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Created December 26, 2022 17:31
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Final Version - Regression Project - Ian Liu.ipynb
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-final-version-regression-project-ian-liu.ipynb
{
"cells": [
{
"cell_type": "markdown",
"metadata": {
"id": "view-in-github",
"colab_type": "text"
},
"source": [
"<a href=\"https://colab.research.google.com/gist/Ianyliu/ce297757f786f8896651add548a04655/-final-version-regression-project-ian-liu.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
]
},
{
"cell_type": "code",
"source": [
"!pip install missingpy pandas-profiling -U"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "qIT-KiN7AJ-1",
"outputId": "ac454174-8ade-480f-d7f0-3647c394776d",
"collapsed": true
},
"execution_count": null,
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
"Looking in indexes: https://pypi.org/simple, https://us-python.pkg.dev/colab-wheels/public/simple/\n",
"Collecting missingpy\n",
" Downloading missingpy-0.2.0-py3-none-any.whl (49 kB)\n",
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"\u001b[?25hRequirement already satisfied: pandas-profiling in /usr/local/lib/python3.8/dist-packages (1.4.1)\n",
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" Downloading statsmodels-0.13.5-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (9.9 MB)\n",
"\u001b[K |████████████████████████████████| 9.9 MB 59.0 MB/s \n",
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"\u001b[?25hCollecting phik<0.13,>=0.11.1\n",
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"Collecting tangled-up-in-unicode>=0.0.4\n",
" Downloading tangled_up_in_unicode-0.2.0-py3-none-any.whl (4.7 MB)\n",
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"Building wheels for collected packages: htmlmin\n",
" Building wheel for htmlmin (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
" Created wheel for htmlmin: filename=htmlmin-0.1.12-py3-none-any.whl size=27098 sha256=ae877fdb1ebd68559c11d82f8058b5146b4cf20abd05a5fd902b350647dcfbf4\n",
" Stored in directory: /root/.cache/pip/wheels/23/14/6e/4be5bfeeb027f4939a01764b48edd5996acf574b0913fe5243\n",
"Successfully built htmlmin\n",
"Installing collected packages: tangled-up-in-unicode, multimethod, visions, imagehash, typeguard, statsmodels, requests, phik, htmlmin, pandas-profiling, missingpy\n",
" Attempting uninstall: typeguard\n",
" Found existing installation: typeguard 2.7.1\n",
" Uninstalling typeguard-2.7.1:\n",
" Successfully uninstalled typeguard-2.7.1\n",
" Attempting uninstall: statsmodels\n",
" Found existing installation: statsmodels 0.12.2\n",
" Uninstalling statsmodels-0.12.2:\n",
" Successfully uninstalled statsmodels-0.12.2\n",
" Attempting uninstall: requests\n",
" Found existing installation: requests 2.23.0\n",
" Uninstalling requests-2.23.0:\n",
" Successfully uninstalled requests-2.23.0\n",
" Attempting uninstall: pandas-profiling\n",
" Found existing installation: pandas-profiling 1.4.1\n",
" Uninstalling pandas-profiling-1.4.1:\n",
" Successfully uninstalled pandas-profiling-1.4.1\n",
"Successfully installed htmlmin-0.1.12 imagehash-4.3.1 missingpy-0.2.0 multimethod-1.9 pandas-profiling-3.5.0 phik-0.12.3 requests-2.28.1 statsmodels-0.13.5 tangled-up-in-unicode-0.2.0 typeguard-2.13.3 visions-0.7.5\n"
]
}
]
},
{
"cell_type": "code",
"source": [
"import sys\n",
"import sklearn.neighbors._base\n",
"sys.modules['sklearn.neighbors.base'] = sklearn.neighbors._base\n",
"from missingpy import MissForest\n",
"from pandas_profiling import ProfileReport"
],
"metadata": {
"id": "1bhSAc9UAe5O"
},
"execution_count": null,
"outputs": []
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"id": "HQIPQRrPqqiA"
},
"outputs": [],
"source": [
"#imports\n",
"import os \n",
"import pandas as pd\n",
"import numpy as np\n",
"import random\n",
"import math\n",
"import seaborn as sns\n",
"from sklearn.model_selection import train_test_split\n",
"from sklearn.linear_model import LinearRegression\n",
"from sklearn.preprocessing import LabelEncoder, OneHotEncoder\n",
"from datetime import datetime\n",
"import statsmodels.api as sm\n",
"from statsmodels.stats.outliers_influence import variance_inflation_factor\n",
"import matplotlib.pyplot as plt\n",
"from scipy import stats \n",
"from statsmodels.stats.anova import AnovaRM\n",
"from statsmodels.formula.api import ols\n",
"from sklearn.preprocessing import StandardScaler\n",
"import missingno as msno\n",
"from statsmodels.stats.diagnostic import het_breuschpagan\n",
"import statsmodels.tsa.api as smt\n",
"from sklearn.dummy import DummyRegressor"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"id": "DpEXxaGzqqiQ"
},
"outputs": [],
"source": [
"pd.set_option('display.max_columns', None)"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"id": "652tgm0srSFL"
},
"outputs": [],
"source": [
"from google.colab import drive\n",
"drive.mount('/content/drive')"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"id": "EhdBe53FqqiS",
"colab": {
"base_uri": "https://localhost:8080/"
},
"outputId": "2c52cf0a-8d30-4627-b244-8809eeb2a5ab",
"collapsed": true
},
"outputs": [
{
"output_type": "stream",
"name": "stderr",
"text": [
"/usr/local/lib/python3.8/dist-packages/IPython/core/interactiveshell.py:3326: DtypeWarning: Columns (35) have mixed types.Specify dtype option on import or set low_memory=False.\n",
" exec(code_obj, self.user_global_ns, self.user_ns)\n"
]
}
],
"source": [
"original_df = pd.read_csv(r\"allChannelData.csv\")\n",
"df = original_df"
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "4mpTG-neqqiU"
},
"source": [
"# Data Cleaning"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"id": "yUiqms1-qqiW",
"outputId": "4e1c12ae-4d2d-4d79-eb78-e8000840854e",
"scrolled": true,
"collapsed": true,
"colab": {
"base_uri": "https://localhost:8080/"
}
},
"outputs": [
{
"output_type": "execute_result",
"data": {
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" cpm dataStartDate dataEndDate Video Publish Times length \\\n",
"248220 0.0 2022-10-01 2022-11-01 05/11/2020 609 \n",
"3494 0.0 2020-11-01 2020-12-01 11/14/2022 778.0 \n",
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"204587 0.0 2022-03-01 2022-04-01 08/01/2020 1726 \n",
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" estimatedHoursWatched CumulativeSubscribers Channel titleLength \\\n",
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]
},
"metadata": {},
"execution_count": 47
}
],
"source": [
"df.sample(n=5)"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"id": "MveP9s4qqqiY",
"outputId": "2755e4ad-f46c-4ae9-9e29-58ab083b358a",
"colab": {
"base_uri": "https://localhost:8080/"
}
},
"outputs": [
{
"output_type": "execute_result",
"data": {
"text/plain": [
"Index(['views', 'redViews', 'comments', 'likes', 'dislikes', 'shares',\n",
" 'videosAddedToPlaylists', 'videosRemovedFromPlaylists',\n",
" 'estimatedMinutesWatched', 'estimatedRedMinutesWatched',\n",
" 'averageViewDuration', 'averageViewPercentage',\n",
" 'annotationClickThroughRate', 'annotationCloseRate',\n",
" 'annotationImpressions', 'annotationClickableImpressions',\n",
" 'annotationClosableImpressions', 'annotationClicks', 'annotationCloses',\n",
" 'cardClickRate', 'cardTeaserClickRate', 'cardImpressions',\n",
" 'cardTeaserImpressions', 'cardClicks', 'cardTeaserClicks',\n",
" 'subscribersGained', 'subscribersLost', 'grossRevenue',\n",
" 'monetizedPlaybacks', 'playbackBasedCpm', 'adImpressions', 'cpm',\n",
" 'dataStartDate', 'dataEndDate', 'Video Publish Times', 'length',\n",
" 'estimatedHoursWatched', 'CumulativeSubscribers', 'Channel',\n",
" 'titleLength', 'descriptionLength', 'numOfKeywords',\n",
" 'PlaylistCategory'],\n",
" dtype='object')"
]
},
"metadata": {},
"execution_count": 7
}
],
"source": [
"df.columns"
]
},
{
"cell_type": "markdown",
"source": [
"## Summary Stats"
],
"metadata": {
"id": "kNs71qO_sduU"
}
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "nAe6zqKcqqia",
"outputId": "7c45938a-ad13-4ec0-a30a-251039c44967"
},
"outputs": [
{
"output_type": "execute_result",
"data": {
"text/plain": [
" count unique top freq \\\n",
"views 288835.0 NaN NaN NaN \n",
"redViews 288835.0 NaN NaN NaN \n",
"comments 288835.0 NaN NaN NaN \n",
"likes 288835.0 NaN NaN NaN \n",
"dislikes 288835.0 NaN NaN NaN \n",
"shares 288835.0 NaN NaN NaN \n",
"videosAddedToPlaylists 288835.0 NaN NaN NaN \n",
"videosRemovedFromPlaylists 288835.0 NaN NaN NaN \n",
"estimatedMinutesWatched 288835.0 NaN NaN NaN \n",
"estimatedRedMinutesWatched 288835.0 NaN NaN NaN \n",
"averageViewDuration 288835 1945 0:00:00 195315 \n",
"averageViewPercentage 288835.0 NaN NaN NaN \n",
"annotationClickThroughRate 288835.0 NaN NaN NaN \n",
"annotationCloseRate 288835.0 NaN NaN NaN \n",
"annotationImpressions 288835.0 NaN NaN NaN \n",
"annotationClickableImpressions 288835.0 NaN NaN NaN \n",
"annotationClosableImpressions 288835.0 NaN NaN NaN \n",
"annotationClicks 288835.0 NaN NaN NaN \n",
"annotationCloses 288835.0 NaN NaN NaN \n",
"cardClickRate 288835.0 NaN NaN NaN \n",
"cardTeaserClickRate 288835.0 NaN NaN NaN \n",
"cardImpressions 288835.0 NaN NaN NaN \n",
"cardTeaserImpressions 288835.0 NaN NaN NaN \n",
"cardClicks 288835.0 NaN NaN NaN \n",
"cardTeaserClicks 288835.0 NaN NaN NaN \n",
"subscribersGained 288835.0 NaN NaN NaN \n",
"subscribersLost 288835.0 NaN NaN NaN \n",
"grossRevenue 288835.0 NaN NaN NaN \n",
"monetizedPlaybacks 288835.0 NaN NaN NaN \n",
"playbackBasedCpm 288835.0 NaN NaN NaN \n",
"adImpressions 288835.0 NaN NaN NaN \n",
"cpm 288835.0 NaN NaN NaN \n",
"dataStartDate 288835 24 2021-12-01 12756 \n",
"dataEndDate 288835 26 2022-01-01 12756 \n",
"Video Publish Times 288835 1108 NaT 4311 \n",
"length 286720 8268 NaT 2196 \n",
"estimatedHoursWatched 288835.0 NaN NaN NaN \n",
"CumulativeSubscribers 288835.0 NaN NaN NaN \n",
"Channel 288835.0 NaN NaN NaN \n",
"titleLength 288835.0 NaN NaN NaN \n",
"descriptionLength 288835.0 NaN NaN NaN \n",
"numOfKeywords 288835.0 NaN NaN NaN \n",
"PlaylistCategory 288835.0 NaN NaN NaN \n",
"\n",
" mean std min 25% \\\n",
"views 1295.633071 8387.893711 0.0 0.0 \n",
"redViews 52.950345 346.582899 0.0 0.0 \n",
"comments 2.822051 43.2113 0.0 0.0 \n",
"likes 73.507729 456.774941 -81.0 0.0 \n",
"dislikes 0.849911 6.877958 -193.0 0.0 \n",
"shares 7.833317 61.818454 0.0 0.0 \n",
"videosAddedToPlaylists 9.205134 54.298329 0.0 0.0 \n",
"videosRemovedFromPlaylists 5.377316 28.422843 0.0 0.0 \n",
"estimatedMinutesWatched 10033.754929 70158.314132 0.0 0.0 \n",
"estimatedRedMinutesWatched 512.656537 3741.776855 0.0 0.0 \n",
"averageViewDuration NaN NaN NaN NaN \n",
"averageViewPercentage 9.423256 18.891189 0.0 0.0 \n",
"annotationClickThroughRate 0.0 0.0 0.0 0.0 \n",
"annotationCloseRate 0.0 0.0 0.0 0.0 \n",
"annotationImpressions 0.0 0.0 0.0 0.0 \n",
"annotationClickableImpressions 0.0 0.0 0.0 0.0 \n",
"annotationClosableImpressions 0.0 0.0 0.0 0.0 \n",
"annotationClicks 0.0 0.0 0.0 0.0 \n",
"annotationCloses 0.0 0.0 0.0 0.0 \n",
"cardClickRate 0.001717 0.026466 0.0 0.0 \n",
"cardTeaserClickRate 0.000088 0.00434 0.0 0.0 \n",
"cardImpressions 0.900462 26.148661 0.0 0.0 \n",
"cardTeaserImpressions 217.188686 2641.392207 0.0 0.0 \n",
"cardClicks 0.039594 0.90739 0.0 0.0 \n",
"cardTeaserClicks 0.279627 6.637093 0.0 0.0 \n",
"subscribersGained 1.401935 25.584436 0.0 0.0 \n",
"subscribersLost 0.228158 1.635675 0.0 0.0 \n",
"grossRevenue 9.038058 60.009922 0.0 0.0 \n",
"monetizedPlaybacks 1184.191552 7722.524884 0.0 0.0 \n",
"playbackBasedCpm 1.966516 33.925066 0.0 0.0 \n",
"adImpressions 1948.302467 12803.261375 0.0 0.0 \n",
"cpm 1.219942 17.185537 0.0 0.0 \n",
"dataStartDate NaN NaN NaN NaN \n",
"dataEndDate NaN NaN NaN NaN \n",
"Video Publish Times NaN NaN NaN NaN \n",
"length NaN NaN NaN NaN \n",
"estimatedHoursWatched 167.229249 1169.305236 0.0 0.0 \n",
"CumulativeSubscribers 1.173777 24.789249 -105.0 0.0 \n",
"Channel 1.831128 0.800777 1.0 1.0 \n",
"titleLength 54.031489 25.526314 0.0 33.0 \n",
"descriptionLength 317.136119 228.142358 0.0 162.0 \n",
"numOfKeywords 16.98747 25.684976 0.0 1.0 \n",
"PlaylistCategory 26.383143 13.456194 0.0 19.0 \n",
"\n",
" 50% 75% max \n",
"views 0.0 2.0 730749.0 \n",
"redViews 0.0 0.0 32461.0 \n",
"comments 0.0 0.0 6018.0 \n",
"likes 0.0 0.0 18001.0 \n",
"dislikes 0.0 0.0 1638.0 \n",
"shares 0.0 0.0 6108.0 \n",
"videosAddedToPlaylists 0.0 0.0 4984.0 \n",
"videosRemovedFromPlaylists 0.0 0.0 4314.0 \n",
"estimatedMinutesWatched 0.0 2.0 3676005.0 \n",
"estimatedRedMinutesWatched 0.0 0.0 218681.0 \n",
"averageViewDuration NaN NaN NaN \n",
"averageViewPercentage 0.0 6.52 518.13 \n",
"annotationClickThroughRate 0.0 0.0 0.0 \n",
"annotationCloseRate 0.0 0.0 0.0 \n",
"annotationImpressions 0.0 0.0 0.0 \n",
"annotationClickableImpressions 0.0 0.0 0.0 \n",
"annotationClosableImpressions 0.0 0.0 0.0 \n",
"annotationClicks 0.0 0.0 0.0 \n",
"annotationCloses 0.0 0.0 0.0 \n",
"cardClickRate 0.0 0.0 1.5 \n",
"cardTeaserClickRate 0.0 0.0 1.0 \n",
"cardImpressions 0.0 0.0 3429.0 \n",
"cardTeaserImpressions 0.0 0.0 227010.0 \n",
"cardClicks 0.0 0.0 150.0 \n",
"cardTeaserClicks 0.0 0.0 735.0 \n",
"subscribersGained 0.0 0.0 8181.0 \n",
"subscribersLost 0.0 0.0 159.0 \n",
"grossRevenue 0.0 0.0 2193.96 \n",
"monetizedPlaybacks 0.0 0.0 293115.0 \n",
"playbackBasedCpm 0.0 0.0 17755.667 \n",
"adImpressions 0.0 0.0 445864.0 \n",
"cpm 0.0 0.0 8877.833 \n",
"dataStartDate NaN NaN NaN \n",
"dataEndDate NaN NaN NaN \n",
"Video Publish Times NaN NaN NaN \n",
"length NaN NaN NaN \n",
"estimatedHoursWatched 0.0 0.033333 61266.75 \n",
"CumulativeSubscribers 0.0 0.0 8072.0 \n",
"Channel 2.0 2.0 4.0 \n",
"titleLength 53.0 74.0 100.0 \n",
"descriptionLength 262.0 409.0 2157.0 \n",
"numOfKeywords 1.0 35.0 111.0 \n",
"PlaylistCategory 29.0 37.0 45.0 "
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" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>6108.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>videosAddedToPlaylists</th>\n",
" <td>288835.0</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>9.205134</td>\n",
" <td>54.298329</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>4984.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>videosRemovedFromPlaylists</th>\n",
" <td>288835.0</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>5.377316</td>\n",
" <td>28.422843</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>4314.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>estimatedMinutesWatched</th>\n",
" <td>288835.0</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>10033.754929</td>\n",
" <td>70158.314132</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>2.0</td>\n",
" <td>3676005.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>estimatedRedMinutesWatched</th>\n",
" <td>288835.0</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>512.656537</td>\n",
" <td>3741.776855</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>218681.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>averageViewDuration</th>\n",
" <td>288835</td>\n",
" <td>1945</td>\n",
" <td>0:00:00</td>\n",
" <td>195315</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>averageViewPercentage</th>\n",
" <td>288835.0</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>9.423256</td>\n",
" <td>18.891189</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>6.52</td>\n",
" <td>518.13</td>\n",
" </tr>\n",
" <tr>\n",
" <th>annotationClickThroughRate</th>\n",
" <td>288835.0</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>annotationCloseRate</th>\n",
" <td>288835.0</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>annotationImpressions</th>\n",
" <td>288835.0</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>annotationClickableImpressions</th>\n",
" <td>288835.0</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>annotationClosableImpressions</th>\n",
" <td>288835.0</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>annotationClicks</th>\n",
" <td>288835.0</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>annotationCloses</th>\n",
" <td>288835.0</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>cardClickRate</th>\n",
" <td>288835.0</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>0.001717</td>\n",
" <td>0.026466</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>1.5</td>\n",
" </tr>\n",
" <tr>\n",
" <th>cardTeaserClickRate</th>\n",
" <td>288835.0</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>0.000088</td>\n",
" <td>0.00434</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>1.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>cardImpressions</th>\n",
" <td>288835.0</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>0.900462</td>\n",
" <td>26.148661</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>3429.0</td>\n",
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" <tr>\n",
" <th>cardTeaserImpressions</th>\n",
" <td>288835.0</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>217.188686</td>\n",
" <td>2641.392207</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>227010.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>cardClicks</th>\n",
" <td>288835.0</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>0.039594</td>\n",
" <td>0.90739</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>150.0</td>\n",
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" <tr>\n",
" <th>cardTeaserClicks</th>\n",
" <td>288835.0</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>0.279627</td>\n",
" <td>6.637093</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>735.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>subscribersGained</th>\n",
" <td>288835.0</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>1.401935</td>\n",
" <td>25.584436</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>8181.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>subscribersLost</th>\n",
" <td>288835.0</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>0.228158</td>\n",
" <td>1.635675</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>159.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>grossRevenue</th>\n",
" <td>288835.0</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>9.038058</td>\n",
