ...       ...  \n",
       "228    443         0        19  \n",
       "229    285         0         6  \n",
       "230   1647         0        72  \n",
       "231    534         0        17  \n",
       "232    767         0        39  \n",
       "\n",
       "[233 rows x 6 columns]"
      ]
     },
     "execution_count": 57,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "video_data"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "11781624-6022-4dce-ad60-84b6c11abcd7",
   "metadata": {},
   "source": [
    "#### In the next step, we will obtain the video statistics for all the channels. In total, we obtained 3,722 videos as seen in below."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "id": "533a5aa7-675e-4639-a1f6-a0dd9fc7a93a",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[{'Title': 'The Digital Nomad Dream is Dead (and this is replacing it)',\n",
       "  'Published_date': '2024-01-15T19:02:40Z',\n",
       "  'Views': '9572',\n",
       "  'Likes': '739',\n",
       "  'Favorite': '0',\n",
       "  'Comments': '80'},\n",
       " {'Title': 'I Survived a 50 Hour Dopamine Detox (Extreme Mode)',\n",
       "  'Published_date': '2023-12-19T19:08:29Z',\n",
       "  'Views': '7987',\n",
       "  'Likes': '500',\n",
       "  'Favorite': '0',\n",
       "  'Comments': '95'},\n",
       " {'Title': 'Asking Digital Nomads How They Make Money',\n",
       "  'Published_date': '2023-10-20T15:39:59Z',\n",
       "  'Views': '24319',\n",
       "  'Likes': '885',\n",
       "  'Favorite': '0',\n",
       "  'Comments': '73'},\n",
       " {'Title': 'How To Waste The Rest Of Your Life (Starting Today)',\n",
       "  'Published_date': '2023-08-03T13:00:44Z',\n",
       "  'Views': '25009',\n",
       "  'Likes': '1700',\n",
       "  'Favorite': '0',\n",
       "  'Comments': '187'},\n",
       " {'Title': 'I Tried Making $500/Day Using These 12 Side Hustles',\n",
       "  'Published_date': '2023-06-29T16:12:27Z',\n",
       "  'Views': '692003',\n",
       "  'Likes': '22546',\n",
       "  'Favorite': '0',\n",
       "  'Comments': '1225'},\n",
       " {'Title': 'Asking Solopreneurs How To Make $1,000,000',\n",
       "  'Published_date': '2023-05-22T15:06:35Z',\n",
       "  'Views': '420417',\n",
       "  'Likes': '11089',\n",
       "  'Favorite': '0',\n",
       "  'Comments': '204'},\n",
       " {'Title': 'How to stay productive 96% of every day (for normal people)',\n",
       "  'Published_date': '2023-04-07T11:58:54Z',\n",
       "  'Views': '133263',\n",
       "  'Likes': '6135',\n",
       "  'Favorite': '0',\n",
       "  'Comments': '220'},\n",
       " {'Title': 'Quitting My 9-5 Job Was A Huge Mistake',\n",
       "  'Published_date': '2023-03-16T13:56:15Z',\n",
       "  'Views': '68902',\n",
       "  'Likes': '3602',\n",
       "  'Favorite': '0',\n",
       "  'Comments': '363'},\n",
       " {'Title': 'Quitting My 9-5 Job Saved My Life: My Story',\n",
       "  'Published_date': '2023-02-21T17:18:18Z',\n",
       "  'Views': '32356',\n",
       "  'Likes': '1726',\n",
       "  'Favorite': '0',\n",
       "  'Comments': '243'},\n",
       " {'Title': 'How To Get Ahead Of 99% Of People (In 180 days)',\n",
       "  'Published_date': '2023-01-23T16:09:19Z',\n",
       "  'Views': '250454',\n",
       "  'Likes': '15539',\n",
       "  'Favorite': '0',\n",
       "  'Comments': '579'},\n",
       " {'Title': 'How To Start a Recession-Proof Business (5 requirements)',\n",
       "  'Published_date': '2022-12-26T14:23:26Z',\n",
       "  'Views': '18917',\n",
       "  'Likes': '1302',\n",
       "  'Favorite': '0',\n",
       "  'Comments': '17'},\n",
       " {'Title': 'Recession 2023: How To Get Rich',\n",
       "  'Published_date': '2022-12-17T15:00:25Z',\n",
       "  'Views': '30437',\n",
       "  'Likes': '1778',\n",
       "  'Favorite': '0',\n",
       "  'Comments': '113'},\n",
       " {'Title': 'The ONLY 2 reasons you should be working a 9-5',\n",
       "  'Published_date': '2022-11-10T16:33:28Z',\n",
       "  'Views': '145831',\n",
       "  'Likes': '11590',\n",
       "  'Favorite': '0',\n",
       "  'Comments': '302'},\n",
       " {'Title': 'The Rise of Ultra Rich Young Youtubers: The Dark Truth',\n",
       "  'Published_date': '2022-11-04T13:49:07Z',\n",
       "  'Views': '1060585',\n",
       "  'Likes': '64604',\n",
       "  'Favorite': '0',\n",
       "  'Comments': '3117'},\n",
       " {'Title': 'How To Figure Out What To Do With Your Life',\n",
       "  'Published_date': '2022-10-31T19:36:46Z',\n",
       "  'Views': '41351',\n",
       "  'Likes': '5291',\n",
       "  'Favorite': '0',\n",
       "  'Comments': '74'},\n",
       " {'Title': 'How I Would Learn Data Analysis (If I Could Start Over)',\n",
       "  'Published_date': '2022-10-24T13:43:39Z',\n",
       "  'Views': '518357',\n",
       "  'Likes': '30890',\n",
       "  'Favorite': '0',\n",
       "  'Comments': '455'},\n",