" <td>60.009922</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>2193.96</td>\n",
" </tr>\n",
" <tr>\n",
" <th>monetizedPlaybacks</th>\n",
" <td>288835.0</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>1184.191552</td>\n",
" <td>7722.524884</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>293115.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>playbackBasedCpm</th>\n",
" <td>288835.0</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>1.966516</td>\n",
" <td>33.925066</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>17755.667</td>\n",
" </tr>\n",
" <tr>\n",
" <th>adImpressions</th>\n",
" <td>288835.0</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>1948.302467</td>\n",
" <td>12803.261375</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>445864.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>cpm</th>\n",
" <td>288835.0</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>1.219942</td>\n",
" <td>17.185537</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>8877.833</td>\n",
" </tr>\n",
" <tr>\n",
" <th>dataStartDate</th>\n",
" <td>288835</td>\n",
" <td>24</td>\n",
" <td>2021-12-01</td>\n",
" <td>12756</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>dataEndDate</th>\n",
" <td>288835</td>\n",
" <td>26</td>\n",
" <td>2022-01-01</td>\n",
" <td>12756</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Video Publish Times</th>\n",
" <td>288835</td>\n",
" <td>1108</td>\n",
" <td>NaT</td>\n",
" <td>4311</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>length</th>\n",
" <td>286720</td>\n",
" <td>8268</td>\n",
" <td>NaT</td>\n",
" <td>2196</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>estimatedHoursWatched</th>\n",
" <td>288835.0</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>167.229249</td>\n",
" <td>1169.305236</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.033333</td>\n",
" <td>61266.75</td>\n",
" </tr>\n",
" <tr>\n",
" <th>CumulativeSubscribers</th>\n",
" <td>288835.0</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>1.173777</td>\n",
" <td>24.789249</td>\n",
" <td>-105.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>8072.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Channel</th>\n",
" <td>288835.0</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>1.831128</td>\n",
" <td>0.800777</td>\n",
" <td>1.0</td>\n",
" <td>1.0</td>\n",
" <td>2.0</td>\n",
" <td>2.0</td>\n",
" <td>4.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>titleLength</th>\n",
" <td>288835.0</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>54.031489</td>\n",
" <td>25.526314</td>\n",
" <td>0.0</td>\n",
" <td>33.0</td>\n",
" <td>53.0</td>\n",
" <td>74.0</td>\n",
" <td>100.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>descriptionLength</th>\n",
" <td>288835.0</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>317.136119</td>\n",
" <td>228.142358</td>\n",
" <td>0.0</td>\n",
" <td>162.0</td>\n",
" <td>262.0</td>\n",
" <td>409.0</td>\n",
" <td>2157.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>numOfKeywords</th>\n",
" <td>288835.0</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>16.98747</td>\n",
" <td>25.684976</td>\n",
" <td>0.0</td>\n",
" <td>1.0</td>\n",
" <td>1.0</td>\n",
" <td>35.0</td>\n",
" <td>111.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>PlaylistCategory</th>\n",
" <td>288835.0</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>26.383143</td>\n",
" <td>13.456194</td>\n",
" <td>0.0</td>\n",
" <td>19.0</td>\n",
" <td>29.0</td>\n",
" <td>37.0</td>\n",
" <td>45.0</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
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" docLink.innerHTML = docLinkHtml;\n",
" element.appendChild(docLink);\n",
" }\n",
" </script>\n",
" </div>\n",
" </div>\n",
" "
]
},
"metadata": {},
"execution_count": 48
}
],
"source": [
"summary_df = df.describe(include='all')\n",
"summary_df = summary_df.T\n",
"summary_df "
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"id": "0BHy0GQAqqic",
"outputId": "6a6290e6-4ff6-4197-d67c-d5aeaa364731",
"colab": {
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" count unique top freq mean std min 25% \\\n",
"annotationClickThroughRate 288835.0 NaN NaN NaN 0.0 0.0 0.0 0.0 \n",
"annotationCloseRate 288835.0 NaN NaN NaN 0.0 0.0 0.0 0.0 \n",
"annotationImpressions 288835.0 NaN NaN NaN 0.0 0.0 0.0 0.0 \n",
"annotationClickableImpressions 288835.0 NaN NaN NaN 0.0 0.0 0.0 0.0 \n",
"annotationClosableImpressions 288835.0 NaN NaN NaN 0.0 0.0 0.0 0.0 \n",
"annotationClicks 288835.0 NaN NaN NaN 0.0 0.0 0.0 0.0 \n",
"annotationCloses 288835.0 NaN NaN NaN 0.0 0.0 0.0 0.0 \n",
"\n",
" 50% 75% max \n",
"annotationClickThroughRate 0.0 0.0 0.0 \n",
"annotationCloseRate 0.0 0.0 0.0 \n",
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"annotationClickableImpressions 0.0 0.0 0.0 \n",
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},
"metadata": {},
"execution_count": 49
}
],
"source": [
"summary_df[(summary_df['min'] == 0) & (summary_df['max'] == 0) & (summary_df['mean'] == 0)]"
]
},
{
"cell_type": "markdown",
"source": [
"## Convert Video Publish Time to Days Since Data Retreival"
],
"metadata": {
"id": "wS_7WZIC2YhR"
}
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"id": "gBqqRGmAqqid"
},
"outputs": [],
"source": [
"def convert_yyyymmdd_to_datetime(date):\n",
" if date is None:\n",
" return None\n",
" if isinstance(date, str):\n",
" if '-' in date:\n",
" return datetime.strptime(date, \"%Y-%m-%d\")\n",
" elif '/'in date:\n",
" return datetime.strptime(date, \"%m/%d/%Y\")\n",
" else:\n",
" return None\n",
" "
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"id": "pKFzQ8M2qqii",
"outputId": "189cee08-0079-437c-d53f-3ff003c5e12b",
"colab": {
"base_uri": "https://localhost:8080/"
}
},
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
"151270\n"
]
}
],
"source": [
"\n",
"remove = 0 \n",
"removed = []\n",
"for index, val in enumerate(df['Video Publish Times']):\n",
" vid_pub_time = convert_yyyymmdd_to_datetime(val)\n",
" data_end_date = convert_yyyymmdd_to_datetime(df['dataEndDate'][index])\n",
" if vid_pub_time is None or data_end_date is None:\n",
" continue\n",
" if data_end_date < vid_pub_time:\n",
" remove += 1\n",
" removed.append(index)\n",
"print(remove)"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"id": "92ReEsB3qqij",
"outputId": "e3083a15-d8b2-484c-e9d5-9a45dcc65eef",
"colab": {
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}
},
"outputs": [
{
"output_type": "execute_result",
"data": {
"text/plain": [
"137565"
]
},
"metadata": {},
"execution_count": 94
}
],
"source": [
"len(df) - remove"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"id": "0J9bL-Nbqqik"
},
"outputs": [],
"source": [
"df = df[~df.index.isin(removed)]"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"id": "grMZs4wqqqil"
},
"outputs": [],
"source": [
"df = df[df['Video Publish Times'] != 'NaT']"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"id": "H75HZ06Sqqim",
"outputId": "ed320e79-15df-45c1-c1c3-c5d2eb87fa82",
"scrolled": true,
"colab": {
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}
},
"outputs": [
{
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" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0:00:00</td>\n",
" <td>0.00</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0.000</td>\n",
" <td>0</td>\n",
" <td>0.000</td>\n",
" <td>0</td>\n",
" <td>0.000</td>\n",
" <td>2021-12-01</td>\n",
" <td>2022-01-01</td>\n",
" <td>01/08/2021</td>\n",
" <td>599</td>\n",
" <td>0.000000</td>\n",
" <td>0</td>\n",
" <td>1</td>\n",
" <td>69</td>\n",
" <td>180</td>\n",
" <td>1</td>\n",
" <td>45</td>\n",
" </tr>\n",
" <tr>\n",
" <th>19757</th>\n",
" <td>30</td>\n",
" <td>3</td>\n",
" <td>0</td>\n",
" <td>-5</td>\n",
" <td>1</td>\n",
" <td>0</td>\n",
" <td>2</td>\n",
" <td>4</td>\n",
" <td>119</td>\n",
" <td>11</td>\n",
" <td>0:03:59</td>\n",
" <td>41.51</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0.066</td>\n",
" <td>13</td>\n",
" <td>5.077</td>\n",
" <td>17</td>\n",
" <td>3.882</td>\n",
" <td>2022-03-01</td>\n",
" <td>2022-04-01</td>\n",
" <td>02/20/2022</td>\n",
" <td>576</td>\n",
" <td>1.983333</td>\n",
" <td>0</td>\n",
" <td>1</td>\n",
" <td>21</td>\n",
" <td>1249</td>\n",
" <td>38</td>\n",
" <td>13</td>\n",
" </tr>\n",
" <tr>\n",
" <th>78272</th>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>1</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0:00:00</td>\n",
" <td>0.00</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0.000</td>\n",
" <td>0</td>\n",
" <td>0.000</td>\n",
" <td>0</td>\n",
" <td>0.000</td>\n",
" <td>2021-12-01</td>\n",
" <td>2022-01-01</td>\n",
" <td>09/14/2021</td>\n",
" <td>762</td>\n",
" <td>0.000000</td>\n",
" <td>0</td>\n",
" <td>2</td>\n",
" <td>73</td>\n",
" <td>105</td>\n",
" <td>1</td>\n",
" <td>29</td>\n",
" </tr>\n",
" <tr>\n",
" <th>82041</th>\n",
" <td>1</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>-1</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>1</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0:00:10</td>\n",
" <td>0.97</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0.000</td>\n",
" <td>0</td>\n",
" <td>0.000</td>\n",
" <td>0</td>\n",
" <td>0.000</td>\n",
" <td>2022-01-01</td>\n",
" <td>2022-02-01</td>\n",
" <td>07/09/2021</td>\n",
" <td>1077</td>\n",
" <td>0.000000</td>\n",
" <td>0</td>\n",
" <td>2</td>\n",
" <td>53</td>\n",
" <td>404</td>\n",
" <td>1</td>\n",
" <td>29</td>\n",
" </tr>\n",
" <tr>\n",
" <th>114783</th>\n",
" <td>2</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>-3</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>11</td>\n",
" <td>0</td>\n",
" <td>0:05:50</td>\n",
" <td>48.88</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0.001</td>\n",
" <td>1</td>\n",
" <td>1.000</td>\n",
" <td>2</td>\n",
" <td>0.500</td>\n",
" <td>2022-09-01</td>\n",
" <td>2022-10-01</td>\n",
" <td>07/21/2021</td>\n",
" <td>717</td>\n",
" <td>0.183333</td>\n",
" <td>0</td>\n",
" <td>2</td>\n",
" <td>63</td>\n",
" <td>460</td>\n",
" <td>30</td>\n",
" <td>19</td>\n",
" </tr>\n",
" <tr>\n",
" <th>129783</th>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0:00:00</td>\n",
" <td>0.00</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0.000</td>\n",
" <td>0</td>\n",
" <td>0.000</td>\n",
" <td>0</td>\n",
" <td>0.000</td>\n",
" <td>2022-10-01</td>\n",
" <td>2022-10-31</td>\n",
" <td>01/25/2022</td>\n",
" <td>454</td>\n",
" <td>0.000000</td>\n",
" <td>0</td>\n",
" <td>3</td>\n",
" <td>61</td>\n",
" <td>665</td>\n",
" <td>59</td>\n",
" <td>25</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>\n",
" <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-6941e03d-d892-465b-8570-1afbaf3fd94a')\"\n",
" title=\"Convert this dataframe to an interactive table.\"\n",
" style=\"display:none;\">\n",
" \n",
" <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
" width=\"24px\">\n",
" <path d=\"M0 0h24v24H0V0z\" fill=\"none\"/>\n",
" <path d=\"M18.56 5.44l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94zm-11 1L8.5 8.5l.94-2.06 2.06-.94-2.06-.94L8.5 2.5l-.94 2.06-2.06.94zm10 10l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94z\"/><path d=\"M17.41 7.96l-1.37-1.37c-.4-.4-.92-.59-1.43-.59-.52 0-1.04.2-1.43.59L10.3 9.45l-7.72 7.72c-.78.78-.78 2.05 0 2.83L4 21.41c.39.39.9.59 1.41.59.51 0 1.02-.2 1.41-.59l7.78-7.78 2.81-2.81c.8-.78.8-2.07 0-2.86zM5.41 20L4 18.59l7.72-7.72 1.47 1.35L5.41 20z\"/>\n",
" </svg>\n",
" </button>\n",
" \n",
" <style>\n",
" .colab-df-container {\n",
" display:flex;\n",
" flex-wrap:wrap;\n",
" gap: 12px;\n",
" }\n",
"\n",
" .colab-df-convert {\n",
" background-color: #E8F0FE;\n",
" border: none;\n",
" border-radius: 50%;\n",
" cursor: pointer;\n",
" display: none;\n",
" fill: #1967D2;\n",
" height: 32px;\n",
" padding: 0 0 0 0;\n",
" width: 32px;\n",
" }\n",
"\n",
" .colab-df-convert:hover {\n",
" background-color: #E2EBFA;\n",
" box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
" fill: #174EA6;\n",
" }\n",
"\n",
" [theme=dark] .colab-df-convert {\n",
" background-color: #3B4455;\n",
" fill: #D2E3FC;\n",
" }\n",
"\n",
" [theme=dark] .colab-df-convert:hover {\n",
" background-color: #434B5C;\n",
" box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
" filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
" fill: #FFFFFF;\n",
" }\n",
" </style>\n",
"\n",
" <script>\n",
" const buttonEl =\n",
" document.querySelector('#df-6941e03d-d892-465b-8570-1afbaf3fd94a button.colab-df-convert');\n",
" buttonEl.style.display =\n",
" google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
"\n",
" async function convertToInteractive(key) {\n",
" const element = document.querySelector('#df-6941e03d-d892-465b-8570-1afbaf3fd94a');\n",
" const dataTable =\n",
" await google.colab.kernel.invokeFunction('convertToInteractive',\n",
" [key], {});\n",
" if (!dataTable) return;\n",
"\n",
" const docLinkHtml = 'Like what you see? Visit the ' +\n",
" '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
" + ' to learn more about interactive tables.';\n",
" element.innerHTML = '';\n",
" dataTable['output_type'] = 'display_data';\n",
" await google.colab.output.renderOutput(dataTable, element);\n",
" const docLink = document.createElement('div');\n",
" docLink.innerHTML = docLinkHtml;\n",
" element.appendChild(docLink);\n",
" }\n",
" </script>\n",
" </div>\n",
" </div>\n",
" "
]
},
"metadata": {},
"execution_count": 97
}
],
"source": [
"df.reset_index(drop=True, inplace=True)\n",
"df.sample(7)"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"id": "JaSIddBuqqim"
},
"outputs": [],
"source": [
"diff = []\n",
"for index, data_end_date in enumerate(df['dataEndDate']):\n",
" vid_pub_time = convert_yyyymmdd_to_datetime(df['Video Publish Times'][index])\n",
" data_end_date = convert_yyyymmdd_to_datetime(data_end_date)\n",
" data_start_date = convert_yyyymmdd_to_datetime(df['dataStartDate'][index])\n",
" \n",
" if vid_pub_time is None or data_start_date is None:\n",
" diff.append(None)\n",
" continue\n",
" if vid_pub_time.year > (data_start_date.year):\n",
" diff.append(0) \n",
" elif vid_pub_time.month >= (data_start_date.month) and vid_pub_time.year == (data_start_date.year):\n",
" diff.append(0)\n",
" else:\n",
" if (data_start_date - vid_pub_time).days <= 0:\n",
" print(data_start_date, vid_pub_time)\n",
" diff.append((data_start_date - vid_pub_time).days)\n"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"id": "1U0YuQgiqqio"
},
"outputs": [],
"source": [
"df['daysFromPublishDateToDataRetrieval'] = diff"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"id": "h-NJluLdqqio",
"outputId": "4cf44c13-9824-4fe6-a7ce-2b1a61623bc3",
"colab": {
"base_uri": "https://localhost:8080/"
}
},
"outputs": [
{
"output_type": "execute_result",
"data": {
"text/plain": [
"daysFromPublishDateToDataRetrieval\n",
"0 10028\n",
"1 289\n",
"2 313\n",
"3 304\n",
"4 297\n",
" ... \n",
"2231 1\n",
"2258 1\n",
"2262 1\n",
"2288 1\n",
"2292 1\n",
"Length: 1410, dtype: int64"
]
},
"metadata": {},
"execution_count": 100
}
],
"source": [
"df.value_counts(['daysFromPublishDateToDataRetrieval']).sort_index()"
]
},
{
"cell_type": "markdown",
"source": [
"## Drop All 0 Columns and Redundant Columns"
],
"metadata": {
"id": "lg4e8Rk3sj1R"
}
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"id": "HR9IurTpqqip"
},
"outputs": [],
"source": [
"# remove columns with all 0 values\n",
"df = df.drop('annotationClickThroughRate', axis=1, errors='ignore')\n",
"df = df.drop('annotationCloseRate', axis=1, errors='ignore')\n",
"df = df.drop('annotationClickableImpressions', axis=1, errors='ignore')\n",
"df = df.drop('annotationClosableImpressions', axis=1, errors='ignore')\n",
"df = df.drop('annotationImpressions', axis=1, errors='ignore')\n",
"df = df.drop('annotationClicks', axis=1, errors='ignore')\n",
"df = df.drop('annotationCloses', axis=1, errors='ignore')\n",
"\n",
"# Remove redundant columns\n",
"df = df.drop('estimatedHoursWatched', axis=1, errors='ignore')\n",
"df = df.drop('dataEndDate', axis=1, errors='ignore')\n",
"df = df.drop('dataStartDate', axis=1, errors='ignore')\n",
"df = df.drop('Video Publish Times', axis=1, errors='ignore')\n",
"df = df.drop('titleLength', axis=1, errors='ignore')\n",
"df = df.drop('descriptionLength', axis=1, errors='ignore')"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"id": "KQ3OW-3Hqqiq",
"outputId": "b4db0521-e022-43d3-a755-3e4f28aab3fb",
"colab": {
"base_uri": "https://localhost:8080/"
}
},
"outputs": [
{
"output_type": "execute_result",
"data": {
"text/plain": [
"Index(['views', 'redViews', 'comments', 'likes', 'dislikes', 'shares',\n",
" 'videosAddedToPlaylists', 'videosRemovedFromPlaylists',\n",
" 'estimatedMinutesWatched', 'estimatedRedMinutesWatched',\n",
" 'averageViewDuration', 'averageViewPercentage', 'cardClickRate',\n",
" 'cardTeaserClickRate', 'cardImpressions', 'cardTeaserImpressions',\n",
" 'cardClicks', 'cardTeaserClicks', 'subscribersGained',\n",
" 'subscribersLost', 'grossRevenue', 'monetizedPlaybacks',\n",
" 'playbackBasedCpm', 'adImpressions', 'cpm', 'length',\n",
" 'CumulativeSubscribers', 'Channel', 'numOfKeywords', 'PlaylistCategory',\n",
" 'daysFromPublishDateToDataRetrieval'],\n",
" dtype='object')"
]
},
"metadata": {},
"execution_count": 102
}
],
"source": [
"df.columns"
]
},
{
"cell_type": "markdown",
"source": [
"## Convert All Time to Seconds "
],
"metadata": {
"id": "9owCnflosofK"
}
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"id": "olN8ZmALqqir"
},
"outputs": [],
"source": [
"def get_sec(time_str: str):\n",
" \"\"\"Get seconds from time.\"\"\"\n",
" if time_str is None:\n",
" return None\n",
" if isinstance(time_str, int) or isinstance(time_str, float):\n",
" return time_str\n",
" if isinstance(time_str, str) and ':' not in time_str:\n",
" if time_str[:2] == 'PT':\n",
" time_str = time_str[2:]\n",
" duration = 0\n",
" if 'H' in time_str:\n",
" duration += 3600 * int(time_str.split('H')[0])\n",
" time_str = time_str.split('H')[1]\n",
" \n",
" if 'M' in time_str:\n",
" duration += 60 * int(time_str.split('M')[0])\n",
" time_str = time_str.split('M')[1]\n",
" \n",
" if 'S' in time_str:\n",
" duration += int(time_str.split('S')[0])\n",
" time_str = time_str.split('S')[1]\n",
" \n",
" return duration \n",
" else: \n",
" try:\n",
" return float(time_str)\n",
" except:\n",
" try:\n",
" return int(time_str)\n",
" except:\n",
" return None\n",
" elif isinstance(time_str, str) and ':' in time_str:\n",
" h, m, s = time_str.split(':')\n",
" return int(h) * 3600 + int(m) * 60 + int(s)\n",
" else:\n",
" return None"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"id": "kKPu62tVqqis"
},
"outputs": [],
"source": [
"df = df[df['length'].isna() == False]"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"id": "U5JnUWAGqqit"
},
"outputs": [],
"source": [
"df['length'] = df['length'].apply(get_sec)"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"id": "cqkM6iH9qqit"
},
"outputs": [],
"source": [
"df['averageViewDuration'] = df['averageViewDuration'].apply(get_sec)"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"id": "thqNAUv0qqiu",
"outputId": "76ca7a84-25a3-4391-ba6e-c93d8b1f869b",
"scrolled": true,
"colab": {
"base_uri": "https://localhost:8080/"
}
},
"outputs": [
{
"output_type": "execute_result",
"data": {
"text/plain": [
"length 84\n",
"dtype: int64"
]
},
"metadata": {},
"execution_count": 107
}
],
"source": [
"df.isna().sum()[df.isna().sum() != 0]"
]
},
{
"cell_type": "markdown",
"source": [
"## Check Missing Observations"
],
"metadata": {
"id": "Z3JblKCSZQrL"
}
},
{
"cell_type": "code",
"source": [
"msno.heatmap(df)"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "oQ7UlIiJZUB3",
"outputId": "36ab8294-ee03-44b4-9959-d23ea0c4dedc"
},
"execution_count": null,
"outputs": [
{
"output_type": "execute_result",
"data": {
"text/plain": [
"<matplotlib.axes._subplots.AxesSubplot at 0x7f4beef8eee0>"
]
},
"metadata": {},
"execution_count": 108
},
{
"output_type": "display_data",
"data": {
"text/plain": [
"<Figure size 1440x864 with 2 Axes>"
],
"image/png": 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\n"
},
"metadata": {
"needs_background": "light"
}
}
]
},
{
"cell_type": "code",
"source": [
"msno.matrix(df.sort_values(\"grossRevenue\"));"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "RjI-ei4BZU4S",
"outputId": "b1f1256b-f248-4574-a5af-cc88830edf79"
},
"execution_count": null,
"outputs": [
{
"output_type": "display_data",
"data": {
"text/plain": [
"<Figure size 1800x720 with 2 Axes>"
],
"image/png": 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},
"metadata": {
"needs_background": "light"
}
}
]
},
{
"cell_type": "markdown",
"source": [
"## Use imputation to replace negative predictor values for likes & dislikes"
],
"metadata": {
"id": "cXtvBOSg_h_Q"
}
},
{
"cell_type": "code",
"source": [
"summary_df = df.describe(include='all')\n",
"summary_df = summary_df.T\n",
"summary_df"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "kCHRSYCq_nrC",
"outputId": "76f64150-6f02-4b56-b63f-57a47f768e8d"
},
"execution_count": null,
"outputs": [
{
"output_type": "execute_result",
"data": {
"text/plain": [
" count mean std \\\n",
"views 133170.0 2159.193602 10499.123501 \n",
"redViews 133170.0 92.106263 451.276751 \n",
"comments 133170.0 4.116565 23.777574 \n",
"likes 133170.0 120.277878 544.201395 \n",
"dislikes 133170.0 1.405054 8.865805 \n",
"shares 133170.0 11.991590 62.700418 \n",
"videosAddedToPlaylists 133170.0 15.255966 64.298396 \n",
"videosRemovedFromPlaylists 133170.0 9.385350 34.372455 \n",
"estimatedMinutesWatched 133170.0 16650.691064 82663.759487 \n",
"estimatedRedMinutesWatched 133170.0 879.384659 4390.837129 \n",
"averageViewDuration 133170.0 191.394391 286.653344 \n",
"averageViewPercentage 133170.0 19.209420 23.207633 \n",
"cardClickRate 133170.0 0.002891 0.034418 \n",
"cardTeaserClickRate 133170.0 0.000179 0.006385 \n",
"cardImpressions 133170.0 1.345558 29.385509 \n",
"cardTeaserImpressions 133170.0 364.117932 3238.819497 \n",
"cardClicks 133170.0 0.056161 0.862664 \n",
"cardTeaserClicks 133170.0 0.419847 7.003825 \n",
"subscribersGained 133170.0 1.906706 15.927877 \n",
"subscribersLost 133170.0 0.391537 2.088110 \n",
"grossRevenue 133170.0 14.817125 72.241918 \n",
"monetizedPlaybacks 133170.0 1971.845739 9527.403908 \n",
"playbackBasedCpm 133170.0 4.072948 49.854216 \n",
"adImpressions 133170.0 3240.556394 15743.825556 \n",
"cpm 133170.0 2.524946 25.228942 \n",
"length 133170.0 1476.820117 2160.380796 \n",
"CumulativeSubscribers 133170.0 1.515169 14.706610 \n",
"Channel 133170.0 1.757077 0.625806 \n",
"numOfKeywords 133170.0 25.304363 27.916158 \n",
"PlaylistCategory 133170.0 30.985995 13.089769 \n",
"daysFromPublishDateToDataRetrieval 133170.0 283.954314 244.958514 \n",
"\n",
" min 25% 50% 75% \\\n",
"views 0.0 0.0 2.00 13.000 \n",
"redViews 0.0 0.0 0.00 0.000 \n",
"comments 0.0 0.0 0.00 0.000 \n",
"likes -81.0 -2.0 0.00 0.000 \n",
"dislikes -80.0 0.0 0.00 0.000 \n",
"shares 0.0 0.0 0.00 0.000 \n",
"videosAddedToPlaylists 0.0 0.0 0.00 0.000 \n",
"videosRemovedFromPlaylists 0.0 0.0 0.00 2.000 \n",
"estimatedMinutesWatched 0.0 0.0 3.00 56.000 \n",
"estimatedRedMinutesWatched 0.0 0.0 0.00 0.000 \n",
"averageViewDuration 0.0 0.0 72.00 305.000 \n",
"averageViewPercentage 0.0 0.0 7.99 34.960 \n",
"cardClickRate 0.0 0.0 0.00 0.000 \n",
"cardTeaserClickRate 0.0 0.0 0.00 0.000 \n",
"cardImpressions 0.0 0.0 0.00 0.000 \n",
"cardTeaserImpressions 0.0 0.0 0.00 0.000 \n",
"cardClicks 0.0 0.0 0.00 0.000 \n",
"cardTeaserClicks 0.0 0.0 0.00 0.000 \n",
"subscribersGained 0.0 0.0 0.00 0.000 \n",
"subscribersLost 0.0 0.0 0.00 0.000 \n",
"grossRevenue 0.0 0.0 0.00 0.057 \n",
"monetizedPlaybacks 0.0 0.0 0.00 8.000 \n",
"playbackBasedCpm 0.0 0.0 0.00 6.000 \n",
"adImpressions 0.0 0.0 0.00 12.000 \n",
"cpm 0.0 0.0 0.00 4.000 \n",
"length 9.0 635.0 808.00 1200.000 \n",
"CumulativeSubscribers -105.0 0.0 0.00 0.000 \n",
"Channel 1.0 1.0 2.00 2.000 \n",
"numOfKeywords 0.0 1.0 17.00 48.000 \n",
"PlaylistCategory 1.0 21.0 29.00 45.000 \n",
"daysFromPublishDateToDataRetrieval 0.0 83.0 232.00 429.000 \n",
"\n",
" max \n",
"views 730749.000 \n",
"redViews 32461.000 \n",
"comments 3041.000 \n",
"likes 18001.000 \n",
"dislikes 1638.000 \n",
"shares 2952.000 \n",
"videosAddedToPlaylists 1819.000 \n",
"videosRemovedFromPlaylists 1675.000 \n",
"estimatedMinutesWatched 2458178.000 \n",
"estimatedRedMinutesWatched 170741.000 \n",
"averageViewDuration 11544.000 \n",
"averageViewPercentage 518.130 \n",
"cardClickRate 1.500 \n",
"cardTeaserClickRate 1.000 \n",
"cardImpressions 3429.000 \n",
"cardTeaserImpressions 183411.000 \n",
"cardClicks 94.000 \n",
"cardTeaserClicks 735.000 \n",
"subscribersGained 1268.000 \n",
"subscribersLost 159.000 \n",
"grossRevenue 1864.061 \n",
"monetizedPlaybacks 293115.000 \n",
"playbackBasedCpm 17755.667 \n",
"adImpressions 427568.000 \n",
"cpm 8877.833 \n",
"length 33440.000 \n",
"CumulativeSubscribers 1208.000 \n",
"Channel 4.000 \n",
"numOfKeywords 111.000 \n",
"PlaylistCategory 45.000 \n",
"daysFromPublishDateToDataRetrieval 2292.000 "
],
"text/html": [
"\n",
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" <div class=\"colab-df-container\">\n",
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" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>count</th>\n",
" <th>mean</th>\n",
" <th>std</th>\n",
" <th>min</th>\n",
" <th>25%</th>\n",
" <th>50%</th>\n",
" <th>75%</th>\n",
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" <tbody>\n",
" <tr>\n",
" <th>views</th>\n",
" <td>133170.0</td>\n",
" <td>2159.193602</td>\n",
" <td>10499.123501</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
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" <td>730749.000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>redViews</th>\n",
" <td>133170.0</td>\n",
" <td>92.106263</td>\n",
" <td>451.276751</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.00</td>\n",
" <td>0.000</td>\n",
" <td>32461.000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>comments</th>\n",
" <td>133170.0</td>\n",
" <td>4.116565</td>\n",
" <td>23.777574</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.00</td>\n",
" <td>0.000</td>\n",
" <td>3041.000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>likes</th>\n",
" <td>133170.0</td>\n",
" <td>120.277878</td>\n",
" <td>544.201395</td>\n",
" <td>-81.0</td>\n",
" <td>-2.0</td>\n",
" <td>0.00</td>\n",
" <td>0.000</td>\n",
" <td>18001.000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>dislikes</th>\n",
" <td>133170.0</td>\n",
" <td>1.405054</td>\n",
" <td>8.865805</td>\n",
" <td>-80.0</td>\n",
" <td>0.0</td>\n",
" <td>0.00</td>\n",
" <td>0.000</td>\n",
" <td>1638.000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>shares</th>\n",
" <td>133170.0</td>\n",
" <td>11.991590</td>\n",
" <td>62.700418</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.00</td>\n",
" <td>0.000</td>\n",
" <td>2952.000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>videosAddedToPlaylists</th>\n",
" <td>133170.0</td>\n",
" <td>15.255966</td>\n",
" <td>64.298396</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.00</td>\n",
" <td>0.000</td>\n",
" <td>1819.000</td>\n",
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" <tr>\n",
" <th>videosRemovedFromPlaylists</th>\n",
" <td>133170.0</td>\n",
" <td>9.385350</td>\n",
" <td>34.372455</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.00</td>\n",
" <td>2.000</td>\n",
" <td>1675.000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>estimatedMinutesWatched</th>\n",
" <td>133170.0</td>\n",
" <td>16650.691064</td>\n",
" <td>82663.759487</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>3.00</td>\n",
" <td>56.000</td>\n",
" <td>2458178.000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>estimatedRedMinutesWatched</th>\n",
" <td>133170.0</td>\n",
" <td>879.384659</td>\n",
" <td>4390.837129</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.00</td>\n",
" <td>0.000</td>\n",
" <td>170741.000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>averageViewDuration</th>\n",
" <td>133170.0</td>\n",
" <td>191.394391</td>\n",
" <td>286.653344</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>72.00</td>\n",
" <td>305.000</td>\n",
" <td>11544.000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>averageViewPercentage</th>\n",
" <td>133170.0</td>\n",
" <td>19.209420</td>\n",
" <td>23.207633</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>7.99</td>\n",
" <td>34.960</td>\n",
" <td>518.130</td>\n",
" </tr>\n",
" <tr>\n",
" <th>cardClickRate</th>\n",
" <td>133170.0</td>\n",
" <td>0.002891</td>\n",
" <td>0.034418</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.00</td>\n",
" <td>0.000</td>\n",
" <td>1.500</td>\n",
" </tr>\n",
" <tr>\n",
" <th>cardTeaserClickRate</th>\n",
" <td>133170.0</td>\n",
" <td>0.000179</td>\n",
" <td>0.006385</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.00</td>\n",
" <td>0.000</td>\n",
" <td>1.000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>cardImpressions</th>\n",
" <td>133170.0</td>\n",
" <td>1.345558</td>\n",
" <td>29.385509</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.00</td>\n",
" <td>0.000</td>\n",
" <td>3429.000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>cardTeaserImpressions</th>\n",
" <td>133170.0</td>\n",
" <td>364.117932</td>\n",
" <td>3238.819497</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.00</td>\n",
" <td>0.000</td>\n",
" <td>183411.000</td>\n",
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" <th>cardClicks</th>\n",
" <td>133170.0</td>\n",
" <td>0.056161</td>\n",
" <td>0.862664</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.00</td>\n",
" <td>0.000</td>\n",
" <td>94.000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>cardTeaserClicks</th>\n",
" <td>133170.0</td>\n",
" <td>0.419847</td>\n",
" <td>7.003825</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.00</td>\n",
" <td>0.000</td>\n",
" <td>735.000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>subscribersGained</th>\n",
" <td>133170.0</td>\n",
" <td>1.906706</td>\n",
" <td>15.927877</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.00</td>\n",
" <td>0.000</td>\n",
" <td>1268.000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>subscribersLost</th>\n",
" <td>133170.0</td>\n",
" <td>0.391537</td>\n",
" <td>2.088110</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.00</td>\n",
" <td>0.000</td>\n",
" <td>159.000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>grossRevenue</th>\n",
" <td>133170.0</td>\n",
" <td>14.817125</td>\n",
" <td>72.241918</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.00</td>\n",
" <td>0.057</td>\n",
" <td>1864.061</td>\n",
" </tr>\n",
" <tr>\n",
" <th>monetizedPlaybacks</th>\n",
" <td>133170.0</td>\n",
" <td>1971.845739</td>\n",
" <td>9527.403908</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.00</td>\n",
" <td>8.000</td>\n",
" <td>293115.000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>playbackBasedCpm</th>\n",
" <td>133170.0</td>\n",
" <td>4.072948</td>\n",
" <td>49.854216</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.00</td>\n",
" <td>6.000</td>\n",
" <td>17755.667</td>\n",
" </tr>\n",
" <tr>\n",
" <th>adImpressions</th>\n",
" <td>133170.0</td>\n",
" <td>3240.556394</td>\n",
" <td>15743.825556</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.00</td>\n",
" <td>12.000</td>\n",
" <td>427568.000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>cpm</th>\n",
" <td>133170.0</td>\n",
" <td>2.524946</td>\n",
" <td>25.228942</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.00</td>\n",
" <td>4.000</td>\n",
" <td>8877.833</td>\n",
" </tr>\n",
" <tr>\n",
" <th>length</th>\n",
" <td>133170.0</td>\n",
" <td>1476.820117</td>\n",
" <td>2160.380796</td>\n",
" <td>9.0</td>\n",
" <td>635.0</td>\n",
" <td>808.00</td>\n",
" <td>1200.000</td>\n",
" <td>33440.000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>CumulativeSubscribers</th>\n",
" <td>133170.0</td>\n",
" <td>1.515169</td>\n",
" <td>14.706610</td>\n",
" <td>-105.0</td>\n",
" <td>0.0</td>\n",
" <td>0.00</td>\n",
" <td>0.000</td>\n",
" <td>1208.000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Channel</th>\n",
" <td>133170.0</td>\n",
" <td>1.757077</td>\n",
" <td>0.625806</td>\n",
" <td>1.0</td>\n",
" <td>1.0</td>\n",
" <td>2.00</td>\n",
" <td>2.000</td>\n",
" <td>4.000</td>\n",
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" <tr>\n",
" <th>numOfKeywords</th>\n",
" <td>133170.0</td>\n",
" <td>25.304363</td>\n",
" <td>27.916158</td>\n",
" <td>0.0</td>\n",
" <td>1.0</td>\n",
" <td>17.00</td>\n",
" <td>48.000</td>\n",
" <td>111.000</td>\n",
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" <tr>\n",
" <th>PlaylistCategory</th>\n",
" <td>133170.0</td>\n",
" <td>30.985995</td>\n",
" <td>13.089769</td>\n",
" <td>1.0</td>\n",
" <td>21.0</td>\n",
" <td>29.00</td>\n",
" <td>45.000</td>\n",
" <td>45.000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>daysFromPublishDateToDataRetrieval</th>\n",
" <td>133170.0</td>\n",
" <td>283.954314</td>\n",
" <td>244.958514</td>\n",
" <td>0.0</td>\n",
" <td>83.0</td>\n",
" <td>232.00</td>\n",
" <td>429.000</td>\n",
" <td>2292.000</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
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]
},
"metadata": {},
"execution_count": 112
}
]
},
{
"cell_type": "code",
"source": [
"test_df = df\n",
"test_df['dislikes'] = df['dislikes'].mask(df['dislikes'] < 0, np.nan)\n",
"test_df['likes'] = df['likes'].mask(df['likes'] < 0, np.nan)\n",
"df = test_df\n",
"\n",
"test_df.describe(include='all').T"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "0Bm-cCLg_9YV",
"outputId": "d0f27bcd-3944-4dbe-8b33-df89f7d6371c"
},
"execution_count": null,
"outputs": [
{
"output_type": "execute_result",
"data": {
"text/plain": [
" count mean std \\\n",
"views 133170.0 2159.193602 10499.123501 \n",
"redViews 133170.0 92.106263 451.276751 \n",
"comments 133170.0 4.116565 23.777574 \n",
"likes 74428.0 217.584740 713.038788 \n",
"dislikes 132999.0 1.414996 8.856528 \n",
"shares 133170.0 11.991590 62.700418 \n",
"videosAddedToPlaylists 133170.0 15.255966 64.298396 \n",
"videosRemovedFromPlaylists 133170.0 9.385350 34.372455 \n",
"estimatedMinutesWatched 133170.0 16650.691064 82663.759487 \n",
"estimatedRedMinutesWatched 133170.0 879.384659 4390.837129 \n",
"averageViewDuration 133170.0 191.394391 286.653344 \n",
"averageViewPercentage 133170.0 19.209420 23.207633 \n",
"cardClickRate 133170.0 0.002891 0.034418 \n",
"cardTeaserClickRate 133170.0 0.000179 0.006385 \n",
"cardImpressions 133170.0 1.345558 29.385509 \n",
"cardTeaserImpressions 133170.0 364.117932 3238.819497 \n",
"cardClicks 133170.0 0.056161 0.862664 \n",
"cardTeaserClicks 133170.0 0.419847 7.003825 \n",
"subscribersGained 133170.0 1.906706 15.927877 \n",
"subscribersLost 133170.0 0.391537 2.088110 \n",
"grossRevenue 133170.0 14.817125 72.241918 \n",
"monetizedPlaybacks 133170.0 1971.845739 9527.403908 \n",
"playbackBasedCpm 133170.0 4.072948 49.854216 \n",
"adImpressions 133170.0 3240.556394 15743.825556 \n",
"cpm 133170.0 2.524946 25.228942 \n",
"length 133170.0 1476.820117 2160.380796 \n",
"CumulativeSubscribers 133170.0 1.515169 14.706610 \n",
"Channel 133170.0 1.757077 0.625806 \n",
"numOfKeywords 133170.0 25.304363 27.916158 \n",
"PlaylistCategory 133170.0 30.985995 13.089769 \n",
"daysFromPublishDateToDataRetrieval 133170.0 283.954314 244.958514 \n",
"\n",
" min 25% 50% 75% \\\n",
"views 0.0 0.0 2.00 13.000 \n",
"redViews 0.0 0.0 0.00 0.000 \n",
"comments 0.0 0.0 0.00 0.000 \n",
"likes 0.0 0.0 0.00 0.000 \n",
"dislikes 0.0 0.0 0.00 0.000 \n",
"shares 0.0 0.0 0.00 0.000 \n",
"videosAddedToPlaylists 0.0 0.0 0.00 0.000 \n",
"videosRemovedFromPlaylists 0.0 0.0 0.00 2.000 \n",
"estimatedMinutesWatched 0.0 0.0 3.00 56.000 \n",
"estimatedRedMinutesWatched 0.0 0.0 0.00 0.000 \n",
"averageViewDuration 0.0 0.0 72.00 305.000 \n",
"averageViewPercentage 0.0 0.0 7.99 34.960 \n",
"cardClickRate 0.0 0.0 0.00 0.000 \n",
"cardTeaserClickRate 0.0 0.0 0.00 0.000 \n",
"cardImpressions 0.0 0.0 0.00 0.000 \n",
"cardTeaserImpressions 0.0 0.0 0.00 0.000 \n",
"cardClicks 0.0 0.0 0.00 0.000 \n",
"cardTeaserClicks 0.0 0.0 0.00 0.000 \n",
"subscribersGained 0.0 0.0 0.00 0.000 \n",
"subscribersLost 0.0 0.0 0.00 0.000 \n",
"grossRevenue 0.0 0.0 0.00 0.057 \n",
"monetizedPlaybacks 0.0 0.0 0.00 8.000 \n",