       " {'Title': 'FASTEST Way to Become a Freelancer and ACTUALLY Get Freelance Jobs',\n",
       "  'Published_date': '2022-10-12T16:06:58Z',\n",
       "  'Views': '66574',\n",
       "  'Likes': '2967',\n",
       "  'Favorite': '0',\n",
       "  'Comments': '102'},\n",
       " {'Title': 'How I Travel The World Without A Job (4 Income Streams)',\n",
       "  'Published_date': '2022-09-26T14:41:56Z',\n",
       "  'Views': '68870',\n",
       "  'Likes': '3711',\n",
       "  'Favorite': '0',\n",
       "  'Comments': '252'},\n",
       " {'Title': 'Becoming a Freelancer Saved My Life',\n",
       "  'Published_date': '2022-08-22T15:22:20Z',\n",
       "  'Views': '112819',\n",
       "  'Likes': '6712',\n",
       "  'Favorite': '0',\n",
       "  'Comments': '503'},\n",
       " {'Title': 'FASTEST Way to Become a Data Analyst and ACTUALLY Get a Job',\n",
       "  'Published_date': '2022-07-11T13:07:22Z',\n",
       "  'Views': '2719746',\n",
       "  'Likes': '105337',\n",
       "  'Favorite': '0',\n",
       "  'Comments': '1470'},\n",
       " {'Title': 'How To Stick To Your Habits While Traveling',\n",
       "  'Published_date': '2022-07-01T13:00:23Z',\n",
       "  'Views': '10980',\n",
       "  'Likes': '607',\n",
       "  'Favorite': '0',\n",
       "  'Comments': '67'},\n",
       " {'Title': '3 SHORT Books That Changed My Life (under 200 pages)',\n",
       "  'Published_date': '2022-06-09T13:38:49Z',\n",
       "  'Views': '23229',\n",
       "  'Likes': '1350',\n",
       "  'Favorite': '0',\n",
       "  'Comments': '92'},\n",
       " {'Title': '3 Life Lessons I learned working as a Data Analyst',\n",
       "  'Published_date': '2022-05-04T13:33:29Z',\n",
       "  'Views': '32277',\n",
       "  'Likes': '1856',\n",
       "  'Favorite': '0',\n",
       "  'Comments': '116'},\n",
       " {'Title': 'If Daily Standups Were 100% Honest',\n",
       "  'Published_date': '2022-04-22T11:36:22Z',\n",
       "  'Views': '11989',\n",
       "  'Likes': '767',\n",
       "  'Favorite': '0',\n",
       "  'Comments': '82'},\n",
       " {'Title': 'We Spent 1 Month Living On \"DEATH ISLAND\"',\n",
       "  'Published_date': '2022-04-18T16:11:51Z',\n",
       "  'Views': '7196',\n",
       "  'Likes': '397',\n",
       "  'Favorite': '0',\n",
       "  'Comments': '82'},\n",
       " {'Title': '5 Linkedin Profile Tips to Get a Data Analyst Job',\n",
       "  'Published_date': '2022-04-11T17:22:45Z',\n",
       "  'Views': '104703',\n",
       "  'Likes': '6412',\n",
       "  'Favorite': '0',\n",
       "  'Comments': '132'},\n",
       " {'Title': \"I Worked a Tech Job For 2000 Days.. Here's What Happened\",\n",
       "  'Published_date': '2022-03-30T15:52:27Z',\n",
       "  'Views': '108301',\n",
       "  'Likes': '5500',\n",
       "  'Favorite': '0',\n",
       "  'Comments': '480'},\n",
       " {'Title': 'The reality of traveling the world (nothing goes as planned)',\n",
       "  'Published_date': '2022-03-17T04:10:56Z',\n",
       "  'Views': '15146',\n",
       "  'Likes': '922',\n",
       "  'Favorite': '0',\n",
       "  'Comments': '188'},\n",
       " {'Title': 'The REAL Reason I Quit My 6-Figure Data Analyst Job',\n",
       "  'Published_date': '2022-03-07T17:43:04Z',\n",
       "  'Views': '68637',\n",
       "  'Likes': '3425',\n",
       "  'Favorite': '0',\n",
       "  'Comments': '210'},\n",
       " {'Title': 'data analyst quits job to become a youtuber',\n",
       "  'Published_date': '2022-02-28T11:17:53Z',\n",
       "  'Views': '8747',\n",
       "  'Likes': '684',\n",
       "  'Favorite': '0',\n",
       "  'Comments': '122'},\n",
       " {'Title': '5 things I wish I knew in my 20s',\n",
       "  'Published_date': '2022-02-21T10:32:02Z',\n",
       "  'Views': '29390',\n",
       "  'Likes': '2244',\n",
       "  'Favorite': '0',\n",
       "  'Comments': '175'},\n",
       " {'Title': 'Life is a game. This is how you win',\n",
       "  'Published_date': '2022-02-12T15:20:28Z',\n",
       "  'Views': '22422',\n",
       "  'Likes': '2242',\n",
       "  'Favorite': '0',\n",
       "  'Comments': '227'},\n",
       " {'Title': \"We ate the world's OLDEST soup\",\n",
       "  'Published_date': '2022-01-31T10:32:21Z',\n",
       "  'Views': '12212',\n",
       "  'Likes': '444',\n",
       "  'Favorite': '0',\n",
       "  'Comments': '88'},\n",
       " {'Title': 'Day in the Life of a \"Retired\" Data Analyst',\n",
       "  'Published_date': '2022-01-26T18:21:06Z',\n",
       "  'Views': '40966',\n",
       "  'Likes': '2183',\n",
       "  'Favorite': '0',\n",
       "  'Comments': '263'},\n",
       " {'Title': 'I QUIT my $170,000 Data Analyst Job After Learning 3 Lessons',\n",
       "  'Published_date': '2022-01-17T10:58:08Z',\n",
       "  'Views': '1000332',\n",
       "  'Likes': '41012',\n",
       "  'Favorite': '0',\n",
       "  'Comments': '1899'},\n",
       " {'Title': 'We Tried the Famous Michelin Star Thai Street Food Restaurant - Jay Fai',\n",
       "  'Published_date': '2022-01-10T14:58:46Z',\n",
       "  'Views': '7872',\n",
       "  'Likes': '398',\n",
       "  'Favorite': '0',\n",
       "  'Comments': '51'},\n",
       " {'Title': 'We picked the worst year ever to travel the world',\n",
       "  'Published_date': '2022-01-07T12:12:28Z',\n",
       "  'Views': '10761',\n",
       "  'Likes': '437',\n",
       "  'Favorite': '0',\n",
       "  'Comments': '100'},\n",
       " {'Title': \"What I'm packing for 1 year of travel\",\n",
       "  'Published_date': '2022-01-01T15:58:59Z',\n",
       "  'Views': '6378',\n",
       "  'Likes': '286',\n",
       "  'Favorite': '0',\n",
       "  'Comments': '89'},\n",
       " {'Title': 'Final preparations before we start traveling the world',\n",
       "  'Published_date': '2021-12-14T13:04:36Z',\n",
       "  'Views': '3345',\n",
       "  'Likes': '195',\n",
       "  'Favorite': '0',\n",
       "  'Comments': '61'},\n",
       " {'Title': 'Vlogging for the first time is HARD',\n",
       "  'Published_date': '2021-11-30T18:47:58Z',\n",
       "  'Views': '5216',\n",
       "  'Likes': '306',\n",
       "  'Favorite': '0',\n",
       "  'Comments': '62'},\n",
       " {'Title': 'Q&A: I have cried',\n",
       "  'Published_date': '2021-11-17T16:50:59Z',\n",
       "  'Views': '5623',\n",
       "  'Likes': '304',\n",
       "  'Favorite': '0',\n",
       "  'Comments': '51'},\n",
       " {'Title': 'Top 5 Youtubers I Watch The Most',\n",
       "  'Published_date': '2021-11-10T16:44:41Z',\n",
       "  'Views': '12963',\n",
       "  'Likes': '653',\n",
       "  'Favorite': '0',\n",
       "  'Comments': '56'},\n",
       " {'Title': 'Preparing for a 1 year trip around the world is HARD',\n",
       "  'Published_date': '2021-11-01T13:09:41Z',\n",
       "  'Views': '4504',\n",
       "  'Likes': '237',\n",
       "  'Favorite': '0',\n",
       "  'Comments': '60'},\n",
       " {'Title': 'How I Became a Data Analyst (without a related degree)',\n",
       "  'Published_date': '2021-10-17T14:03:58Z',\n",
       "  'Views': '246478',\n",
       "  'Likes': '12390',\n",
       "  'Favorite': '0',\n",
       "  'Comments': '484'},\n",
       " {'Title': 'For people without a purpose in life: READ THIS TWEET',\n",
       "  'Published_date': '2021-10-11T19:05:22Z',\n",
       "  'Views': '10454',\n",
       "  'Likes': '808',\n",
       "  'Favorite': '0',\n",
       "  'Comments': '47'},\n",
       " {'Title': '5 Reasons Why You Should Quit Your Office Job',\n",
       "  'Published_date': '2021-10-04T17:06:19Z',\n",
       "  'Views': '19093',\n",
       "  'Likes': '875',\n",
       "  'Favorite': '0',\n",
       "  'Comments': '86'},\n",
       " {'Title': 'Covid ruined our 2022 travel plans',\n",
       "  'Published_date': '2021-09-02T19:44:58Z',\n",
       "  'Views': '2967',\n",
       "  'Likes': '96',\n",
       "  'Favorite': '0',\n",
       "  'Comments': '41'},\n",
       " {'Title': 'ONE piece of advice to my 18-year-old self',\n",
       "  'Published_date': '2021-08-02T15:00:36Z',\n",
       "  'Views': '6881',\n",
       "  'Likes': '512',\n",
       "  'Favorite': '0',\n",
       "  'Comments': '75'},\n",
       " {'Title': \"when things don't go as planned\",\n",
       "  'Published_date': '2021-07-27T08:35:44Z',\n",
       "  'Views': '1590',\n",
       "  'Likes': '137',\n",
       "  'Favorite': '0',\n",
       "  'Comments': '63'},\n",
       " {'Title': '4 reasons why you should leave your hometown',\n",
       "  'Published_date': '2021-06-29T20:14:00Z',\n",
       "  'Views': '9894',\n",
       "  'Likes': '555',\n",
       "  'Favorite': '0',\n",
       "  'Comments': '94'},\n",
       " {'Title': 'Day in the Life of a Data Analyst  (Work From Home)',\n",
       "  'Published_date': '2021-06-22T12:12:14Z',\n",
       "  'Views': '814968',\n",
       "  'Likes': '25981',\n",
       "  'Favorite': '0',\n",
       "  'Comments': '1007'},\n",
       " {'Title': 'The PSYCHOLOGICAL reason I bought a $4000 camera',\n",
       "  'Published_date': '2021-06-07T17:11:13Z',\n",
       "  'Views': '2908',\n",
       "  'Likes': '221',\n",
       "  'Favorite': '0',\n",
       "  'Comments': '80'},\n",
       " {'Title': 'what you got wrong about retirement',\n",
       "  'Published_date': '2021-06-01T13:33:02Z',\n",
       "  'Views': '3110',\n",
       "  'Likes': '300',\n",
       "  'Favorite': '0',\n",
       "  'Comments': '56'},\n",
       " {'Title': 'Things I wish I knew before starting Youtube (as a starting Youtuber)',\n",
       "  'Published_date': '2021-05-24T17:50:41Z',\n",
       "  'Views': '4202',\n",
       "  'Likes': '354',\n",
       "  'Favorite': '0',\n",
       "  'Comments': '88'},\n",
       " {'Title': \"Matt D'Avella's Master Youtube course review (Matt D'Avella style)\",\n",
       "  'Published_date': '2021-05-19T10:42:11Z',\n",
       "  'Views': '43929',\n",
       "  'Likes': '2496',\n",
       "  'Favorite': '0',\n",