"playbackBasedCpm 0.0 0.0 0.00 6.000 \n",
"adImpressions 0.0 0.0 0.00 12.000 \n",
"cpm 0.0 0.0 0.00 4.000 \n",
"length 9.0 635.0 808.00 1200.000 \n",
"CumulativeSubscribers -105.0 0.0 0.00 0.000 \n",
"Channel 1.0 1.0 2.00 2.000 \n",
"numOfKeywords 0.0 1.0 17.00 48.000 \n",
"PlaylistCategory 1.0 21.0 29.00 45.000 \n",
"daysFromPublishDateToDataRetrieval 0.0 83.0 232.00 429.000 \n",
"\n",
" max \n",
"views 730749.000 \n",
"redViews 32461.000 \n",
"comments 3041.000 \n",
"likes 18001.000 \n",
"dislikes 1638.000 \n",
"shares 2952.000 \n",
"videosAddedToPlaylists 1819.000 \n",
"videosRemovedFromPlaylists 1675.000 \n",
"estimatedMinutesWatched 2458178.000 \n",
"estimatedRedMinutesWatched 170741.000 \n",
"averageViewDuration 11544.000 \n",
"averageViewPercentage 518.130 \n",
"cardClickRate 1.500 \n",
"cardTeaserClickRate 1.000 \n",
"cardImpressions 3429.000 \n",
"cardTeaserImpressions 183411.000 \n",
"cardClicks 94.000 \n",
"cardTeaserClicks 735.000 \n",
"subscribersGained 1268.000 \n",
"subscribersLost 159.000 \n",
"grossRevenue 1864.061 \n",
"monetizedPlaybacks 293115.000 \n",
"playbackBasedCpm 17755.667 \n",
"adImpressions 427568.000 \n",
"cpm 8877.833 \n",
"length 33440.000 \n",
"CumulativeSubscribers 1208.000 \n",
"Channel 4.000 \n",
"numOfKeywords 111.000 \n",
"PlaylistCategory 45.000 \n",
"daysFromPublishDateToDataRetrieval 2292.000 "
],
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"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>count</th>\n",
" <th>mean</th>\n",
" <th>std</th>\n",
" <th>min</th>\n",
" <th>25%</th>\n",
" <th>50%</th>\n",
" <th>75%</th>\n",
" <th>max</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>views</th>\n",
" <td>133170.0</td>\n",
" <td>2159.193602</td>\n",
" <td>10499.123501</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>2.00</td>\n",
" <td>13.000</td>\n",
" <td>730749.000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>redViews</th>\n",
" <td>133170.0</td>\n",
" <td>92.106263</td>\n",
" <td>451.276751</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.00</td>\n",
" <td>0.000</td>\n",
" <td>32461.000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>comments</th>\n",
" <td>133170.0</td>\n",
" <td>4.116565</td>\n",
" <td>23.777574</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.00</td>\n",
" <td>0.000</td>\n",
" <td>3041.000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>likes</th>\n",
" <td>74428.0</td>\n",
" <td>217.584740</td>\n",
" <td>713.038788</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.00</td>\n",
" <td>0.000</td>\n",
" <td>18001.000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>dislikes</th>\n",
" <td>132999.0</td>\n",
" <td>1.414996</td>\n",
" <td>8.856528</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.00</td>\n",
" <td>0.000</td>\n",
" <td>1638.000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>shares</th>\n",
" <td>133170.0</td>\n",
" <td>11.991590</td>\n",
" <td>62.700418</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.00</td>\n",
" <td>0.000</td>\n",
" <td>2952.000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>videosAddedToPlaylists</th>\n",
" <td>133170.0</td>\n",
" <td>15.255966</td>\n",
" <td>64.298396</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.00</td>\n",
" <td>0.000</td>\n",
" <td>1819.000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>videosRemovedFromPlaylists</th>\n",
" <td>133170.0</td>\n",
" <td>9.385350</td>\n",
" <td>34.372455</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.00</td>\n",
" <td>2.000</td>\n",
" <td>1675.000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>estimatedMinutesWatched</th>\n",
" <td>133170.0</td>\n",
" <td>16650.691064</td>\n",
" <td>82663.759487</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>3.00</td>\n",
" <td>56.000</td>\n",
" <td>2458178.000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>estimatedRedMinutesWatched</th>\n",
" <td>133170.0</td>\n",
" <td>879.384659</td>\n",
" <td>4390.837129</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.00</td>\n",
" <td>0.000</td>\n",
" <td>170741.000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>averageViewDuration</th>\n",
" <td>133170.0</td>\n",
" <td>191.394391</td>\n",
" <td>286.653344</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>72.00</td>\n",
" <td>305.000</td>\n",
" <td>11544.000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>averageViewPercentage</th>\n",
" <td>133170.0</td>\n",
" <td>19.209420</td>\n",
" <td>23.207633</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>7.99</td>\n",
" <td>34.960</td>\n",
" <td>518.130</td>\n",
" </tr>\n",
" <tr>\n",
" <th>cardClickRate</th>\n",
" <td>133170.0</td>\n",
" <td>0.002891</td>\n",
" <td>0.034418</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.00</td>\n",
" <td>0.000</td>\n",
" <td>1.500</td>\n",
" </tr>\n",
" <tr>\n",
" <th>cardTeaserClickRate</th>\n",
" <td>133170.0</td>\n",
" <td>0.000179</td>\n",
" <td>0.006385</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.00</td>\n",
" <td>0.000</td>\n",
" <td>1.000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>cardImpressions</th>\n",
" <td>133170.0</td>\n",
" <td>1.345558</td>\n",
" <td>29.385509</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.00</td>\n",
" <td>0.000</td>\n",
" <td>3429.000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>cardTeaserImpressions</th>\n",
" <td>133170.0</td>\n",
" <td>364.117932</td>\n",
" <td>3238.819497</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.00</td>\n",
" <td>0.000</td>\n",
" <td>183411.000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>cardClicks</th>\n",
" <td>133170.0</td>\n",
" <td>0.056161</td>\n",
" <td>0.862664</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.00</td>\n",
" <td>0.000</td>\n",
" <td>94.000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>cardTeaserClicks</th>\n",
" <td>133170.0</td>\n",
" <td>0.419847</td>\n",
" <td>7.003825</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.00</td>\n",
" <td>0.000</td>\n",
" <td>735.000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>subscribersGained</th>\n",
" <td>133170.0</td>\n",
" <td>1.906706</td>\n",
" <td>15.927877</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.00</td>\n",
" <td>0.000</td>\n",
" <td>1268.000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>subscribersLost</th>\n",
" <td>133170.0</td>\n",
" <td>0.391537</td>\n",
" <td>2.088110</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.00</td>\n",
" <td>0.000</td>\n",
" <td>159.000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>grossRevenue</th>\n",
" <td>133170.0</td>\n",
" <td>14.817125</td>\n",
" <td>72.241918</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.00</td>\n",
" <td>0.057</td>\n",
" <td>1864.061</td>\n",
" </tr>\n",
" <tr>\n",
" <th>monetizedPlaybacks</th>\n",
" <td>133170.0</td>\n",
" <td>1971.845739</td>\n",
" <td>9527.403908</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.00</td>\n",
" <td>8.000</td>\n",
" <td>293115.000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>playbackBasedCpm</th>\n",
" <td>133170.0</td>\n",
" <td>4.072948</td>\n",
" <td>49.854216</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.00</td>\n",
" <td>6.000</td>\n",
" <td>17755.667</td>\n",
" </tr>\n",
" <tr>\n",
" <th>adImpressions</th>\n",
" <td>133170.0</td>\n",
" <td>3240.556394</td>\n",
" <td>15743.825556</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.00</td>\n",
" <td>12.000</td>\n",
" <td>427568.000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>cpm</th>\n",
" <td>133170.0</td>\n",
" <td>2.524946</td>\n",
" <td>25.228942</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.00</td>\n",
" <td>4.000</td>\n",
" <td>8877.833</td>\n",
" </tr>\n",
" <tr>\n",
" <th>length</th>\n",
" <td>133170.0</td>\n",
" <td>1476.820117</td>\n",
" <td>2160.380796</td>\n",
" <td>9.0</td>\n",
" <td>635.0</td>\n",
" <td>808.00</td>\n",
" <td>1200.000</td>\n",
" <td>33440.000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>CumulativeSubscribers</th>\n",
" <td>133170.0</td>\n",
" <td>1.515169</td>\n",
" <td>14.706610</td>\n",
" <td>-105.0</td>\n",
" <td>0.0</td>\n",
" <td>0.00</td>\n",
" <td>0.000</td>\n",
" <td>1208.000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Channel</th>\n",
" <td>133170.0</td>\n",
" <td>1.757077</td>\n",
" <td>0.625806</td>\n",
" <td>1.0</td>\n",
" <td>1.0</td>\n",
" <td>2.00</td>\n",
" <td>2.000</td>\n",
" <td>4.000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>numOfKeywords</th>\n",
" <td>133170.0</td>\n",
" <td>25.304363</td>\n",
" <td>27.916158</td>\n",
" <td>0.0</td>\n",
" <td>1.0</td>\n",
" <td>17.00</td>\n",
" <td>48.000</td>\n",
" <td>111.000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>PlaylistCategory</th>\n",
" <td>133170.0</td>\n",
" <td>30.985995</td>\n",
" <td>13.089769</td>\n",
" <td>1.0</td>\n",
" <td>21.0</td>\n",
" <td>29.00</td>\n",
" <td>45.000</td>\n",
" <td>45.000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>daysFromPublishDateToDataRetrieval</th>\n",
" <td>133170.0</td>\n",
" <td>283.954314</td>\n",
" <td>244.958514</td>\n",
" <td>0.0</td>\n",
" <td>83.0</td>\n",
" <td>232.00</td>\n",
" <td>429.000</td>\n",
" <td>2292.000</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
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]
},
"metadata": {},
"execution_count": 113
}
]
},
{
"cell_type": "code",
"source": [
"df.isna().sum()"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "V3TbsGvMBk77",
"outputId": "5f17af45-b24e-46fe-de85-116bea147204"
},
"execution_count": null,
"outputs": [
{
"output_type": "execute_result",
"data": {
"text/plain": [
"views 0\n",
"redViews 0\n",
"comments 0\n",
"likes 58742\n",
"dislikes 171\n",
"shares 0\n",
"videosAddedToPlaylists 0\n",
"videosRemovedFromPlaylists 0\n",
"estimatedMinutesWatched 0\n",
"estimatedRedMinutesWatched 0\n",
"averageViewDuration 0\n",
"averageViewPercentage 0\n",
"cardClickRate 0\n",
"cardTeaserClickRate 0\n",
"cardImpressions 0\n",
"cardTeaserImpressions 0\n",
"cardClicks 0\n",
"cardTeaserClicks 0\n",
"subscribersGained 0\n",
"subscribersLost 0\n",
"grossRevenue 0\n",
"monetizedPlaybacks 0\n",
"playbackBasedCpm 0\n",
"adImpressions 0\n",
"cpm 0\n",
"length 0\n",
"CumulativeSubscribers 0\n",
"Channel 0\n",
"numOfKeywords 0\n",
"PlaylistCategory 0\n",
"daysFromPublishDateToDataRetrieval 0\n",
"dtype: int64"
]
},
"metadata": {},
"execution_count": 114
}
]
},
{
"cell_type": "markdown",
"source": [
"The missing values will be imputed with MissForest\n",
"I used this repository: https://github.com/epsilon-machine/missingpy\n",
"\n",
"And initially got the idea from here: https://towardsdatascience.com/missforest-the-best-missing-data-imputation-algorithm-4d01182aed3\n"
],
"metadata": {
"id": "2C584tc7Rv4k"
}
},
{
"cell_type": "code",
"source": [
"impute_df = test_df\n",
"imputer = MissForest()\n",
"imputed_results = imputer.fit_transform(impute_df)\n",
"print(imputed_results)"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "0Hz3Cf6bFHFt",
"outputId": "eaa8be5e-bff0-49b8-931b-2a2929e7f688"
},
"execution_count": null,
"outputs": [
{
"output_type": "stream",
"name": "stderr",
"text": [
"/usr/local/lib/python3.8/dist-packages/sklearn/ensemble/_forest.py:396: FutureWarning: Criterion 'mse' was deprecated in v1.0 and will be removed in version 1.2. Use `criterion='squared_error'` which is equivalent.\n",
" warn(\n",
"/usr/local/lib/python3.8/dist-packages/sklearn/ensemble/_forest.py:396: FutureWarning: Criterion 'mse' was deprecated in v1.0 and will be removed in version 1.2. Use `criterion='squared_error'` which is equivalent.\n",
" warn(\n"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
"Iteration: 0\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
"/usr/local/lib/python3.8/dist-packages/sklearn/ensemble/_forest.py:396: FutureWarning: Criterion 'mse' was deprecated in v1.0 and will be removed in version 1.2. Use `criterion='squared_error'` which is equivalent.\n",
" warn(\n",
"/usr/local/lib/python3.8/dist-packages/sklearn/ensemble/_forest.py:396: FutureWarning: Criterion 'mse' was deprecated in v1.0 and will be removed in version 1.2. Use `criterion='squared_error'` which is equivalent.\n",
" warn(\n"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
"Iteration: 1\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
"/usr/local/lib/python3.8/dist-packages/sklearn/ensemble/_forest.py:396: FutureWarning: Criterion 'mse' was deprecated in v1.0 and will be removed in version 1.2. Use `criterion='squared_error'` which is equivalent.\n",
" warn(\n",
"/usr/local/lib/python3.8/dist-packages/sklearn/ensemble/_forest.py:396: FutureWarning: Criterion 'mse' was deprecated in v1.0 and will be removed in version 1.2. Use `criterion='squared_error'` which is equivalent.\n",
" warn(\n"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
"Iteration: 2\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
"/usr/local/lib/python3.8/dist-packages/sklearn/ensemble/_forest.py:396: FutureWarning: Criterion 'mse' was deprecated in v1.0 and will be removed in version 1.2. Use `criterion='squared_error'` which is equivalent.\n",
" warn(\n",
"/usr/local/lib/python3.8/dist-packages/sklearn/ensemble/_forest.py:396: FutureWarning: Criterion 'mse' was deprecated in v1.0 and will be removed in version 1.2. Use `criterion='squared_error'` which is equivalent.\n",
" warn(\n"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
"Iteration: 3\n",
"[[1.18871e+05 6.55400e+03 3.04100e+03 ... 1.00000e+00 2.20000e+01\n",
" 0.00000e+00]\n",
" [3.27910e+04 1.79300e+03 8.00000e+01 ... 1.00000e+00 4.50000e+01\n",
" 0.00000e+00]\n",
" [3.06970e+04 1.21700e+03 5.00000e+01 ... 1.00000e+00 4.50000e+01\n",
" 0.00000e+00]\n",
" ...\n",
" [1.50000e+01 0.00000e+00 0.00000e+00 ... 9.60000e+01 3.00000e+00\n",
" 1.48000e+02]\n",
" [5.00000e+00 0.00000e+00 0.00000e+00 ... 9.60000e+01 3.00000e+00\n",
" 1.21000e+02]\n",
" [5.00000e+00 0.00000e+00 0.00000e+00 ... 8.60000e+01 3.00000e+00\n",
" 1.08000e+02]]\n"
]
}
]
},
{
"cell_type": "code",
"source": [
"imputed_results.shape"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "gcF41DCdQlep",
"outputId": "f14185b1-ee4b-417c-a57b-f6b45a519615"
},
"execution_count": null,
"outputs": [
{
"output_type": "execute_result",
"data": {
"text/plain": [
"(133170, 31)"
]
},
"metadata": {},
"execution_count": 116
}
]
},
{
"cell_type": "code",
"source": [
"test_df.columns"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "PaOew8-tPEX3",
"outputId": "ed8a5416-0cbf-486e-c313-fdd419311be1"
},
"execution_count": null,
"outputs": [
{
"output_type": "execute_result",
"data": {
"text/plain": [
"Index(['views', 'redViews', 'comments', 'likes', 'dislikes', 'shares',\n",
" 'videosAddedToPlaylists', 'videosRemovedFromPlaylists',\n",
" 'estimatedMinutesWatched', 'estimatedRedMinutesWatched',\n",
" 'averageViewDuration', 'averageViewPercentage', 'cardClickRate',\n",
" 'cardTeaserClickRate', 'cardImpressions', 'cardTeaserImpressions',\n",
" 'cardClicks', 'cardTeaserClicks', 'subscribersGained',\n",
" 'subscribersLost', 'grossRevenue', 'monetizedPlaybacks',\n",
" 'playbackBasedCpm', 'adImpressions', 'cpm', 'length',\n",
" 'CumulativeSubscribers', 'Channel', 'numOfKeywords', 'PlaylistCategory',\n",
" 'daysFromPublishDateToDataRetrieval'],\n",
" dtype='object')"
]
},
"metadata": {},
"execution_count": 117
}
]
},
{
"cell_type": "code",
"source": [
"impute_df = pd.DataFrame(imputed_results, columns = test_df.columns)"
],
"metadata": {
"id": "sqVVsDfyO-ng"
},
"execution_count": null,
"outputs": []
},
{
"cell_type": "code",
"source": [
"impute_df.to_csv(\"imputedData.csv\", index = False)"
],
"metadata": {
"id": "XG-yrCKaKmGu"
},
"execution_count": null,
"outputs": []
},
{
"cell_type": "code",
"source": [
"impute_df.isna().sum()"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "QEsOAdBS3G1d",
"outputId": "681fa165-57de-4684-bec0-52795d96c6b2"
},
"execution_count": null,
"outputs": [
{
"output_type": "execute_result",
"data": {
"text/plain": [
"views 0\n",
"redViews 0\n",
"comments 0\n",
"likes 0\n",
"dislikes 0\n",
"shares 0\n",
"videosAddedToPlaylists 0\n",
"videosRemovedFromPlaylists 0\n",
"estimatedMinutesWatched 0\n",
"estimatedRedMinutesWatched 0\n",
"averageViewDuration 0\n",
"averageViewPercentage 0\n",
"cardClickRate 0\n",
"cardTeaserClickRate 0\n",
"cardImpressions 0\n",
"cardTeaserImpressions 0\n",
"cardClicks 0\n",
"cardTeaserClicks 0\n",
"subscribersGained 0\n",
"subscribersLost 0\n",
"grossRevenue 0\n",
"monetizedPlaybacks 0\n",
"playbackBasedCpm 0\n",
"adImpressions 0\n",
"cpm 0\n",
"length 0\n",
"CumulativeSubscribers 0\n",
"Channel 0\n",
"numOfKeywords 0\n",
"PlaylistCategory 0\n",
"daysFromPublishDateToDataRetrieval 0\n",
"dtype: int64"
]
},
"metadata": {},
"execution_count": 120
}
]
},
{
"cell_type": "code",
"source": [
"df = impute_df"
],
"metadata": {
"id": "qnA3t0qD6VgD"
},
"execution_count": null,
"outputs": []
},
{
"cell_type": "markdown",
"source": [
"## Summary Stats Again"
],
"metadata": {
"id": "Lc0IJ2IIs0_6"
}
},
{
"cell_type": "code",
"source": [
"df.columns"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "6wM5y7OhsU3v",
"outputId": "78f567cf-1aa9-452a-d92e-a85dc561b8fa"
},
"execution_count": null,
"outputs": [
{
"output_type": "execute_result",
"data": {
"text/plain": [
"Index(['views', 'redViews', 'comments', 'likes', 'dislikes', 'shares',\n",
" 'videosAddedToPlaylists', 'videosRemovedFromPlaylists',\n",
" 'estimatedMinutesWatched', 'estimatedRedMinutesWatched',\n",
" 'averageViewDuration', 'averageViewPercentage', 'cardClickRate',\n",
" 'cardTeaserClickRate', 'cardImpressions', 'cardTeaserImpressions',\n",
" 'cardClicks', 'cardTeaserClicks', 'subscribersGained',\n",
" 'subscribersLost', 'grossRevenue', 'monetizedPlaybacks',\n",
" 'playbackBasedCpm', 'adImpressions', 'cpm', 'length',\n",
" 'CumulativeSubscribers', 'Channel', 'numOfKeywords', 'PlaylistCategory',\n",
" 'daysFromPublishDateToDataRetrieval'],\n",
" dtype='object')"
]
},
"metadata": {},
"execution_count": 124
}
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"id": "9Y7zyeUJqqi1",
"outputId": "89700fff-a2db-4dec-b4ec-262ccaf0e6a8",
"colab": {
"base_uri": "https://localhost:8080/"
}
},