       "  'Comments': '303'},\n",
       " {'Title': 'How to follow my journey around the world (+ Ask Me Anything Event)',\n",
       "  'Published_date': '2021-05-12T14:40:56Z',\n",
       "  'Views': '1712',\n",
       "  'Likes': '79',\n",
       "  'Favorite': '0',\n",
       "  'Comments': '28'},\n",
       " {'Title': 'Most important Personality Characteristic for SUCCESS',\n",
       "  'Published_date': '2021-05-10T19:56:23Z',\n",
       "  'Views': '2920',\n",
       "  'Likes': '214',\n",
       "  'Favorite': '0',\n",
       "  'Comments': '35'},\n",
       " {'Title': 'Best advice I have EVER heard',\n",
       "  'Published_date': '2021-05-03T14:24:44Z',\n",
       "  'Views': '24951',\n",
       "  'Likes': '1372',\n",
       "  'Favorite': '0',\n",
       "  'Comments': '115'},\n",
       " {'Title': 'One thing COVID-19 lockdown has taught me',\n",
       "  'Published_date': '2021-04-26T18:03:06Z',\n",
       "  'Views': '1336',\n",
       "  'Likes': '98',\n",
       "  'Favorite': '0',\n",
       "  'Comments': '31'},\n",
       " {'Title': 'best investment I have EVER made',\n",
       "  'Published_date': '2021-04-19T13:38:23Z',\n",
       "  'Views': '4658',\n",
       "  'Likes': '232',\n",
       "  'Favorite': '0',\n",
       "  'Comments': '58'},\n",
       " {'Title': 'My Top 5 Favorite Podcasts (2021)',\n",
       "  'Published_date': '2021-04-12T13:16:16Z',\n",
       "  'Views': '7080',\n",
       "  'Likes': '186',\n",
       "  'Favorite': '0',\n",
       "  'Comments': '52'},\n",
       " {'Title': 'Being Happy Now vs. Constantly Improving Yourself',\n",
       "  'Published_date': '2021-04-09T11:00:14Z',\n",
       "  'Views': '4659',\n",
       "  'Likes': '336',\n",
       "  'Favorite': '0',\n",
       "  'Comments': '58'},\n",
       " {'Title': '3 Steps To Financial Freedom',\n",
       "  'Published_date': '2021-04-05T10:19:47Z',\n",
       "  'Views': '3693',\n",
       "  'Likes': '275',\n",
       "  'Favorite': '0',\n",
       "  'Comments': '31'},\n",
       " {'Title': '4 Types of Wealth for a Rich Life',\n",
       "  'Published_date': '2021-03-29T13:53:14Z',\n",
       "  'Views': '1711',\n",
       "  'Likes': '108',\n",
       "  'Favorite': '0',\n",
       "  'Comments': '38'},\n",
       " {'Title': 'One Book that MOST Changed My Life #OneMinuteMonday',\n",
       "  'Published_date': '2021-03-22T19:34:12Z',\n",
       "  'Views': '3360',\n",
       "  'Likes': '167',\n",
       "  'Favorite': '0',\n",
       "  'Comments': '36'},\n",
       " {'Title': '4 Simple Things That COMPLETELY Changed My Life #OneMinuteMonday',\n",
       "  'Published_date': '2021-03-15T12:54:20Z',\n",
       "  'Views': '3022',\n",
       "  'Likes': '196',\n",
       "  'Favorite': '0',\n",
       "  'Comments': '45'},\n",
       " {'Title': '3 Steps BEFORE Quitting Your Job',\n",
       "  'Published_date': '2021-03-08T14:58:40Z',\n",
       "  'Views': '2726',\n",
       "  'Likes': '151',\n",
       "  'Favorite': '0',\n",
       "  'Comments': '23'},\n",
       " {'Title': '3 One-Minute Habits that changed my life',\n",
       "  'Published_date': '2021-03-01T15:36:39Z',\n",
       "  'Views': '5070',\n",
       "  'Likes': '305',\n",
       "  'Favorite': '0',\n",
       "  'Comments': '39'},\n",
       " {'Title': 'Quitting my job to travel the world and chase my dreams',\n",
       "  'Published_date': '2021-02-15T17:27:39Z',\n",
       "  'Views': '3871',\n",
       "  'Likes': '243',\n",
       "  'Favorite': '0',\n",
       "  'Comments': '50'},\n",
       " {'Title': 'The \"Time Billionaire\" Concept',\n",
       "  'Published_date': '2021-01-19T20:36:38Z',\n",
       "  'Views': '5339',\n",
       "  'Likes': '599',\n",
       "  'Favorite': '0',\n",
       "  'Comments': '84'},\n",
       " {'Title': '*Watches Captain Sinbad Once*',\n",
       "  'Published_date': '2021-01-02T14:14:20Z',\n",
       "  'Views': '56237',\n",
       "  'Likes': '5072',\n",
       "  'Favorite': '0',\n",
       "  'Comments': '535'},\n",
       " {'Title': \"I tried Joe Rogans Sober October (HARD MODE) ..Here's What Happened\",\n",
       "  'Published_date': '2020-11-23T19:01:55Z',\n",
       "  'Views': '2969',\n",
       "  'Likes': '93',\n",
       "  'Favorite': '0',\n",
       "  'Comments': '21'},\n",
       " {'Title': 'Be Grateful | Amsterdam Cinematic Video | A6000',\n",
       "  'Published_date': '2020-11-04T20:11:24Z',\n",
       "  'Views': '40046',\n",
       "  'Likes': '1453',\n",
       "  'Favorite': '0',\n",
       "  'Comments': '212'},\n",
       " {'Title': \"This Website Predicts Our Future... (we're f*cked)\",\n",
       "  'Published_date': '2020-10-05T20:01:20Z',\n",
       "  'Views': '2030',\n",
       "  'Likes': '71',\n",
       "  'Favorite': '0',\n",
       "  'Comments': '12'},\n",
       " {'Title': 'The Social Dilemma: Humanity Is Screwed Unless We Do This..',\n",
       "  'Published_date': '2020-09-21T19:15:14Z',\n",
       "  'Views': '1315',\n",