"outputs": [
{
"output_type": "execute_result",
"data": {
"text/plain": [
" count mean std \\\n",
"views 133170.0 2159.193602 10499.123501 \n",
"redViews 133170.0 92.106263 451.276751 \n",
"comments 133170.0 4.116565 23.777574 \n",
"likes 133170.0 121.799494 543.898989 \n",
"dislikes 133170.0 1.420680 8.860767 \n",
"shares 133170.0 11.991590 62.700418 \n",
"videosAddedToPlaylists 133170.0 15.255966 64.298396 \n",
"videosRemovedFromPlaylists 133170.0 9.385350 34.372455 \n",
"estimatedMinutesWatched 133170.0 16650.691064 82663.759487 \n",
"estimatedRedMinutesWatched 133170.0 879.384659 4390.837129 \n",
"averageViewDuration 133170.0 191.394391 286.653344 \n",
"averageViewPercentage 133170.0 19.209420 23.207633 \n",
"cardClickRate 133170.0 0.002891 0.034418 \n",
"cardTeaserClickRate 133170.0 0.000179 0.006385 \n",
"cardImpressions 133170.0 1.345558 29.385509 \n",
"cardTeaserImpressions 133170.0 364.117932 3238.819497 \n",
"cardClicks 133170.0 0.056161 0.862664 \n",
"cardTeaserClicks 133170.0 0.419847 7.003825 \n",
"subscribersGained 133170.0 1.906706 15.927877 \n",
"subscribersLost 133170.0 0.391537 2.088110 \n",
"grossRevenue 133170.0 14.817125 72.241918 \n",
"monetizedPlaybacks 133170.0 1971.845739 9527.403908 \n",
"playbackBasedCpm 133170.0 4.072948 49.854216 \n",
"adImpressions 133170.0 3240.556394 15743.825556 \n",
"cpm 133170.0 2.524946 25.228942 \n",
"length 133170.0 1476.820117 2160.380796 \n",
"CumulativeSubscribers 133170.0 1.515169 14.706610 \n",
"Channel 133170.0 1.757077 0.625806 \n",
"numOfKeywords 133170.0 25.304363 27.916158 \n",
"PlaylistCategory 133170.0 30.985995 13.089769 \n",
"daysFromPublishDateToDataRetrieval 133170.0 283.954314 244.958514 \n",
"\n",
" min 25% 50% 75% \\\n",
"views 0.0 0.0 2.00 13.000 \n",
"redViews 0.0 0.0 0.00 0.000 \n",
"comments 0.0 0.0 0.00 0.000 \n",
"likes 0.0 0.0 0.00 0.340 \n",
"dislikes 0.0 0.0 0.00 0.000 \n",
"shares 0.0 0.0 0.00 0.000 \n",
"videosAddedToPlaylists 0.0 0.0 0.00 0.000 \n",
"videosRemovedFromPlaylists 0.0 0.0 0.00 2.000 \n",
"estimatedMinutesWatched 0.0 0.0 3.00 56.000 \n",
"estimatedRedMinutesWatched 0.0 0.0 0.00 0.000 \n",
"averageViewDuration 0.0 0.0 72.00 305.000 \n",
"averageViewPercentage 0.0 0.0 7.99 34.960 \n",
"cardClickRate 0.0 0.0 0.00 0.000 \n",
"cardTeaserClickRate 0.0 0.0 0.00 0.000 \n",
"cardImpressions 0.0 0.0 0.00 0.000 \n",
"cardTeaserImpressions 0.0 0.0 0.00 0.000 \n",
"cardClicks 0.0 0.0 0.00 0.000 \n",
"cardTeaserClicks 0.0 0.0 0.00 0.000 \n",
"subscribersGained 0.0 0.0 0.00 0.000 \n",
"subscribersLost 0.0 0.0 0.00 0.000 \n",
"grossRevenue 0.0 0.0 0.00 0.057 \n",
"monetizedPlaybacks 0.0 0.0 0.00 8.000 \n",
"playbackBasedCpm 0.0 0.0 0.00 6.000 \n",
"adImpressions 0.0 0.0 0.00 12.000 \n",
"cpm 0.0 0.0 0.00 4.000 \n",
"length 9.0 635.0 808.00 1200.000 \n",
"CumulativeSubscribers -105.0 0.0 0.00 0.000 \n",
"Channel 1.0 1.0 2.00 2.000 \n",
"numOfKeywords 0.0 1.0 17.00 48.000 \n",
"PlaylistCategory 1.0 21.0 29.00 45.000 \n",
"daysFromPublishDateToDataRetrieval 0.0 83.0 232.00 429.000 \n",
"\n",
" max \n",
"views 730749.000 \n",
"redViews 32461.000 \n",
"comments 3041.000 \n",
"likes 18001.000 \n",
"dislikes 1638.000 \n",
"shares 2952.000 \n",
"videosAddedToPlaylists 1819.000 \n",
"videosRemovedFromPlaylists 1675.000 \n",
"estimatedMinutesWatched 2458178.000 \n",
"estimatedRedMinutesWatched 170741.000 \n",
"averageViewDuration 11544.000 \n",
"averageViewPercentage 518.130 \n",
"cardClickRate 1.500 \n",
"cardTeaserClickRate 1.000 \n",
"cardImpressions 3429.000 \n",
"cardTeaserImpressions 183411.000 \n",
"cardClicks 94.000 \n",
"cardTeaserClicks 735.000 \n",
"subscribersGained 1268.000 \n",
"subscribersLost 159.000 \n",
"grossRevenue 1864.061 \n",
"monetizedPlaybacks 293115.000 \n",
"playbackBasedCpm 17755.667 \n",
"adImpressions 427568.000 \n",
"cpm 8877.833 \n",
"length 33440.000 \n",
"CumulativeSubscribers 1208.000 \n",
"Channel 4.000 \n",
"numOfKeywords 111.000 \n",
"PlaylistCategory 45.000 \n",
"daysFromPublishDateToDataRetrieval 2292.000 "
],
"text/html": [
"\n",
" <div id=\"df-840e7346-6040-4a32-a3d4-8d0c945d58e2\">\n",
" <div class=\"colab-df-container\">\n",
" <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>count</th>\n",
" <th>mean</th>\n",
" <th>std</th>\n",
" <th>min</th>\n",
" <th>25%</th>\n",
" <th>50%</th>\n",
" <th>75%</th>\n",
" <th>max</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>views</th>\n",
" <td>133170.0</td>\n",
" <td>2159.193602</td>\n",
" <td>10499.123501</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>2.00</td>\n",
" <td>13.000</td>\n",
" <td>730749.000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>redViews</th>\n",
" <td>133170.0</td>\n",
" <td>92.106263</td>\n",
" <td>451.276751</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.00</td>\n",
" <td>0.000</td>\n",
" <td>32461.000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>comments</th>\n",
" <td>133170.0</td>\n",
" <td>4.116565</td>\n",
" <td>23.777574</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.00</td>\n",
" <td>0.000</td>\n",
" <td>3041.000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>likes</th>\n",
" <td>133170.0</td>\n",
" <td>121.799494</td>\n",
" <td>543.898989</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.00</td>\n",
" <td>0.340</td>\n",
" <td>18001.000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>dislikes</th>\n",
" <td>133170.0</td>\n",
" <td>1.420680</td>\n",
" <td>8.860767</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.00</td>\n",
" <td>0.000</td>\n",
" <td>1638.000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>shares</th>\n",
" <td>133170.0</td>\n",
" <td>11.991590</td>\n",
" <td>62.700418</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.00</td>\n",
" <td>0.000</td>\n",
" <td>2952.000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>videosAddedToPlaylists</th>\n",
" <td>133170.0</td>\n",
" <td>15.255966</td>\n",
" <td>64.298396</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.00</td>\n",
" <td>0.000</td>\n",
" <td>1819.000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>videosRemovedFromPlaylists</th>\n",
" <td>133170.0</td>\n",
" <td>9.385350</td>\n",
" <td>34.372455</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.00</td>\n",
" <td>2.000</td>\n",
" <td>1675.000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>estimatedMinutesWatched</th>\n",
" <td>133170.0</td>\n",
" <td>16650.691064</td>\n",
" <td>82663.759487</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>3.00</td>\n",
" <td>56.000</td>\n",
" <td>2458178.000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>estimatedRedMinutesWatched</th>\n",
" <td>133170.0</td>\n",
" <td>879.384659</td>\n",
" <td>4390.837129</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.00</td>\n",
" <td>0.000</td>\n",
" <td>170741.000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>averageViewDuration</th>\n",
" <td>133170.0</td>\n",
" <td>191.394391</td>\n",
" <td>286.653344</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>72.00</td>\n",
" <td>305.000</td>\n",
" <td>11544.000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>averageViewPercentage</th>\n",
" <td>133170.0</td>\n",
" <td>19.209420</td>\n",
" <td>23.207633</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>7.99</td>\n",
" <td>34.960</td>\n",
" <td>518.130</td>\n",
" </tr>\n",
" <tr>\n",
" <th>cardClickRate</th>\n",
" <td>133170.0</td>\n",
" <td>0.002891</td>\n",
" <td>0.034418</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.00</td>\n",
" <td>0.000</td>\n",
" <td>1.500</td>\n",
" </tr>\n",
" <tr>\n",
" <th>cardTeaserClickRate</th>\n",
" <td>133170.0</td>\n",
" <td>0.000179</td>\n",
" <td>0.006385</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.00</td>\n",
" <td>0.000</td>\n",
" <td>1.000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>cardImpressions</th>\n",
" <td>133170.0</td>\n",
" <td>1.345558</td>\n",
" <td>29.385509</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.00</td>\n",
" <td>0.000</td>\n",
" <td>3429.000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>cardTeaserImpressions</th>\n",
" <td>133170.0</td>\n",
" <td>364.117932</td>\n",
" <td>3238.819497</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.00</td>\n",
" <td>0.000</td>\n",
" <td>183411.000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>cardClicks</th>\n",
" <td>133170.0</td>\n",
" <td>0.056161</td>\n",
" <td>0.862664</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.00</td>\n",
" <td>0.000</td>\n",
" <td>94.000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>cardTeaserClicks</th>\n",
" <td>133170.0</td>\n",
" <td>0.419847</td>\n",
" <td>7.003825</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.00</td>\n",
" <td>0.000</td>\n",
" <td>735.000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>subscribersGained</th>\n",
" <td>133170.0</td>\n",
" <td>1.906706</td>\n",
" <td>15.927877</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.00</td>\n",
" <td>0.000</td>\n",
" <td>1268.000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>subscribersLost</th>\n",
" <td>133170.0</td>\n",
" <td>0.391537</td>\n",
" <td>2.088110</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.00</td>\n",
" <td>0.000</td>\n",
" <td>159.000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>grossRevenue</th>\n",
" <td>133170.0</td>\n",
" <td>14.817125</td>\n",
" <td>72.241918</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.00</td>\n",
" <td>0.057</td>\n",
" <td>1864.061</td>\n",
" </tr>\n",
" <tr>\n",
" <th>monetizedPlaybacks</th>\n",
" <td>133170.0</td>\n",
" <td>1971.845739</td>\n",
" <td>9527.403908</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.00</td>\n",
" <td>8.000</td>\n",
" <td>293115.000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>playbackBasedCpm</th>\n",
" <td>133170.0</td>\n",
" <td>4.072948</td>\n",
" <td>49.854216</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.00</td>\n",
" <td>6.000</td>\n",
" <td>17755.667</td>\n",
" </tr>\n",
" <tr>\n",
" <th>adImpressions</th>\n",
" <td>133170.0</td>\n",
" <td>3240.556394</td>\n",
" <td>15743.825556</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.00</td>\n",
" <td>12.000</td>\n",
" <td>427568.000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>cpm</th>\n",
" <td>133170.0</td>\n",
" <td>2.524946</td>\n",
" <td>25.228942</td>\n",
" <td>0.0</td>\n",
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" <td>0.00</td>\n",
" <td>4.000</td>\n",
" <td>8877.833</td>\n",
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" <tr>\n",
" <th>length</th>\n",
" <td>133170.0</td>\n",
" <td>1476.820117</td>\n",
" <td>2160.380796</td>\n",
" <td>9.0</td>\n",
" <td>635.0</td>\n",
" <td>808.00</td>\n",
" <td>1200.000</td>\n",
" <td>33440.000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>CumulativeSubscribers</th>\n",
" <td>133170.0</td>\n",
" <td>1.515169</td>\n",
" <td>14.706610</td>\n",
" <td>-105.0</td>\n",
" <td>0.0</td>\n",
" <td>0.00</td>\n",
" <td>0.000</td>\n",
" <td>1208.000</td>\n",
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" <tr>\n",
" <th>Channel</th>\n",
" <td>133170.0</td>\n",
" <td>1.757077</td>\n",
" <td>0.625806</td>\n",
" <td>1.0</td>\n",
" <td>1.0</td>\n",
" <td>2.00</td>\n",
" <td>2.000</td>\n",
" <td>4.000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>numOfKeywords</th>\n",
" <td>133170.0</td>\n",
" <td>25.304363</td>\n",
" <td>27.916158</td>\n",
" <td>0.0</td>\n",
" <td>1.0</td>\n",
" <td>17.00</td>\n",
" <td>48.000</td>\n",
" <td>111.000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>PlaylistCategory</th>\n",
" <td>133170.0</td>\n",
" <td>30.985995</td>\n",
" <td>13.089769</td>\n",
" <td>1.0</td>\n",
" <td>21.0</td>\n",
" <td>29.00</td>\n",
" <td>45.000</td>\n",
" <td>45.000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>daysFromPublishDateToDataRetrieval</th>\n",
" <td>133170.0</td>\n",
" <td>283.954314</td>\n",
" <td>244.958514</td>\n",
" <td>0.0</td>\n",
" <td>83.0</td>\n",
" <td>232.00</td>\n",
" <td>429.000</td>\n",
" <td>2292.000</td>\n",
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]
},
"metadata": {},
"execution_count": 125
}
],
"source": [
"summary_df = df.describe(include='all')\n",
"summary_df = summary_df.T\n",
"summary_df "
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"id": "EhBpPzk5qqi1",
"outputId": "3b8e43eb-b3e5-4cd7-e0b3-676ff15fadbb",
"colab": {
"base_uri": "https://localhost:8080/"
}
},
"outputs": [
{
"output_type": "execute_result",
"data": {
"text/plain": [
"Series([], dtype: int64)"
]
},
"metadata": {},
"execution_count": 126
}
],
"source": [
"df.isna().sum()[df.isna().sum() != 0]"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"id": "P_IjE5otqqi2"
},
"outputs": [],
"source": [
"gross_revenue_col = df.pop('grossRevenue')\n",
"df.insert(0, 'grossRevenue', gross_revenue_col)"
]
},
{
"cell_type": "markdown",
"source": [
"## Show Duplicate rows"
],
"metadata": {
"id": "z6fAmPzd9npv"
}
},
{
"cell_type": "code",
"source": [
"duplicate_df = df[df.duplicated()]\n",
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],
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"execution_count": null,
"outputs": [
{
"output_type": "execute_result",
"data": {
"text/plain": [
" grossRevenue views redViews comments likes dislikes shares \\\n",
"864 0.0 0.0 0.0 0.0 0.0 0.0 0.0 \n",
"1539 0.0 0.0 0.0 0.0 0.0 0.0 0.0 \n",
"1635 0.0 0.0 0.0 0.0 0.0 0.0 0.0 \n",
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"... ... ... ... ... ... ... ... \n",
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"\n",
" videosAddedToPlaylists videosRemovedFromPlaylists \\\n",
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" monetizedPlaybacks playbackBasedCpm adImpressions cpm length \\\n",
"864 0.0 0.0 0.0 0.0 557.0 \n",
"1539 0.0 0.0 0.0 0.0 557.0 \n",
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" CumulativeSubscribers Channel numOfKeywords PlaylistCategory \\\n",
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" <td>261.0</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",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\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>129711</th>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>595.0</td>\n",
" <td>0.0</td>\n",
" <td>3.0</td>\n",
" <td>72.0</td>\n",
" <td>25.0</td>\n",
" <td>51.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>129793</th>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>491.0</td>\n",
" <td>0.0</td>\n",
" <td>3.0</td>\n",
" <td>59.0</td>\n",
" <td>25.0</td>\n",
" <td>200.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>131857</th>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>481.0</td>\n",
" <td>0.0</td>\n",
" <td>4.0</td>\n",
" <td>1.0</td>\n",
" <td>15.0</td>\n",
" <td>308.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>132476</th>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>481.0</td>\n",
" <td>0.0</td>\n",
" <td>4.0</td>\n",
" <td>1.0</td>\n",
" <td>15.0</td>\n",
" <td>339.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>132791</th>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>482.0</td>\n",
" <td>0.0</td>\n",
" <td>4.0</td>\n",
" <td>26.0</td>\n",
" <td>15.0</td>\n",
" <td>76.0</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"<p>92 rows × 31 columns</p>\n",
"</div>\n",
" <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-3ea6a41a-73f5-4002-9fb0-2298a51fcffa')\"\n",
" title=\"Convert this dataframe to an interactive table.\"\n",
" style=\"display:none;\">\n",
" \n",
" <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
" width=\"24px\">\n",
" <path d=\"M0 0h24v24H0V0z\" fill=\"none\"/>\n",
" <path d=\"M18.56 5.44l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94zm-11 1L8.5 8.5l.94-2.06 2.06-.94-2.06-.94L8.5 2.5l-.94 2.06-2.06.94zm10 10l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94z\"/><path d=\"M17.41 7.96l-1.37-1.37c-.4-.4-.92-.59-1.43-.59-.52 0-1.04.2-1.43.59L10.3 9.45l-7.72 7.72c-.78.78-.78 2.05 0 2.83L4 21.41c.39.39.9.59 1.41.59.51 0 1.02-.2 1.41-.59l7.78-7.78 2.81-2.81c.8-.78.8-2.07 0-2.86zM5.41 20L4 18.59l7.72-7.72 1.47 1.35L5.41 20z\"/>\n",
" </svg>\n",
" </button>\n",
" \n",
" <style>\n",
" .colab-df-container {\n",
" display:flex;\n",
" flex-wrap:wrap;\n",
" gap: 12px;\n",
" }\n",
"\n",
" .colab-df-convert {\n",
" background-color: #E8F0FE;\n",
" border: none;\n",
" border-radius: 50%;\n",
" cursor: pointer;\n",
" display: none;\n",
" fill: #1967D2;\n",
" height: 32px;\n",
" padding: 0 0 0 0;\n",
" width: 32px;\n",
" }\n",
"\n",
" .colab-df-convert:hover {\n",
" background-color: #E2EBFA;\n",
" box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
" fill: #174EA6;\n",
" }\n",
"\n",
" [theme=dark] .colab-df-convert {\n",
" background-color: #3B4455;\n",
" fill: #D2E3FC;\n",
" }\n",
"\n",
" [theme=dark] .colab-df-convert:hover {\n",
" background-color: #434B5C;\n",
" box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
" filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
" fill: #FFFFFF;\n",
" }\n",
" </style>\n",
"\n",
" <script>\n",
" const buttonEl =\n",
" document.querySelector('#df-3ea6a41a-73f5-4002-9fb0-2298a51fcffa button.colab-df-convert');\n",
" buttonEl.style.display =\n",
" google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
"\n",
" async function convertToInteractive(key) {\n",
" const element = document.querySelector('#df-3ea6a41a-73f5-4002-9fb0-2298a51fcffa');\n",
" const dataTable =\n",
" await google.colab.kernel.invokeFunction('convertToInteractive',\n",
" [key], {});\n",
" if (!dataTable) return;\n",
"\n",
" const docLinkHtml = 'Like what you see? Visit the ' +\n",
" '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
" + ' to learn more about interactive tables.';\n",
" element.innerHTML = '';\n",
" dataTable['output_type'] = 'display_data';\n",
" await google.colab.output.renderOutput(dataTable, element);\n",
" const docLink = document.createElement('div');\n",
" docLink.innerHTML = docLinkHtml;\n",
" element.appendChild(docLink);\n",
" }\n",
" </script>\n",
" </div>\n",
" </div>\n",
" "
]
},
"metadata": {},
"execution_count": 133
}
]
},
{
"cell_type": "markdown",
"source": [
"## Drop 0 views, 0 adImpressions, etc."