       "  'Likes': '117',\n",
       "  'Favorite': '0',\n",
       "  'Comments': '17'},\n",
       " {'Title': \"I Used Elon Musk's Master Plan To Improve My Life\",\n",
       "  'Published_date': '2020-08-17T11:50:20Z',\n",
       "  'Views': '6248',\n",
       "  'Likes': '435',\n",
       "  'Favorite': '0',\n",
       "  'Comments': '86'},\n",
       " {'Title': 'How to Create Purpose in Life | Greece Travel Video | Sony A6000 Cinematic Travel Video',\n",
       "  'Published_date': '2020-07-24T16:48:50Z',\n",
       "  'Views': '4474',\n",
       "  'Likes': '269',\n",
       "  'Favorite': '0',\n",
       "  'Comments': '31'},\n",
       " {'Title': 'This book is turning me into an immortal millionaire',\n",
       "  'Published_date': '2020-06-09T16:50:56Z',\n",
       "  'Views': '3748',\n",
       "  'Likes': '224',\n",
       "  'Favorite': '0',\n",
       "  'Comments': '35'},\n",
       " {'Title': '3 Ways the Coronavirus Will Change Your Future (+ how you can prepare)',\n",
       "  'Published_date': '2020-04-30T13:02:10Z',\n",
       "  'Views': '1660',\n",
       "  'Likes': '62',\n",
       "  'Favorite': '0',\n",
       "  'Comments': '16'},\n",
       " {'Title': 'How Google Assistant, Siri & Alexa are slowly taking over your life',\n",
       "  'Published_date': '2020-03-30T19:21:12Z',\n",
       "  'Views': '3218',\n",
       "  'Likes': '161',\n",
       "  'Favorite': '0',\n",
       "  'Comments': '35'},\n",
       " {'Title': 'Escape | A short cinematic travel film shot in Yucatan, Mexico',\n",
       "  'Published_date': '2020-02-16T21:00:16Z',\n",
       "  'Views': '13643',\n",
       "  'Likes': '465',\n",
       "  'Favorite': '0',\n",
       "  'Comments': '53'}]"
      ]
     },
     "execution_count": 45,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "get_video_details(youtube,video_ids)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "id": "74d81a29-83a9-41f8-b49c-b245d81ae467",
   "metadata": {},
   "outputs": [],
   "source": [
    "video_details = get_video_details(youtube,video_ids)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 87,
   "id": "b837701b-4c40-442d-a6d2-68ab8c249968",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>channelName</th>\n",
       "      <th>subscribers</th>\n",
       "      <th>views</th>\n",
       "      <th>totalVideos</th>\n",
       "      <th>playlistId</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Stefanovic</td>\n",
       "      <td>262000</td>\n",
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       "      <td>81</td>\n",
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       "      <td>256000</td>\n",
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       "      <td>Mo Chen</td>\n",
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      ],
      "text/plain": [
       "         channelName  subscribers     views  totalVideos  \\\n",
       "0         Stefanovic       262000   9368189           81   \n",
       "1      Corey Schafer      1250000  91999206          232   \n",
       "2       Lore So What        19700    907497           91   \n",
       "3  Data Science Dojo       102000   5775001          461   \n",
       "4            Ken Jee       256000   8790825          286   \n",
       "5         Tina Huang       601000  27929660          179   \n",
       "6            Mo Chen        79600   2506295           84   \n",
       "7      Luke Barousse       402000  19507777          151   \n",
       "8   Alex The Analyst       672000  28733161          278   \n",
       "\n",
       "                 playlistId  \n",
       "0  UU0GmdVKZhMM3Rmielp4oVAA  \n",
       "1  UUCezIgC97PvUuR4_gbFUs5g  \n",
       "2  UUtoNXlIegvxkvf5Ji8S57Ag  \n",
       "3  UUzL_0nIe8B4-7ShhVPfJkgw  \n",
       "4  UUiT9RITQ9PW6BhXK0y2jaeg  \n",
       "5  UU2UXDak6o7rBm23k3Vv5dww  \n",
       "6  UUDybamfye5An6p-j1t2YMsg  \n",
       "7  UULLw7jmFsvfIVaUFsLs8mlQ  \n",
       "8  UU7cs8q-gJRlGwj4A8OmCmXg  "
      ]
     },
     "execution_count": 87,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "channel_data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "id": "206a8cc4-8b9a-45e0-8174-9cd45a8136c2",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\sloru\\AppData\\Local\\Temp\\ipykernel_9204\\1180904848.py:2: UserWarning: \n",
      "The palette list has fewer values (9) than needed (10) and will cycle, which may produce an uninterpretable plot.\n",
      "  ax1 = sns.barplot(x='Views', y='Title', data=top10_videos, hue= 'Views', palette=custom_colors, legend=False)\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 700x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "custom_colors = ['skyblue', 'lightcoral', 'lightgreen', 'yellow','red', 'pink', 'blue','green','orange']\n",
    "ax1 = sns.barplot(x='Views', y='Title', data=top10_videos, hue= 'Views', palette=custom_colors, legend=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "734b417e-d5e8-4f59-90c0-1698e2f7c31a",
   "metadata": {},
   "outputs": [],
   "source": [
    "#Here, we can see that Corey schafer's one video has way more views than the other nine videos."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "id": "d8c77531-e5eb-4a5c-b8a2-3a3a479e4355",
   "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>Title</th>\n",
       "      <th>Published_date</th>\n",
       "      <th>Views</th>\n",
       "      <th>Likes</th>\n",
       "      <th>Favorite</th>\n",
       "      <th>Comments</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>How to Use ChatGPT as a Powerful Tool for Prog...</td>\n",
       "      <td>2023-05-21</td>\n",
       "      <td>270729</td>\n",
       "      <td>7564</td>\n",
       "      <td>0</td>\n",
       "      <td>436</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Python Tutorial: Simulate the Powerball Lotter...</td>\n",
       "      <td>2023-01-09</td>\n",
       "      <td>136408</td>\n",
       "      <td>4257</td>\n",
       "      <td>0</td>\n",
       "      <td>772</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Python YouTube API Tutorial: Using OAuth to Ac...</td>\n",
       "      <td>2020-09-10</td>\n",
       "      <td>138854</td>\n",
       "      <td>2661</td>\n",
       "      <td>0</td>\n",
       "      <td>351</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Python YouTube API Tutorial: Sort a Playlist b...</td>\n",
       "      <td>2020-07-31</td>\n",
       "      <td>45716</td>\n",
       "      <td>1099</td>\n",
       "      <td>0</td>\n",
       "      <td>129</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Python YouTube API Tutorial: Calculating the D...</td>\n",
       "      <td>2020-06-10</td>\n",
       "      <td>55877</td>\n",
       "      <td>1598</td>\n",
       "      <td>0</td>\n",
       "      <td>177</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>228</th>\n",
       "      <td>Lab Puppy playing fetch in a lake</td>\n",
       "      <td>2014-04-25</td>\n",
       "      <td>13528</td>\n",
       "      <td>443</td>\n",
       "      <td>0</td>\n",
       "      <td>19</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>229</th>\n",
       "      <td>Lab Puppy playing fetch in a creek</td>\n",
       "      <td>2014-04-25</td>\n",
       "      <td>12859</td>\n",
       "      <td>285</td>\n",
       "      <td>0</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>230</th>\n",
       "      <td>If I'm running even 1 minute late for my dog's...</td>\n",
       "      <td>2014-04-25</td>\n",
       "      <td>75317</td>\n",
       "      <td>1647</td>\n",
       "      <td>0</td>\n",
       "      <td>72</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>231</th>\n",
       "      <td>Lab Puppy Diving in Snow</td>\n",
       "      <td>2014-03-22</td>\n",
       "      <td>27846</td>\n",
       "      <td>534</td>\n",
       "      <td>0</td>\n",
       "      <td>17</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>232</th>\n",
       "      <td>Lab puppy playing in bath tub</td>\n",
       "      <td>2014-01-20</td>\n",
       "      <td>26893</td>\n",
       "      <td>767</td>\n",
       "      <td>0</td>\n",
       "      <td>39</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>233 rows × 6 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                                                 Title Published_date   Views  \\\n",
       "0    How to Use ChatGPT as a Powerful Tool for Prog...     2023-05-21  270729   \n",
       "1    Python Tutorial: Simulate the Powerball Lotter...     2023-01-09  136408   \n",
       "2    Python YouTube API Tutorial: Using OAuth to Ac...     2020-09-10  138854   \n",
       "3    Python YouTube API Tutorial: Sort a Playlist b...     2020-07-31   45716   \n",
       "4    Python YouTube API Tutorial: Calculating the D...     2020-06-10   55877   \n",
       "..                                                 ...            ...     ...   \n",
       "228                  Lab Puppy playing fetch in a lake     2014-04-25   13528   \n",
       "229                 Lab Puppy playing fetch in a creek     2014-04-25   12859   \n",
       "230  If I'm running even 1 minute late for my dog's...     2014-04-25   75317   \n",
       "231                           Lab Puppy Diving in Snow     2014-03-22   27846   \n",
       "232                      Lab puppy playing in bath tub     2014-01-20   26893   \n",
       "\n",
       "     Likes  Favorite  Comments  \n",
       "0     7564         0       436  \n",
       "1     4257         0       772  \n",
       "2     2661         0       351  \n",
       "3     1099         0       129  \n",
       "4     1598         0       177  \n",
       "..     ...       ...       ...  \n",
       "228    443         0        19  \n",
       "229    285         0         6  \n",
       "230   1647         0        72  \n",
       "231    534         0        17  \n",