],
"metadata": {
"id": "O-uDFmvRfBCg"
}
},
{
"cell_type": "code",
"source": [
"remove_df = df[(df['adImpressions'] == 0)]\n",
"remove_df"
],
"metadata": {
"id": "EbT3ZXPE3uc9"
},
"execution_count": null,
"outputs": []
},
{
"cell_type": "code",
"source": [
"df = df.drop(remove_df.index,errors='ignore')\n",
"df.reset_index(drop=True, inplace=True)"
],
"metadata": {
"id": "iVa6U9hi3zPV"
},
"execution_count": null,
"outputs": []
},
{
"cell_type": "code",
"source": [
"remove_df = df[(df['views'] == 0) & (df['redViews'] == 0)]\n",
"remove_df"
],
"metadata": {
"id": "huMKWDcFivzf"
},
"execution_count": null,
"outputs": []
},
{
"cell_type": "code",
"source": [
"df = df.drop(remove_df.index,errors='ignore')\n",
"df.reset_index(drop=True, inplace=True)"
],
"metadata": {
"id": "-3L_OBr6jwXT"
},
"execution_count": null,
"outputs": []
},
{
"cell_type": "code",
"source": [
"len(df)"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "8OLADAOK-oNf",
"outputId": "c9f4d0d0-4c77-4fc4-dbba-89ea737c637d"
},
"execution_count": null,
"outputs": [
{
"output_type": "execute_result",
"data": {
"text/plain": [
"62916"
]
},
"metadata": {},
"execution_count": 150
}
]
},
{
"cell_type": "markdown",
"source": [
"## Drop Lowly Correlated Variables (<0.5)"
],
"metadata": {
"id": "ajHc_4KBstq8"
}
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"id": "7DPwCFoIqqiz"
},
"outputs": [],
"source": [
"#Only numerical values\n",
"num_df = df\n",
"num_df = num_df.drop('Channel', axis=1)\n",
"num_df = num_df.drop('PlaylistCategory', axis=1)"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"id": "w0F1EIQ2qqiz",
"outputId": "418694bc-d9e8-4a1e-bf8c-c933ff6ebd9c",
"colab": {
"base_uri": "https://localhost:8080/"
}
},
"outputs": [
{
"output_type": "execute_result",
"data": {
"text/plain": [
" grossRevenue views redViews \\\n",
"grossRevenue 1.000000 0.896221 0.867498 \n",
"views 0.896221 1.000000 0.969096 \n",
"redViews 0.867498 0.969096 1.000000 \n",
"comments 0.693357 0.747849 0.787051 \n",
"likes 0.904362 0.880637 0.831578 \n",
"dislikes 0.675779 0.824809 0.788898 \n",
"shares 0.818165 0.831151 0.788561 \n",
"videosAddedToPlaylists 0.911066 0.893728 0.855399 \n",
"videosRemovedFromPlaylists 0.871958 0.869344 0.852084 \n",
"estimatedMinutesWatched 0.906425 0.878297 0.865456 \n",
"estimatedRedMinutesWatched 0.866161 0.844381 0.875825 \n",
"averageViewDuration 0.169409 0.131921 0.142872 \n",
"averageViewPercentage 0.186656 0.195644 0.191271 \n",
"cardClickRate 0.241542 0.237707 0.236057 \n",
"cardTeaserClickRate 0.005648 0.004142 0.004152 \n",
"cardImpressions 0.180609 0.177861 0.143633 \n",
"cardTeaserImpressions 0.487047 0.492966 0.481286 \n",
"cardClicks 0.278366 0.286460 0.259902 \n",
"cardTeaserClicks 0.227961 0.213413 0.177021 \n",
"subscribersGained 0.667617 0.770972 0.756490 \n",
"subscribersLost 0.734069 0.748367 0.749917 \n",
"monetizedPlaybacks 0.973013 0.933356 0.903988 \n",
"playbackBasedCpm -0.000306 -0.004962 -0.004773 \n",
"adImpressions 0.985759 0.922657 0.892692 \n",
"cpm -0.002446 -0.006601 -0.006399 \n",
"length -0.002389 -0.024462 -0.011914 \n",
"CumulativeSubscribers 0.618290 0.728067 0.712182 \n",
"numOfKeywords 0.047816 0.075308 0.101310 \n",
"daysFromPublishDateToDataRetrieval -0.247163 -0.243247 -0.243733 \n",
"\n",
" comments likes dislikes shares \\\n",
"grossRevenue 0.693357 0.904362 0.675779 0.818165 \n",
"views 0.747849 0.880637 0.824809 0.831151 \n",
"redViews 0.787051 0.831578 0.788898 0.788561 \n",
"comments 1.000000 0.697669 0.642609 0.722934 \n",
"likes 0.697669 1.000000 0.697455 0.881143 \n",
"dislikes 0.642609 0.697455 1.000000 0.707118 \n",
"shares 0.722934 0.881143 0.707118 1.000000 \n",
"videosAddedToPlaylists 0.713733 0.965812 0.690591 0.892757 \n",
"videosRemovedFromPlaylists 0.687493 0.922696 0.644885 0.809781 \n",
"estimatedMinutesWatched 0.752633 0.911857 0.715884 0.845905 \n",
"estimatedRedMinutesWatched 0.774180 0.862574 0.677037 0.787315 \n",
"averageViewDuration 0.142968 0.182742 0.141513 0.159831 \n",
"averageViewPercentage 0.147946 0.209009 0.158386 0.178684 \n",
"cardClickRate 0.166525 0.258220 0.161316 0.197961 \n",
"cardTeaserClickRate 0.004886 0.006603 0.003484 0.005111 \n",
"cardImpressions 0.116571 0.200442 0.127363 0.166836 \n",
"cardTeaserImpressions 0.363252 0.446746 0.334572 0.386598 \n",
"cardClicks 0.203246 0.276990 0.198537 0.242974 \n",
"cardTeaserClicks 0.153278 0.250792 0.162012 0.211005 \n",
"subscribersGained 0.615336 0.550869 0.631346 0.625167 \n",
"subscribersLost 0.688951 0.763905 0.629282 0.723906 \n",
"monetizedPlaybacks 0.707748 0.913221 0.678266 0.834746 \n",
"playbackBasedCpm -0.003673 -0.004530 -0.003291 -0.004070 \n",
"adImpressions 0.703339 0.916127 0.678270 0.833160 \n",
"cpm -0.005035 -0.006517 -0.004600 -0.005744 \n",
"length 0.018493 -0.002401 0.016640 0.003760 \n",
"CumulativeSubscribers 0.568122 0.487780 0.593884 0.573809 \n",
"numOfKeywords 0.040434 0.050279 0.011417 0.018316 \n",
"daysFromPublishDateToDataRetrieval -0.205367 -0.270249 -0.193743 -0.224304 \n",
"\n",
" videosAddedToPlaylists \\\n",
"grossRevenue 0.911066 \n",
"views 0.893728 \n",
"redViews 0.855399 \n",
"comments 0.713733 \n",
"likes 0.965812 \n",
"dislikes 0.690591 \n",
"shares 0.892757 \n",
"videosAddedToPlaylists 1.000000 \n",
"videosRemovedFromPlaylists 0.966756 \n",
"estimatedMinutesWatched 0.902931 \n",
"estimatedRedMinutesWatched 0.854630 \n",
"averageViewDuration 0.174700 \n",
"averageViewPercentage 0.220386 \n",
"cardClickRate 0.257608 \n",
"cardTeaserClickRate 0.005686 \n",
"cardImpressions 0.185523 \n",
"cardTeaserImpressions 0.462071 \n",
"cardClicks 0.273353 \n",
"cardTeaserClicks 0.231880 \n",
"subscribersGained 0.602464 \n",
"subscribersLost 0.770275 \n",
"monetizedPlaybacks 0.923616 \n",
"playbackBasedCpm -0.004878 \n",
"adImpressions 0.922974 \n",
"cpm -0.006848 \n",
"length -0.016498 \n",
"CumulativeSubscribers 0.542689 \n",
"numOfKeywords 0.057401 \n",
"daysFromPublishDateToDataRetrieval -0.281510 \n",
"\n",
" videosRemovedFromPlaylists \\\n",
"grossRevenue 0.871958 \n",
"views 0.869344 \n",
"redViews 0.852084 \n",
"comments 0.687493 \n",
"likes 0.922696 \n",
"dislikes 0.644885 \n",
"shares 0.809781 \n",
"videosAddedToPlaylists 0.966756 \n",
"videosRemovedFromPlaylists 1.000000 \n",
"estimatedMinutesWatched 0.847362 \n",
"estimatedRedMinutesWatched 0.822990 \n",
"averageViewDuration 0.162834 \n",
"averageViewPercentage 0.231090 \n",
"cardClickRate 0.275452 \n",
"cardTeaserClickRate 0.006030 \n",
"cardImpressions 0.173274 \n",
"cardTeaserImpressions 0.460810 \n",
"cardClicks 0.261907 \n",
"cardTeaserClicks 0.214833 \n",
"subscribersGained 0.555688 \n",
"subscribersLost 0.732187 \n",
"monetizedPlaybacks 0.893937 \n",
"playbackBasedCpm -0.005717 \n",
"adImpressions 0.889937 \n",
"cpm -0.007652 \n",
"length -0.034579 \n",
"CumulativeSubscribers 0.497482 \n",
"numOfKeywords 0.093345 \n",
"daysFromPublishDateToDataRetrieval -0.310708 \n",
"\n",
" estimatedMinutesWatched \\\n",
"grossRevenue 0.906425 \n",
"views 0.878297 \n",
"redViews 0.865456 \n",
"comments 0.752633 \n",
"likes 0.911857 \n",
"dislikes 0.715884 \n",
"shares 0.845905 \n",
"videosAddedToPlaylists 0.902931 \n",
"videosRemovedFromPlaylists 0.847362 \n",
"estimatedMinutesWatched 1.000000 \n",
"estimatedRedMinutesWatched 0.974735 \n",
"averageViewDuration 0.233865 \n",
"averageViewPercentage 0.151279 \n",
"cardClickRate 0.218201 \n",
"cardTeaserClickRate 0.003903 \n",
"cardImpressions 0.148387 \n",
"cardTeaserImpressions 0.422584 \n",
"cardClicks 0.240840 \n",
"cardTeaserClicks 0.186930 \n",
"subscribersGained 0.664655 \n",
"subscribersLost 0.804399 \n",
"monetizedPlaybacks 0.902469 \n",
"playbackBasedCpm -0.003422 \n",
"adImpressions 0.911012 \n",
"cpm -0.005394 \n",
"length 0.071267 \n",
"CumulativeSubscribers 0.605133 \n",
"numOfKeywords 0.062330 \n",
"daysFromPublishDateToDataRetrieval -0.240485 \n",
"\n",
" estimatedRedMinutesWatched \\\n",
"grossRevenue 0.866161 \n",
"views 0.844381 \n",
"redViews 0.875825 \n",
"comments 0.774180 \n",
"likes 0.862574 \n",
"dislikes 0.677037 \n",
"shares 0.787315 \n",
"videosAddedToPlaylists 0.854630 \n",
"videosRemovedFromPlaylists 0.822990 \n",
"estimatedMinutesWatched 0.974735 \n",
"estimatedRedMinutesWatched 1.000000 \n",
"averageViewDuration 0.242988 \n",
"averageViewPercentage 0.139952 \n",
"cardClickRate 0.213680 \n",
"cardTeaserClickRate 0.004051 \n",
"cardImpressions 0.119147 \n",
"cardTeaserImpressions 0.398343 \n",
"cardClicks 0.212446 \n",
"cardTeaserClicks 0.155724 \n",
"subscribersGained 0.638763 \n",
"subscribersLost 0.796843 \n",
"monetizedPlaybacks 0.864006 \n",
"playbackBasedCpm -0.003273 \n",
"adImpressions 0.871398 \n",
"cpm -0.005243 \n",
"length 0.087878 \n",
"CumulativeSubscribers 0.578195 \n",
"numOfKeywords 0.086425 \n",
"daysFromPublishDateToDataRetrieval -0.240034 \n",
"\n",
" averageViewDuration \\\n",
"grossRevenue 0.169409 \n",
"views 0.131921 \n",
"redViews 0.142872 \n",
"comments 0.142968 \n",
"likes 0.182742 \n",
"dislikes 0.141513 \n",
"shares 0.159831 \n",
"videosAddedToPlaylists 0.174700 \n",
"videosRemovedFromPlaylists 0.162834 \n",
"estimatedMinutesWatched 0.233865 \n",
"estimatedRedMinutesWatched 0.242988 \n",
"averageViewDuration 1.000000 \n",
"averageViewPercentage 0.438359 \n",
"cardClickRate 0.041112 \n",
"cardTeaserClickRate -0.001747 \n",
"cardImpressions 0.017892 \n",
"cardTeaserImpressions 0.049550 \n",
"cardClicks 0.027353 \n",
"cardTeaserClicks 0.029724 \n",
"subscribersGained 0.074358 \n",
"subscribersLost 0.178998 \n",
"monetizedPlaybacks 0.150762 \n",
"playbackBasedCpm 0.014082 \n",
"adImpressions 0.158249 \n",
"cpm 0.002278 \n",
"length 0.430214 \n",
"CumulativeSubscribers 0.055104 \n",
"numOfKeywords 0.014823 \n",
"daysFromPublishDateToDataRetrieval -0.069899 \n",
"\n",
" averageViewPercentage cardClickRate \\\n",
"grossRevenue 0.186656 0.241542 \n",
"views 0.195644 0.237707 \n",
"redViews 0.191271 0.236057 \n",
"comments 0.147946 0.166525 \n",
"likes 0.209009 0.258220 \n",
"dislikes 0.158386 0.161316 \n",
"shares 0.178684 0.197961 \n",
"videosAddedToPlaylists 0.220386 0.257608 \n",
"videosRemovedFromPlaylists 0.231090 0.275452 \n",
"estimatedMinutesWatched 0.151279 0.218201 \n",
"estimatedRedMinutesWatched 0.139952 0.213680 \n",
"averageViewDuration 0.438359 0.041112 \n",
"averageViewPercentage 1.000000 0.079032 \n",
"cardClickRate 0.079032 1.000000 \n",
"cardTeaserClickRate 0.003068 0.049340 \n",
"cardImpressions 0.053690 0.048261 \n",
"cardTeaserImpressions 0.122071 0.178478 \n",
"cardClicks 0.072476 0.220629 \n",
"cardTeaserClicks 0.067598 0.077180 \n",
"subscribersGained 0.099669 0.119489 \n",
"subscribersLost 0.143862 0.186541 \n",
"monetizedPlaybacks 0.191253 0.252843 \n",
"playbackBasedCpm 0.009781 -0.001994 \n",
"adImpressions 0.188716 0.247798 \n",
"cpm 0.000798 -0.002400 \n",
"length -0.304512 -0.023350 \n",
"CumulativeSubscribers 0.087455 0.102855 \n",
"numOfKeywords -0.057517 0.045941 \n",
"daysFromPublishDateToDataRetrieval -0.072863 -0.096285 \n",
"\n",
" cardTeaserClickRate cardImpressions \\\n",
"grossRevenue 0.005648 0.180609 \n",
"views 0.004142 0.177861 \n",
"redViews 0.004152 0.143633 \n",
"comments 0.004886 0.116571 \n",
"likes 0.006603 0.200442 \n",
"dislikes 0.003484 0.127363 \n",
"shares 0.005111 0.166836 \n",
"videosAddedToPlaylists 0.005686 0.185523 \n",
"videosRemovedFromPlaylists 0.006030 0.173274 \n",
"estimatedMinutesWatched 0.003903 0.148387 \n",
"estimatedRedMinutesWatched 0.004051 0.119147 \n",
"averageViewDuration -0.001747 0.017892 \n",
"averageViewPercentage 0.003068 0.053690 \n",
"cardClickRate 0.049340 0.048261 \n",
"cardTeaserClickRate 1.000000 0.019680 \n",
"cardImpressions 0.019680 1.000000 \n",
"cardTeaserImpressions 0.015473 0.713442 \n",
"cardClicks 0.021930 0.857827 \n",
"cardTeaserClicks 0.033766 0.954298 \n",
"subscribersGained 0.001041 0.106659 \n",
"subscribersLost 0.008124 0.128722 \n",
"monetizedPlaybacks 0.004603 0.180089 \n",
"playbackBasedCpm 0.000179 -0.000714 \n",
"adImpressions 0.004922 0.188038 \n",
"cpm -0.000167 -0.001361 \n",
"length -0.004168 -0.020296 \n",
"CumulativeSubscribers -0.000024 0.097159 \n",
"numOfKeywords -0.014791 -0.033079 \n",
"daysFromPublishDateToDataRetrieval -0.020204 -0.054258 \n",
"\n",
" cardTeaserImpressions cardClicks \\\n",
"grossRevenue 0.487047 0.278366 \n",
"views 0.492966 0.286460 \n",
"redViews 0.481286 0.259902 \n",
"comments 0.363252 0.203246 \n",
"likes 0.446746 0.276990 \n",
"dislikes 0.334572 0.198537 \n",
"shares 0.386598 0.242974 \n",
"videosAddedToPlaylists 0.462071 0.273353 \n",
"videosRemovedFromPlaylists 0.460810 0.261907 \n",
"estimatedMinutesWatched 0.422584 0.240840 \n",
"estimatedRedMinutesWatched 0.398343 0.212446 \n",
"averageViewDuration 0.049550 0.027353 \n",
"averageViewPercentage 0.122071 0.072476 \n",
"cardClickRate 0.178478 0.220629 \n",
"cardTeaserClickRate 0.015473 0.021930 \n",
"cardImpressions 0.713442 0.857827 \n",
"cardTeaserImpressions 1.000000 0.776155 \n",
"cardClicks 0.776155 1.000000 \n",
"cardTeaserClicks 0.714629 0.850201 \n",
"subscribersGained 0.392459 0.210472 \n",
"subscribersLost 0.385036 0.219306 \n",
"monetizedPlaybacks 0.492794 0.285063 \n",
"playbackBasedCpm -0.001853 -0.001227 \n",
"adImpressions 0.493686 0.287363 \n",
"cpm -0.002880 -0.001876 \n",
"length -0.044392 -0.026338 \n",
"CumulativeSubscribers 0.370041 0.196635 \n",
"numOfKeywords 0.011872 -0.019450 \n",
"daysFromPublishDateToDataRetrieval -0.133061 -0.077111 \n",
"\n",
" cardTeaserClicks subscribersGained \\\n",
"grossRevenue 0.227961 0.667617 \n",
"views 0.213413 0.770972 \n",
"redViews 0.177021 0.756490 \n",
"comments 0.153278 0.615336 \n",
"likes 0.250792 0.550869 \n",
"dislikes 0.162012 0.631346 \n",
"shares 0.211005 0.625167 \n",
"videosAddedToPlaylists 0.231880 0.602464 \n",
"videosRemovedFromPlaylists 0.214833 0.555688 \n",
"estimatedMinutesWatched 0.186930 0.664655 \n",
"estimatedRedMinutesWatched 0.155724 0.638763 \n",
"averageViewDuration 0.029724 0.074358 \n",
"averageViewPercentage 0.067598 0.099669 \n",
"cardClickRate 0.077180 0.119489 \n",
"cardTeaserClickRate 0.033766 0.001041 \n",
"cardImpressions 0.954298 0.106659 \n",
"cardTeaserImpressions 0.714629 0.392459 \n",
"cardClicks 0.850201 0.210472 \n",
"cardTeaserClicks 1.000000 0.123339 \n",
"subscribersGained 0.123339 1.000000 \n",
"subscribersLost 0.181318 0.621038 \n",
"monetizedPlaybacks 0.219689 0.695869 \n",
"playbackBasedCpm -0.000589 -0.002816 \n",
"adImpressions 0.229567 0.681202 \n",
"cpm -0.001398 -0.003587 \n",
"length -0.020276 -0.008002 \n",
"CumulativeSubscribers 0.107759 0.993830 \n",
"numOfKeywords -0.048063 0.038908 \n",
"daysFromPublishDateToDataRetrieval -0.070724 -0.137026 \n",
"\n",
" subscribersLost monetizedPlaybacks \\\n",
"grossRevenue 0.734069 0.973013 \n",
"views 0.748367 0.933356 \n",
"redViews 0.749917 0.903988 \n",
"comments 0.688951 0.707748 \n",
"likes 0.763905 0.913221 \n",
"dislikes 0.629282 0.678266 \n",
"shares 0.723906 0.834746 \n",
"videosAddedToPlaylists 0.770275 0.923616 \n",
"videosRemovedFromPlaylists 0.732187 0.893937 \n",
"estimatedMinutesWatched 0.804399 0.902469 \n",
"estimatedRedMinutesWatched 0.796843 0.864006 \n",
"averageViewDuration 0.178998 0.150762 \n",
"averageViewPercentage 0.143862 0.191253 \n",
"cardClickRate 0.186541 0.252843 \n",
"cardTeaserClickRate 0.008124 0.004603 \n",
"cardImpressions 0.128722 0.180089 \n",
"cardTeaserImpressions 0.385036 0.492794 \n",
"cardClicks 0.219306 0.285063 \n",
"cardTeaserClicks 0.181318 0.219689 \n",
"subscribersGained 0.621038 0.695869 \n",
"subscribersLost 1.000000 0.743564 \n",
"monetizedPlaybacks 0.743564 1.000000 \n",
"playbackBasedCpm -0.003617 -0.004319 \n",
"adImpressions 0.738978 0.994893 \n",
"cpm -0.004993 -0.006174 \n",
"length 0.039117 -0.017044 \n",
"CumulativeSubscribers 0.530272 0.647508 \n",
"numOfKeywords 0.029166 0.079234 \n",
"daysFromPublishDateToDataRetrieval -0.221032 -0.247356 \n",
"\n",
" playbackBasedCpm adImpressions cpm \\\n",
"grossRevenue -0.000306 0.985759 -0.002446 \n",
"views -0.004962 0.922657 -0.006601 \n",
"redViews -0.004773 0.892692 -0.006399 \n",
"comments -0.003673 0.703339 -0.005035 \n",
"likes -0.004530 0.916127 -0.006517 \n",
"dislikes -0.003291 0.678270 -0.004600 \n",
"shares -0.004070 0.833160 -0.005744 \n",
"videosAddedToPlaylists -0.004878 0.922974 -0.006848 \n",
"videosRemovedFromPlaylists -0.005717 0.889937 -0.007652 \n",
"estimatedMinutesWatched -0.003422 0.911012 -0.005394 \n",
"estimatedRedMinutesWatched -0.003273 0.871398 -0.005243 \n",
"averageViewDuration 0.014082 0.158249 0.002278 \n",
"averageViewPercentage 0.009781 0.188716 0.000798 \n",
"cardClickRate -0.001994 0.247798 -0.002400 \n",
"cardTeaserClickRate 0.000179 0.004922 -0.000167 \n",
"cardImpressions -0.000714 0.188038 -0.001361 \n",
"cardTeaserImpressions -0.001853 0.493686 -0.002880 \n",
"cardClicks -0.001227 0.287363 -0.001876 \n",
"cardTeaserClicks -0.000589 0.229567 -0.001398 \n",
"subscribersGained -0.002816 0.681202 -0.003587 \n",
"subscribersLost -0.003617 0.738978 -0.004993 \n",
"monetizedPlaybacks -0.004319 0.994893 -0.006174 \n",
"playbackBasedCpm 1.000000 -0.003737 0.993123 \n",
"adImpressions -0.003737 1.000000 -0.005816 \n",
"cpm 0.993123 -0.005816 1.000000 \n",
"length 0.002479 -0.011038 -0.000266 \n",
"CumulativeSubscribers -0.002534 0.632291 -0.003174 \n",
"numOfKeywords -0.009037 0.073536 -0.011508 \n",
"daysFromPublishDateToDataRetrieval -0.010301 -0.247062 -0.007628 \n",
"\n",
" length CumulativeSubscribers \\\n",
"grossRevenue -0.002389 0.618290 \n",
"views -0.024462 0.728067 \n",
"redViews -0.011914 0.712182 \n",
"comments 0.018493 0.568122 \n",
"likes -0.002401 0.487780 \n",
"dislikes 0.016640 0.593884 \n",
"shares 0.003760 0.573809 \n",
"videosAddedToPlaylists -0.016498 0.542689 \n",
"videosRemovedFromPlaylists -0.034579 0.497482 \n",
"estimatedMinutesWatched 0.071267 0.605133 \n",
"estimatedRedMinutesWatched 0.087878 0.578195 \n",
"averageViewDuration 0.430214 0.055104 \n",
"averageViewPercentage -0.304512 0.087455 \n",
"cardClickRate -0.023350 0.102855 \n",
"cardTeaserClickRate -0.004168 -0.000024 \n",
"cardImpressions -0.020296 0.097159 \n",
"cardTeaserImpressions -0.044392 0.370041 \n",
"cardClicks -0.026338 0.196635 \n",
"cardTeaserClicks -0.020276 0.107759 \n",
"subscribersGained -0.008002 0.993830 \n",
"subscribersLost 0.039117 0.530272 \n",
"monetizedPlaybacks -0.017044 0.647508 \n",
"playbackBasedCpm 0.002479 -0.002534 \n",
"adImpressions -0.011038 0.632291 \n",
"cpm -0.000266 -0.003174 \n",
"length 1.000000 -0.014192 \n",
"CumulativeSubscribers -0.014192 1.000000 \n",
"numOfKeywords -0.008243 0.037960 \n",
"daysFromPublishDateToDataRetrieval 0.065624 -0.116944 \n",
"\n",
" numOfKeywords \\\n",
"grossRevenue 0.047816 \n",
"views 0.075308 \n",
"redViews 0.101310 \n",
"comments 0.040434 \n",
"likes 0.050279 \n",
"dislikes 0.011417 \n",
"shares 0.018316 \n",
"videosAddedToPlaylists 0.057401 \n",
"videosRemovedFromPlaylists 0.093345 \n",
"estimatedMinutesWatched 0.062330 \n",
"estimatedRedMinutesWatched 0.086425 \n",
"averageViewDuration 0.014823 \n",
"averageViewPercentage -0.057517 \n",
"cardClickRate 0.045941 \n",
"cardTeaserClickRate -0.014791 \n",
"cardImpressions -0.033079 \n",
"cardTeaserImpressions 0.011872 \n",
"cardClicks -0.019450 \n",
"cardTeaserClicks -0.048063 \n",
"subscribersGained 0.038908 \n",
"subscribersLost 0.029166 \n",
"monetizedPlaybacks 0.079234 \n",
"playbackBasedCpm -0.009037 \n",
"adImpressions 0.073536 \n",
"cpm -0.011508 \n",
"length -0.008243 \n",
"CumulativeSubscribers 0.037960 \n",
"numOfKeywords 1.000000 \n",
"daysFromPublishDateToDataRetrieval -0.134546 \n",
"\n",
" daysFromPublishDateToDataRetrieval \n",
"grossRevenue -0.247163 \n",
"views -0.243247 \n",
"redViews -0.243733 \n",
"comments -0.205367 \n",
"likes -0.270249 \n",
"dislikes -0.193743 \n",
"shares -0.224304 \n",
"videosAddedToPlaylists -0.281510 \n",
"videosRemovedFromPlaylists -0.310708 \n",
"estimatedMinutesWatched -0.240485 \n",
"estimatedRedMinutesWatched -0.240034 \n",
"averageViewDuration -0.069899 \n",
"averageViewPercentage -0.072863 \n",
"cardClickRate -0.096285 \n",
"cardTeaserClickRate -0.020204 \n",
"cardImpressions -0.054258 \n",
"cardTeaserImpressions -0.133061 \n",
"cardClicks -0.077111 \n",
"cardTeaserClicks -0.070724 \n",
"subscribersGained -0.137026 \n",
"subscribersLost -0.221032 \n",
"monetizedPlaybacks -0.247356 \n",
"playbackBasedCpm -0.010301 \n",
"adImpressions -0.247062 \n",
"cpm -0.007628 \n",
"length 0.065624 \n",
"CumulativeSubscribers -0.116944 \n",
"numOfKeywords -0.134546 \n",
"daysFromPublishDateToDataRetrieval 1.000000 "
],
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" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>grossRevenue</th>\n",
" <th>views</th>\n",
" <th>redViews</th>\n",
" <th>comments</th>\n",
" <th>likes</th>\n",
" <th>dislikes</th>\n",
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" <th>cardTeaserImpressions</th>\n",
" <th>cardClicks</th>\n",
" <th>cardTeaserClicks</th>\n",
" <th>subscribersGained</th>\n",
" <th>subscribersLost</th>\n",
" <th>monetizedPlaybacks</th>\n",
" <th>playbackBasedCpm</th>\n",
" <th>adImpressions</th>\n",
" <th>cpm</th>\n",
" <th>length</th>\n",
" <th>CumulativeSubscribers</th>\n",
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" <tr>\n",
" <th>grossRevenue</th>\n",
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" <td>0.867498</td>\n",
" <td>0.693357</td>\n",
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" <td>0.866161</td>\n",
" <td>0.169409</td>\n",
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" <td>0.005648</td>\n",
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" <td>0.985759</td>\n",
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" <td>-0.002389</td>\n",
" <td>0.618290</td>\n",
" <td>0.047816</td>\n",
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" <td>0.969096</td>\n",
" <td>0.747849</td>\n",
" <td>0.880637</td>\n",
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" <td>0.131921</td>\n",
" <td>0.195644</td>\n",
" <td>0.237707</td>\n",
" <td>0.004142</td>\n",
" <td>0.177861</td>\n",
" <td>0.492966</td>\n",
" <td>0.286460</td>\n",
" <td>0.213413</td>\n",
" <td>0.770972</td>\n",
" <td>0.748367</td>\n",
" <td>0.933356</td>\n",
" <td>-0.004962</td>\n",
" <td>0.922657</td>\n",
" <td>-0.006601</td>\n",
" <td>-0.024462</td>\n",
" <td>0.728067</td>\n",
" <td>0.075308</td>\n",
" <td>-0.243247</td>\n",
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" <tr>\n",
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" <td>0.969096</td>\n",
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" <td>0.787051</td>\n",
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" <td>-0.243733</td>\n",
" </tr>\n",
" <tr>\n",
" <th>comments</th>\n",
" <td>0.693357</td>\n",
" <td>0.747849</td>\n",
" <td>0.787051</td>\n",
" <td>1.000000</td>\n",
" <td>0.697669</td>\n",
" <td>0.642609</td>\n",
" <td>0.722934</td>\n",
" <td>0.713733</td>\n",
" <td>0.687493</td>\n",
" <td>0.752633</td>\n",
" <td>0.774180</td>\n",
" <td>0.142968</td>\n",
" <td>0.147946</td>\n",
" <td>0.166525</td>\n",
" <td>0.004886</td>\n",
" <td>0.116571</td>\n",
" <td>0.363252</td>\n",
" <td>0.203246</td>\n",
" <td>0.153278</td>\n",
" <td>0.615336</td>\n",
" <td>0.688951</td>\n",
" <td>0.707748</td>\n",
" <td>-0.003673</td>\n",
" <td>0.703339</td>\n",
" <td>-0.005035</td>\n",
" <td>0.018493</td>\n",
" <td>0.568122</td>\n",
" <td>0.040434</td>\n",
" <td>-0.205367</td>\n",
" </tr>\n",
" <tr>\n",
" <th>likes</th>\n",
" <td>0.904362</td>\n",
" <td>0.880637</td>\n",
" <td>0.831578</td>\n",
" <td>0.697669</td>\n",
" <td>1.000000</td>\n",
" <td>0.697455</td>\n",
" <td>0.881143</td>\n",
" <td>0.965812</td>\n",
" <td>0.922696</td>\n",
" <td>0.911857</td>\n",
" <td>0.862574</td>\n",
" <td>0.182742</td>\n",
" <td>0.209009</td>\n",
" <td>0.258220</td>\n",
" <td>0.006603</td>\n",
" <td>0.200442</td>\n",
" <td>0.446746</td>\n",
" <td>0.276990</td>\n",
" <td>0.250792</td>\n",
" <td>0.550869</td>\n",
" <td>0.763905</td>\n",
" <td>0.913221</td>\n",
" <td>-0.004530</td>\n",
" <td>0.916127</td>\n",
" <td>-0.006517</td>\n",
" <td>-0.002401</td>\n",
" <td>0.487780</td>\n",
" <td>0.050279</td>\n",
" <td>-0.270249</td>\n",
" </tr>\n",
" <tr>\n",
" <th>dislikes</th>\n",
" <td>0.675779</td>\n",
" <td>0.824809</td>\n",
" <td>0.788898</td>\n",
" <td>0.642609</td>\n",
" <td>0.697455</td>\n",
" <td>1.000000</td>\n",
" <td>0.707118</td>\n",
" <td>0.690591</td>\n",
" <td>0.644885</td>\n",
" <td>0.715884</td>\n",
" <td>0.677037</td>\n",
" <td>0.141513</td>\n",
" <td>0.158386</td>\n",
" <td>0.161316</td>\n",
" <td>0.003484</td>\n",
" <td>0.127363</td>\n",
" <td>0.334572</td>\n",
" <td>0.198537</td>\n",
" <td>0.162012</td>\n",
" <td>0.631346</td>\n",
" <td>0.629282</td>\n",
" <td>0.678266</td>\n",
" <td>-0.003291</td>\n",
" <td>0.678270</td>\n",
" <td>-0.004600</td>\n",
" <td>0.016640</td>\n",
" <td>0.593884</td>\n",
" <td>0.011417</td>\n",
" <td>-0.193743</td>\n",
" </tr>\n",
" <tr>\n",
" <th>shares</th>\n",
" <td>0.818165</td>\n",
" <td>0.831151</td>\n",
" <td>0.788561</td>\n",
" <td>0.722934</td>\n",
" <td>0.881143</td>\n",
" <td>0.707118</td>\n",
" <td>1.000000</td>\n",
" <td>0.892757</td>\n",
" <td>0.809781</td>\n",
" <td>0.845905</td>\n",
" <td>0.787315</td>\n",
" <td>0.159831</td>\n",
" <td>0.178684</td>\n",
" <td>0.197961</td>\n",
" <td>0.005111</td>\n",
" <td>0.166836</td>\n",
" <td>0.386598</td>\n",
" <td>0.242974</td>\n",
" <td>0.211005</td>\n",
" <td>0.625167</td>\n",
" <td>0.723906</td>\n",
" <td>0.834746</td>\n",
" <td>-0.004070</td>\n",
" <td>0.833160</td>\n",
" <td>-0.005744</td>\n",
" <td>0.003760</td>\n",
" <td>0.573809</td>\n",
" <td>0.018316</td>\n",
" <td>-0.224304</td>\n",
" </tr>\n",
" <tr>\n",
" <th>videosAddedToPlaylists</th>\n",
" <td>0.911066</td>\n",
" <td>0.893728</td>\n",
" <td>0.855399</td>\n",
" <td>0.713733</td>\n",
" <td>0.965812</td>\n",
" <td>0.690591</td>\n",
" <td>0.892757</td>\n",
" <td>1.000000</td>\n",
" <td>0.966756</td>\n",
" <td>0.902931</td>\n",
" <td>0.854630</td>\n",
" <td>0.174700</td>\n",
" <td>0.220386</td>\n",
" <td>0.257608</td>\n",
" <td>0.005686</td>\n",
" <td>0.185523</td>\n",
" <td>0.462071</td>\n",
" <td>0.273353</td>\n",
" <td>0.231880</td>\n",
" <td>0.602464</td>\n",
" <td>0.770275</td>\n",
" <td>0.923616</td>\n",
" <td>-0.004878</td>\n",
" <td>0.922974</td>\n",
" <td>-0.006848</td>\n",
" <td>-0.016498</td>\n",
" <td>0.542689</td>\n",
" <td>0.057401</td>\n",
" <td>-0.281510</td>\n",
" </tr>\n",
" <tr>\n",
" <th>videosRemovedFromPlaylists</th>\n",
" <td>0.871958</td>\n",
" <td>0.869344</td>\n",
" <td>0.852084</td>\n",
" <td>0.687493</td>\n",
" <td>0.922696</td>\n",
" <td>0.644885</td>\n",
" <td>0.809781</td>\n",
" <td>0.966756</td>\n",
" <td>1.000000</td>\n",
" <td>0.847362</td>\n",
" <td>0.822990</td>\n",
" <td>0.162834</td>\n",
" <td>0.231090</td>\n",
" <td>0.275452</td>\n",
" <td>0.006030</td>\n",
" <td>0.173274</td>\n",
" <td>0.460810</td>\n",
" <td>0.261907</td>\n",
" <td>0.214833</td>\n",
" <td>0.555688</td>\n",
" <td>0.732187</td>\n",
" <td>0.893937</td>\n",
" <td>-0.005717</td>\n",
" <td>0.889937</td>\n",
" <td>-0.007652</td>\n",
" <td>-0.034579</td>\n",
" <td>0.497482</td>\n",
" <td>0.093345</td>\n",
" <td>-0.310708</td>\n",
" </tr>\n",
" <tr>\n",
" <th>estimatedMinutesWatched</th>\n",
" <td>0.906425</td>\n",
" <td>0.878297</td>\n",
" <td>0.865456</td>\n",
" <td>0.752633</td>\n",
" <td>0.911857</td>\n",
" <td>0.715884</td>\n",
" <td>0.845905</td>\n",
" <td>0.902931</td>\n",
" <td>0.847362</td>\n",
" <td>1.000000</td>\n",
" <td>0.974735</td>\n",
" <td>0.233865</td>\n",
" <td>0.151279</td>\n",
" <td>0.218201</td>\n",
" <td>0.003903</td>\n",
" <td>0.148387</td>\n",
" <td>0.422584</td>\n",
" <td>0.240840</td>\n",
" <td>0.186930</td>\n",
" <td>0.664655</td>\n",
" <td>0.804399</td>\n",
" <td>0.902469</td>\n",
" <td>-0.003422</td>\n",
" <td>0.911012</td>\n",
" <td>-0.005394</td>\n",
" <td>0.071267</td>\n",
" <td>0.605133</td>\n",
" <td>0.062330</td>\n",
" <td>-0.240485</td>\n",
" </tr>\n",
" <tr>\n",
" <th>estimatedRedMinutesWatched</th>\n",
" <td>0.866161</td>\n",
" <td>0.844381</td>\n",
" <td>0.875825</td>\n",
" <td>0.774180</td>\n",
" <td>0.862574</td>\n",
" <td>0.677037</td>\n",
" <td>0.787315</td>\n",
" <td>0.854630</td>\n",
" <td>0.822990</td>\n",
" <td>0.974735</td>\n",
" <td>1.000000</td>\n",
" <td>0.242988</td>\n",
" <td>0.139952</td>\n",
" <td>0.213680</td>\n",
" <td>0.004051</td>\n",
" <td>0.119147</td>\n",
" <td>0.398343</td>\n",
" <td>0.212446</td>\n",
" <td>0.155724</td>\n",
" <td>0.638763</td>\n",
" <td>0.796843</td>\n",
" <td>0.864006</td>\n",
" <td>-0.003273</td>\n",
" <td>0.871398</td>\n",
" <td>-0.005243</td>\n",
" <td>0.087878</td>\n",
" <td>0.578195</td>\n",
" <td>0.086425</td>\n",
" <td>-0.240034</td>\n",
" </tr>\n",
" <tr>\n",
" <th>averageViewDuration</th>\n",
" <td>0.169409</td>\n",
" <td>0.131921</td>\n",
" <td>0.142872</td>\n",
" <td>0.142968</td>\n",
" <td>0.182742</td>\n",
" <td>0.141513</td>\n",
" <td>0.159831</td>\n",
" <td>0.174700</td>\n",
" <td>0.162834</td>\n",
" <td>0.233865</td>\n",
" <td>0.242988</td>\n",
" <td>1.000000</td>\n",
" <td>0.438359</td>\n",
" <td>0.041112</td>\n",
" <td>-0.001747</td>\n",
" <td>0.017892</td>\n",
" <td>0.049550</td>\n",
" <td>0.027353</td>\n",
" <td>0.029724</td>\n",
" <td>0.074358</td>\n",
" <td>0.178998</td>\n",
" <td>0.150762</td>\n",
" <td>0.014082</td>\n",
" <td>0.158249</td>\n",
" <td>0.002278</td>\n",
" <td>0.430214</td>\n",
" <td>0.055104</td>\n",
" <td>0.014823</td>\n",
" <td>-0.069899</td>\n",
" </tr>\n",
" <tr>\n",
" <th>averageViewPercentage</th>\n",
" <td>0.186656</td>\n",
" <td>0.195644</td>\n",
" <td>0.191271</td>\n",
" <td>0.147946</td>\n",
" <td>0.209009</td>\n",
" <td>0.158386</td>\n",
" <td>0.178684</td>\n",
" <td>0.220386</td>\n",
" <td>0.231090</td>\n",
" <td>0.151279</td>\n",
" <td>0.139952</td>\n",
" <td>0.438359</td>\n",
" <td>1.000000</td>\n",
" <td>0.079032</td>\n",
" <td>0.003068</td>\n",
" <td>0.053690</td>\n",
" <td>0.122071</td>\n",
" <td>0.072476</td>\n",
" <td>0.067598</td>\n",
" <td>0.099669</td>\n",
" <td>0.143862</td>\n",
" <td>0.191253</td>\n",
" <td>0.009781</td>\n",
" <td>0.188716</td>\n",
" <td>0.000798</td>\n",
" <td>-0.304512</td>\n",
" <td>0.087455</td>\n",
" <td>-0.057517</td>\n",
" <td>-0.072863</td>\n",
" </tr>\n",
" <tr>\n",
" <th>cardClickRate</th>\n",
" <td>0.241542</td>\n",
" <td>0.237707</td>\n",
" <td>0.236057</td>\n",
" <td>0.166525</td>\n",
" <td>0.258220</td>\n",
" <td>0.161316</td>\n",
" <td>0.197961</td>\n",
" <td>0.257608</td>\n",
" <td>0.275452</td>\n",
" <td>0.218201</td>\n",
" <td>0.213680</td>\n",
" <td>0.041112</td>\n",
" <td>0.079032</td>\n",
" <td>1.000000</td>\n",
" <td>0.049340</td>\n",
" <td>0.048261</td>\n",
" <td>0.178478</td>\n",
" <td>0.220629</td>\n",
" <td>0.077180</td>\n",