       "232    767         0        39  \n",
       "\n",
       "[233 rows x 6 columns]"
      ]
     },
     "execution_count": 63,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "video_data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "id": "13eafdf8-1e12-43a7-badc-ddca76ed6c4c",
   "metadata": {},
   "outputs": [],
   "source": [
    "video_data['Month'] = pd.to_datetime(video_data['Published_date']).dt.strftime('%b') #added Month colum"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "id": "0ca6cff2-8faf-47c5-bcd4-150cef9bd532",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
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       "\n",
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Title</th>\n",
       "      <th>Published_date</th>\n",
       "      <th>Views</th>\n",
       "      <th>Likes</th>\n",
       "      <th>Favorite</th>\n",
       "      <th>Comments</th>\n",
       "      <th>Month</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>How to Use ChatGPT as a Powerful Tool for Prog...</td>\n",
       "      <td>2023-05-21</td>\n",
       "      <td>270729</td>\n",
       "      <td>7564</td>\n",
       "      <td>0</td>\n",
       "      <td>436</td>\n",
       "      <td>May</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Python Tutorial: Simulate the Powerball Lotter...</td>\n",
       "      <td>2023-01-09</td>\n",
       "      <td>136408</td>\n",
       "      <td>4257</td>\n",
       "      <td>0</td>\n",
       "      <td>772</td>\n",
       "      <td>Jan</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Python YouTube API Tutorial: Using OAuth to Ac...</td>\n",
       "      <td>2020-09-10</td>\n",
       "      <td>138854</td>\n",
       "      <td>2661</td>\n",
       "      <td>0</td>\n",
       "      <td>351</td>\n",
       "      <td>Sep</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Python YouTube API Tutorial: Sort a Playlist b...</td>\n",
       "      <td>2020-07-31</td>\n",
       "      <td>45716</td>\n",
       "      <td>1099</td>\n",
       "      <td>0</td>\n",
       "      <td>129</td>\n",
       "      <td>Jul</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Python YouTube API Tutorial: Calculating the D...</td>\n",
       "      <td>2020-06-10</td>\n",
       "      <td>55877</td>\n",
       "      <td>1598</td>\n",
       "      <td>0</td>\n",
       "      <td>177</td>\n",
       "      <td>Jun</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>228</th>\n",
       "      <td>Lab Puppy playing fetch in a lake</td>\n",
       "      <td>2014-04-25</td>\n",
       "      <td>13528</td>\n",
       "      <td>443</td>\n",
       "      <td>0</td>\n",
       "      <td>19</td>\n",
       "      <td>Apr</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>229</th>\n",
       "      <td>Lab Puppy playing fetch in a creek</td>\n",
       "      <td>2014-04-25</td>\n",
       "      <td>12859</td>\n",
       "      <td>285</td>\n",
       "      <td>0</td>\n",
       "      <td>6</td>\n",
       "      <td>Apr</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>230</th>\n",
       "      <td>If I'm running even 1 minute late for my dog's...</td>\n",
       "      <td>2014-04-25</td>\n",
       "      <td>75317</td>\n",
       "      <td>1647</td>\n",
       "      <td>0</td>\n",
       "      <td>72</td>\n",
       "      <td>Apr</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>231</th>\n",
       "      <td>Lab Puppy Diving in Snow</td>\n",
       "      <td>2014-03-22</td>\n",
       "      <td>27846</td>\n",
       "      <td>534</td>\n",
       "      <td>0</td>\n",
       "      <td>17</td>\n",
       "      <td>Mar</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>232</th>\n",
       "      <td>Lab puppy playing in bath tub</td>\n",
       "      <td>2014-01-20</td>\n",
       "      <td>26893</td>\n",
       "      <td>767</td>\n",
       "      <td>0</td>\n",
       "      <td>39</td>\n",
       "      <td>Jan</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>233 rows × 7 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                                                 Title Published_date   Views  \\\n",
       "0    How to Use ChatGPT as a Powerful Tool for Prog...     2023-05-21  270729   \n",
       "1    Python Tutorial: Simulate the Powerball Lotter...     2023-01-09  136408   \n",
       "2    Python YouTube API Tutorial: Using OAuth to Ac...     2020-09-10  138854   \n",
       "3    Python YouTube API Tutorial: Sort a Playlist b...     2020-07-31   45716   \n",
       "4    Python YouTube API Tutorial: Calculating the D...     2020-06-10   55877   \n",
       "..                                                 ...            ...     ...   \n",
       "228                  Lab Puppy playing fetch in a lake     2014-04-25   13528   \n",
       "229                 Lab Puppy playing fetch in a creek     2014-04-25   12859   \n",
       "230  If I'm running even 1 minute late for my dog's...     2014-04-25   75317   \n",
       "231                           Lab Puppy Diving in Snow     2014-03-22   27846   \n",
       "232                      Lab puppy playing in bath tub     2014-01-20   26893   \n",
       "\n",
       "     Likes  Favorite  Comments Month  \n",
       "0     7564         0       436   May  \n",
       "1     4257         0       772   Jan  \n",
       "2     2661         0       351   Sep  \n",
       "3     1099         0       129   Jul  \n",
       "4     1598         0       177   Jun  \n",
       "..     ...       ...       ...   ...  \n",
       "228    443         0        19   Apr  \n",
       "229    285         0         6   Apr  \n",
       "230   1647         0        72   Apr  \n",
       "231    534         0        17   Mar  \n",
       "232    767         0        39   Jan  \n",
       "\n",
       "[233 rows x 7 columns]"
      ]
     },
     "execution_count": 65,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "video_data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 72,
   "id": "16c566b0-7e96-4d14-8941-8a011c039645",
   "metadata": {},
   "outputs": [],
   "source": [
    "videos_per_month = video_data.groupby('Month', as_index= False). size()"
   ]
  },
  {
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   "execution_count": 73,
   "id": "6c794ca3-53d2-4a2a-bd24-6a5d42c9efc0",
   "metadata": {},
   "outputs": [
    {
     "data": {
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      "text/plain": [
       "   Month  size\n",
       "0    Apr    25\n",
       "1    Aug    32\n",
       "2    Dec    10\n",
       "3    Feb    19\n",
       "4    Jan    13\n",
       "5    Jul    20\n",
       "6    Jun    20\n",
       "7    Mar    22\n",
       "8    May    29\n",
       "9    Nov    13\n",
       "10   Oct    21\n",
       "11   Sep     9"
      ]
     },
     "execution_count": 73,
     "metadata": {},
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   "source": [
    "videos_per_month"
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  {
   "cell_type": "code",
   "execution_count": 74,
   "id": "d437f4f0-36b3-4e07-ad96-2a18b883cb9f",
   "metadata": {},
   "outputs": [],
   "source": [
    "sort_order = ['Jan', 'Feb', 'Mar', 'Apr', 'May', 'Jun', 'July', 'Aug', 'Sep', 'Oct', 'Nov', 'Dec']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 75,
   "id": "98569def-2254-4613-8b3c-f64a1a47cb74",
   "metadata": {},
   "outputs": [],
   "source": [
    "videos_per_month.index = pd.CategoricalIndex(videos_per_month['Month'], categories=sort_order, ordered=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 76,
   "id": "546db8bc-f75d-40b3-84ee-c0b0b5eea001",
   "metadata": {},
   "outputs": [
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      "text/plain": [
       "      Month  size\n",
       "Month            \n",
       "Jan     Jan    13\n",
       "Feb     Feb    19\n",
       "Mar     Mar    22\n",
       "Apr     Apr    25\n",
       "May     May    29\n",
       "Jun     Jun    20\n",
       "Aug     Aug    32\n",
       "Sep     Sep     9\n",
       "Oct     Oct    21\n",
       "Nov     Nov    13\n",
       "Dec     Dec    10\n",
       "NaN     Jul    20"
      ]
     },
     "execution_count": 76,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "videos_per_month.sort_index()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 80,
   "id": "3311ae1e-6d72-40b1-8f8f-8a973129466f",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\sloru\\AppData\\Local\\Temp\\ipykernel_9204\\166238430.py:1: UserWarning: \n",
      "The palette list has fewer values (9) than needed (12) and will cycle, which may produce an uninterpretable plot.\n",
      "  ax2= sns.barplot(x= 'Month', y= 'size', data= videos_per_month, hue= 'Month',palette=custom_colors, legend=False)\n"
     ]
    },
    {
     "data": {
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",
      "text/plain": [
       "<Figure size 700x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "ax2= sns.barplot(x= 'Month', y= 'size', data= videos_per_month, hue= 'Month',palette=custom_colors, legend=False)\n",
    "custom_colors = ['skyblue', 'lightcoral', 'lightgreen', 'yellow','red', 'pink', 'blue','green','orange']\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 81,
   "id": "66f0df15-fd0b-46cb-af5c-25d5314ed76e",
   "metadata": {},
   "outputs": [],
   "source": [
    "#The most number of videos uploaded by Corey schafer's is on the month of August and \n",
    "#the least is on the month of September."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 84,
   "id": "aaaaac6a-e16c-4c69-9972-a3ab7d30754e",
   "metadata": {},
   "outputs": [],
   "source": [
    "video_data.to_csv('video_details (Corey schafer).csv')"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "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": "3.11.5"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}