" <td>0.119489</td>\n",
" <td>0.186541</td>\n",
" <td>0.252843</td>\n",
" <td>-0.001994</td>\n",
" <td>0.247798</td>\n",
" <td>-0.002400</td>\n",
" <td>-0.023350</td>\n",
" <td>0.102855</td>\n",
" <td>0.045941</td>\n",
" <td>-0.096285</td>\n",
" </tr>\n",
" <tr>\n",
" <th>cardTeaserClickRate</th>\n",
" <td>0.005648</td>\n",
" <td>0.004142</td>\n",
" <td>0.004152</td>\n",
" <td>0.004886</td>\n",
" <td>0.006603</td>\n",
" <td>0.003484</td>\n",
" <td>0.005111</td>\n",
" <td>0.005686</td>\n",
" <td>0.006030</td>\n",
" <td>0.003903</td>\n",
" <td>0.004051</td>\n",
" <td>-0.001747</td>\n",
" <td>0.003068</td>\n",
" <td>0.049340</td>\n",
" <td>1.000000</td>\n",
" <td>0.019680</td>\n",
" <td>0.015473</td>\n",
" <td>0.021930</td>\n",
" <td>0.033766</td>\n",
" <td>0.001041</td>\n",
" <td>0.008124</td>\n",
" <td>0.004603</td>\n",
" <td>0.000179</td>\n",
" <td>0.004922</td>\n",
" <td>-0.000167</td>\n",
" <td>-0.004168</td>\n",
" <td>-0.000024</td>\n",
" <td>-0.014791</td>\n",
" <td>-0.020204</td>\n",
" </tr>\n",
" <tr>\n",
" <th>cardImpressions</th>\n",
" <td>0.180609</td>\n",
" <td>0.177861</td>\n",
" <td>0.143633</td>\n",
" <td>0.116571</td>\n",
" <td>0.200442</td>\n",
" <td>0.127363</td>\n",
" <td>0.166836</td>\n",
" <td>0.185523</td>\n",
" <td>0.173274</td>\n",
" <td>0.148387</td>\n",
" <td>0.119147</td>\n",
" <td>0.017892</td>\n",
" <td>0.053690</td>\n",
" <td>0.048261</td>\n",
" <td>0.019680</td>\n",
" <td>1.000000</td>\n",
" <td>0.713442</td>\n",
" <td>0.857827</td>\n",
" <td>0.954298</td>\n",
" <td>0.106659</td>\n",
" <td>0.128722</td>\n",
" <td>0.180089</td>\n",
" <td>-0.000714</td>\n",
" <td>0.188038</td>\n",
" <td>-0.001361</td>\n",
" <td>-0.020296</td>\n",
" <td>0.097159</td>\n",
" <td>-0.033079</td>\n",
" <td>-0.054258</td>\n",
" </tr>\n",
" <tr>\n",
" <th>cardTeaserImpressions</th>\n",
" <td>0.487047</td>\n",
" <td>0.492966</td>\n",
" <td>0.481286</td>\n",
" <td>0.363252</td>\n",
" <td>0.446746</td>\n",
" <td>0.334572</td>\n",
" <td>0.386598</td>\n",
" <td>0.462071</td>\n",
" <td>0.460810</td>\n",
" <td>0.422584</td>\n",
" <td>0.398343</td>\n",
" <td>0.049550</td>\n",
" <td>0.122071</td>\n",
" <td>0.178478</td>\n",
" <td>0.015473</td>\n",
" <td>0.713442</td>\n",
" <td>1.000000</td>\n",
" <td>0.776155</td>\n",
" <td>0.714629</td>\n",
" <td>0.392459</td>\n",
" <td>0.385036</td>\n",
" <td>0.492794</td>\n",
" <td>-0.001853</td>\n",
" <td>0.493686</td>\n",
" <td>-0.002880</td>\n",
" <td>-0.044392</td>\n",
" <td>0.370041</td>\n",
" <td>0.011872</td>\n",
" <td>-0.133061</td>\n",
" </tr>\n",
" <tr>\n",
" <th>cardClicks</th>\n",
" <td>0.278366</td>\n",
" <td>0.286460</td>\n",
" <td>0.259902</td>\n",
" <td>0.203246</td>\n",
" <td>0.276990</td>\n",
" <td>0.198537</td>\n",
" <td>0.242974</td>\n",
" <td>0.273353</td>\n",
" <td>0.261907</td>\n",
" <td>0.240840</td>\n",
" <td>0.212446</td>\n",
" <td>0.027353</td>\n",
" <td>0.072476</td>\n",
" <td>0.220629</td>\n",
" <td>0.021930</td>\n",
" <td>0.857827</td>\n",
" <td>0.776155</td>\n",
" <td>1.000000</td>\n",
" <td>0.850201</td>\n",
" <td>0.210472</td>\n",
" <td>0.219306</td>\n",
" <td>0.285063</td>\n",
" <td>-0.001227</td>\n",
" <td>0.287363</td>\n",
" <td>-0.001876</td>\n",
" <td>-0.026338</td>\n",
" <td>0.196635</td>\n",
" <td>-0.019450</td>\n",
" <td>-0.077111</td>\n",
" </tr>\n",
" <tr>\n",
" <th>cardTeaserClicks</th>\n",
" <td>0.227961</td>\n",
" <td>0.213413</td>\n",
" <td>0.177021</td>\n",
" <td>0.153278</td>\n",
" <td>0.250792</td>\n",
" <td>0.162012</td>\n",
" <td>0.211005</td>\n",
" <td>0.231880</td>\n",
" <td>0.214833</td>\n",
" <td>0.186930</td>\n",
" <td>0.155724</td>\n",
" <td>0.029724</td>\n",
" <td>0.067598</td>\n",
" <td>0.077180</td>\n",
" <td>0.033766</td>\n",
" <td>0.954298</td>\n",
" <td>0.714629</td>\n",
" <td>0.850201</td>\n",
" <td>1.000000</td>\n",
" <td>0.123339</td>\n",
" <td>0.181318</td>\n",
" <td>0.219689</td>\n",
" <td>-0.000589</td>\n",
" <td>0.229567</td>\n",
" <td>-0.001398</td>\n",
" <td>-0.020276</td>\n",
" <td>0.107759</td>\n",
" <td>-0.048063</td>\n",
" <td>-0.070724</td>\n",
" </tr>\n",
" <tr>\n",
" <th>subscribersGained</th>\n",
" <td>0.667617</td>\n",
" <td>0.770972</td>\n",
" <td>0.756490</td>\n",
" <td>0.615336</td>\n",
" <td>0.550869</td>\n",
" <td>0.631346</td>\n",
" <td>0.625167</td>\n",
" <td>0.602464</td>\n",
" <td>0.555688</td>\n",
" <td>0.664655</td>\n",
" <td>0.638763</td>\n",
" <td>0.074358</td>\n",
" <td>0.099669</td>\n",
" <td>0.119489</td>\n",
" <td>0.001041</td>\n",
" <td>0.106659</td>\n",
" <td>0.392459</td>\n",
" <td>0.210472</td>\n",
" <td>0.123339</td>\n",
" <td>1.000000</td>\n",
" <td>0.621038</td>\n",
" <td>0.695869</td>\n",
" <td>-0.002816</td>\n",
" <td>0.681202</td>\n",
" <td>-0.003587</td>\n",
" <td>-0.008002</td>\n",
" <td>0.993830</td>\n",
" <td>0.038908</td>\n",
" <td>-0.137026</td>\n",
" </tr>\n",
" <tr>\n",
" <th>subscribersLost</th>\n",
" <td>0.734069</td>\n",
" <td>0.748367</td>\n",
" <td>0.749917</td>\n",
" <td>0.688951</td>\n",
" <td>0.763905</td>\n",
" <td>0.629282</td>\n",
" <td>0.723906</td>\n",
" <td>0.770275</td>\n",
" <td>0.732187</td>\n",
" <td>0.804399</td>\n",
" <td>0.796843</td>\n",
" <td>0.178998</td>\n",
" <td>0.143862</td>\n",
" <td>0.186541</td>\n",
" <td>0.008124</td>\n",
" <td>0.128722</td>\n",
" <td>0.385036</td>\n",
" <td>0.219306</td>\n",
" <td>0.181318</td>\n",
" <td>0.621038</td>\n",
" <td>1.000000</td>\n",
" <td>0.743564</td>\n",
" <td>-0.003617</td>\n",
" <td>0.738978</td>\n",
" <td>-0.004993</td>\n",
" <td>0.039117</td>\n",
" <td>0.530272</td>\n",
" <td>0.029166</td>\n",
" <td>-0.221032</td>\n",
" </tr>\n",
" <tr>\n",
" <th>monetizedPlaybacks</th>\n",
" <td>0.973013</td>\n",
" <td>0.933356</td>\n",
" <td>0.903988</td>\n",
" <td>0.707748</td>\n",
" <td>0.913221</td>\n",
" <td>0.678266</td>\n",
" <td>0.834746</td>\n",
" <td>0.923616</td>\n",
" <td>0.893937</td>\n",
" <td>0.902469</td>\n",
" <td>0.864006</td>\n",
" <td>0.150762</td>\n",
" <td>0.191253</td>\n",
" <td>0.252843</td>\n",
" <td>0.004603</td>\n",
" <td>0.180089</td>\n",
" <td>0.492794</td>\n",
" <td>0.285063</td>\n",
" <td>0.219689</td>\n",
" <td>0.695869</td>\n",
" <td>0.743564</td>\n",
" <td>1.000000</td>\n",
" <td>-0.004319</td>\n",
" <td>0.994893</td>\n",
" <td>-0.006174</td>\n",
" <td>-0.017044</td>\n",
" <td>0.647508</td>\n",
" <td>0.079234</td>\n",
" <td>-0.247356</td>\n",
" </tr>\n",
" <tr>\n",
" <th>playbackBasedCpm</th>\n",
" <td>-0.000306</td>\n",
" <td>-0.004962</td>\n",
" <td>-0.004773</td>\n",
" <td>-0.003673</td>\n",
" <td>-0.004530</td>\n",
" <td>-0.003291</td>\n",
" <td>-0.004070</td>\n",
" <td>-0.004878</td>\n",
" <td>-0.005717</td>\n",
" <td>-0.003422</td>\n",
" <td>-0.003273</td>\n",
" <td>0.014082</td>\n",
" <td>0.009781</td>\n",
" <td>-0.001994</td>\n",
" <td>0.000179</td>\n",
" <td>-0.000714</td>\n",
" <td>-0.001853</td>\n",
" <td>-0.001227</td>\n",
" <td>-0.000589</td>\n",
" <td>-0.002816</td>\n",
" <td>-0.003617</td>\n",
" <td>-0.004319</td>\n",
" <td>1.000000</td>\n",
" <td>-0.003737</td>\n",
" <td>0.993123</td>\n",
" <td>0.002479</td>\n",
" <td>-0.002534</td>\n",
" <td>-0.009037</td>\n",
" <td>-0.010301</td>\n",
" </tr>\n",
" <tr>\n",
" <th>adImpressions</th>\n",
" <td>0.985759</td>\n",
" <td>0.922657</td>\n",
" <td>0.892692</td>\n",
" <td>0.703339</td>\n",
" <td>0.916127</td>\n",
" <td>0.678270</td>\n",
" <td>0.833160</td>\n",
" <td>0.922974</td>\n",
" <td>0.889937</td>\n",
" <td>0.911012</td>\n",
" <td>0.871398</td>\n",
" <td>0.158249</td>\n",
" <td>0.188716</td>\n",
" <td>0.247798</td>\n",
" <td>0.004922</td>\n",
" <td>0.188038</td>\n",
" <td>0.493686</td>\n",
" <td>0.287363</td>\n",
" <td>0.229567</td>\n",
" <td>0.681202</td>\n",
" <td>0.738978</td>\n",
" <td>0.994893</td>\n",
" <td>-0.003737</td>\n",
" <td>1.000000</td>\n",
" <td>-0.005816</td>\n",
" <td>-0.011038</td>\n",
" <td>0.632291</td>\n",
" <td>0.073536</td>\n",
" <td>-0.247062</td>\n",
" </tr>\n",
" <tr>\n",
" <th>cpm</th>\n",
" <td>-0.002446</td>\n",
" <td>-0.006601</td>\n",
" <td>-0.006399</td>\n",
" <td>-0.005035</td>\n",
" <td>-0.006517</td>\n",
" <td>-0.004600</td>\n",
" <td>-0.005744</td>\n",
" <td>-0.006848</td>\n",
" <td>-0.007652</td>\n",
" <td>-0.005394</td>\n",
" <td>-0.005243</td>\n",
" <td>0.002278</td>\n",
" <td>0.000798</td>\n",
" <td>-0.002400</td>\n",
" <td>-0.000167</td>\n",
" <td>-0.001361</td>\n",
" <td>-0.002880</td>\n",
" <td>-0.001876</td>\n",
" <td>-0.001398</td>\n",
" <td>-0.003587</td>\n",
" <td>-0.004993</td>\n",
" <td>-0.006174</td>\n",
" <td>0.993123</td>\n",
" <td>-0.005816</td>\n",
" <td>1.000000</td>\n",
" <td>-0.000266</td>\n",
" <td>-0.003174</td>\n",
" <td>-0.011508</td>\n",
" <td>-0.007628</td>\n",
" </tr>\n",
" <tr>\n",
" <th>length</th>\n",
" <td>-0.002389</td>\n",
" <td>-0.024462</td>\n",
" <td>-0.011914</td>\n",
" <td>0.018493</td>\n",
" <td>-0.002401</td>\n",
" <td>0.016640</td>\n",
" <td>0.003760</td>\n",
" <td>-0.016498</td>\n",
" <td>-0.034579</td>\n",
" <td>0.071267</td>\n",
" <td>0.087878</td>\n",
" <td>0.430214</td>\n",
" <td>-0.304512</td>\n",
" <td>-0.023350</td>\n",
" <td>-0.004168</td>\n",
" <td>-0.020296</td>\n",
" <td>-0.044392</td>\n",
" <td>-0.026338</td>\n",
" <td>-0.020276</td>\n",
" <td>-0.008002</td>\n",
" <td>0.039117</td>\n",
" <td>-0.017044</td>\n",
" <td>0.002479</td>\n",
" <td>-0.011038</td>\n",
" <td>-0.000266</td>\n",
" <td>1.000000</td>\n",
" <td>-0.014192</td>\n",
" <td>-0.008243</td>\n",
" <td>0.065624</td>\n",
" </tr>\n",
" <tr>\n",
" <th>CumulativeSubscribers</th>\n",
" <td>0.618290</td>\n",
" <td>0.728067</td>\n",
" <td>0.712182</td>\n",
" <td>0.568122</td>\n",
" <td>0.487780</td>\n",
" <td>0.593884</td>\n",
" <td>0.573809</td>\n",
" <td>0.542689</td>\n",
" <td>0.497482</td>\n",
" <td>0.605133</td>\n",
" <td>0.578195</td>\n",
" <td>0.055104</td>\n",
" <td>0.087455</td>\n",
" <td>0.102855</td>\n",
" <td>-0.000024</td>\n",
" <td>0.097159</td>\n",
" <td>0.370041</td>\n",
" <td>0.196635</td>\n",
" <td>0.107759</td>\n",
" <td>0.993830</td>\n",
" <td>0.530272</td>\n",
" <td>0.647508</td>\n",
" <td>-0.002534</td>\n",
" <td>0.632291</td>\n",
" <td>-0.003174</td>\n",
" <td>-0.014192</td>\n",
" <td>1.000000</td>\n",
" <td>0.037960</td>\n",
" <td>-0.116944</td>\n",
" </tr>\n",
" <tr>\n",
" <th>numOfKeywords</th>\n",
" <td>0.047816</td>\n",
" <td>0.075308</td>\n",
" <td>0.101310</td>\n",
" <td>0.040434</td>\n",
" <td>0.050279</td>\n",
" <td>0.011417</td>\n",
" <td>0.018316</td>\n",
" <td>0.057401</td>\n",
" <td>0.093345</td>\n",
" <td>0.062330</td>\n",
" <td>0.086425</td>\n",
" <td>0.014823</td>\n",
" <td>-0.057517</td>\n",
" <td>0.045941</td>\n",
" <td>-0.014791</td>\n",
" <td>-0.033079</td>\n",
" <td>0.011872</td>\n",
" <td>-0.019450</td>\n",
" <td>-0.048063</td>\n",
" <td>0.038908</td>\n",
" <td>0.029166</td>\n",
" <td>0.079234</td>\n",
" <td>-0.009037</td>\n",
" <td>0.073536</td>\n",
" <td>-0.011508</td>\n",
" <td>-0.008243</td>\n",
" <td>0.037960</td>\n",
" <td>1.000000</td>\n",
" <td>-0.134546</td>\n",
" </tr>\n",
" <tr>\n",
" <th>daysFromPublishDateToDataRetrieval</th>\n",
" <td>-0.247163</td>\n",
" <td>-0.243247</td>\n",
" <td>-0.243733</td>\n",
" <td>-0.205367</td>\n",
" <td>-0.270249</td>\n",
" <td>-0.193743</td>\n",
" <td>-0.224304</td>\n",
" <td>-0.281510</td>\n",
" <td>-0.310708</td>\n",
" <td>-0.240485</td>\n",
" <td>-0.240034</td>\n",
" <td>-0.069899</td>\n",
" <td>-0.072863</td>\n",
" <td>-0.096285</td>\n",
" <td>-0.020204</td>\n",
" <td>-0.054258</td>\n",
" <td>-0.133061</td>\n",
" <td>-0.077111</td>\n",
" <td>-0.070724</td>\n",
" <td>-0.137026</td>\n",
" <td>-0.221032</td>\n",
" <td>-0.247356</td>\n",
" <td>-0.010301</td>\n",
" <td>-0.247062</td>\n",
" <td>-0.007628</td>\n",
" <td>0.065624</td>\n",
" <td>-0.116944</td>\n",
" <td>-0.134546</td>\n",
" <td>1.000000</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>\n",
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]
},
"metadata": {},
"execution_count": 152
}
],
"source": [
"num_df.corr()"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"id": "inFf-uraqqi0",
"outputId": "af3b3758-9211-4da8-9e24-a4aeffba1d34",
"colab": {
"base_uri": "https://localhost:8080/"
}
},
"outputs": [
{
"output_type": "execute_result",
"data": {
"text/plain": [
" grossRevenue views redViews \\\n",
"grossRevenue NaN NaN NaN \n",
"views NaN NaN NaN \n",
"redViews NaN NaN NaN \n",
"comments NaN NaN NaN \n",
"likes NaN NaN NaN \n",
"dislikes NaN NaN NaN \n",
"shares NaN NaN NaN \n",
"videosAddedToPlaylists NaN NaN NaN \n",
"videosRemovedFromPlaylists NaN NaN NaN \n",
"estimatedMinutesWatched NaN NaN NaN \n",
"estimatedRedMinutesWatched NaN NaN NaN \n",
"averageViewDuration 0.169409 0.131921 0.142872 \n",
"averageViewPercentage 0.186656 0.195644 0.191271 \n",
"cardClickRate 0.241542 0.237707 0.236057 \n",
"cardTeaserClickRate 0.005648 0.004142 0.004152 \n",
"cardImpressions 0.180609 0.177861 0.143633 \n",
"cardTeaserImpressions 0.487047 0.492966 0.481286 \n",
"cardClicks 0.278366 0.286460 0.259902 \n",
"cardTeaserClicks 0.227961 0.213413 0.177021 \n",
"subscribersGained NaN NaN NaN \n",
"subscribersLost NaN NaN NaN \n",
"monetizedPlaybacks NaN NaN NaN \n",
"playbackBasedCpm -0.000306 -0.004962 -0.004773 \n",
"adImpressions NaN NaN NaN \n",
"cpm -0.002446 -0.006601 -0.006399 \n",
"length -0.002389 -0.024462 -0.011914 \n",
"CumulativeSubscribers NaN NaN NaN \n",
"numOfKeywords 0.047816 0.075308 0.101310 \n",
"daysFromPublishDateToDataRetrieval -0.247163 -0.243247 -0.243733 \n",
"\n",
" comments likes dislikes shares \\\n",
"grossRevenue NaN NaN NaN NaN \n",
"views NaN NaN NaN NaN \n",
"redViews NaN NaN NaN NaN \n",
"comments NaN NaN NaN NaN \n",
"likes NaN NaN NaN NaN \n",
"dislikes NaN NaN NaN NaN \n",
"shares NaN NaN NaN NaN \n",
"videosAddedToPlaylists NaN NaN NaN NaN \n",
"videosRemovedFromPlaylists NaN NaN NaN NaN \n",
"estimatedMinutesWatched NaN NaN NaN NaN \n",
"estimatedRedMinutesWatched NaN NaN NaN NaN \n",
"averageViewDuration 0.142968 0.182742 0.141513 0.159831 \n",
"averageViewPercentage 0.147946 0.209009 0.158386 0.178684 \n",
"cardClickRate 0.166525 0.258220 0.161316 0.197961 \n",
"cardTeaserClickRate 0.004886 0.006603 0.003484 0.005111 \n",
"cardImpressions 0.116571 0.200442 0.127363 0.166836 \n",
"cardTeaserImpressions 0.363252 0.446746 0.334572 0.386598 \n",
"cardClicks 0.203246 0.276990 0.198537 0.242974 \n",
"cardTeaserClicks 0.153278 0.250792 0.162012 0.211005 \n",
"subscribersGained NaN NaN NaN NaN \n",
"subscribersLost NaN NaN NaN NaN \n",
"monetizedPlaybacks NaN NaN NaN NaN \n",
"playbackBasedCpm -0.003673 -0.004530 -0.003291 -0.004070 \n",
"adImpressions NaN NaN NaN NaN \n",
"cpm -0.005035 -0.006517 -0.004600 -0.005744 \n",
"length 0.018493 -0.002401 0.016640 0.003760 \n",
"CumulativeSubscribers NaN 0.487780 NaN NaN \n",
"numOfKeywords 0.040434 0.050279 0.011417 0.018316 \n",
"daysFromPublishDateToDataRetrieval -0.205367 -0.270249 -0.193743 -0.224304 \n",
"\n",
" videosAddedToPlaylists \\\n",
"grossRevenue NaN \n",
"views NaN \n",
"redViews NaN \n",
"comments NaN \n",
"likes NaN \n",
"dislikes NaN \n",
"shares NaN \n",
"videosAddedToPlaylists NaN \n",
"videosRemovedFromPlaylists NaN \n",
"estimatedMinutesWatched NaN \n",
"estimatedRedMinutesWatched NaN \n",
"averageViewDuration 0.174700 \n",
"averageViewPercentage 0.220386 \n",
"cardClickRate 0.257608 \n",
"cardTeaserClickRate 0.005686 \n",
"cardImpressions 0.185523 \n",
"cardTeaserImpressions 0.462071 \n",
"cardClicks 0.273353 \n",
"cardTeaserClicks 0.231880 \n",
"subscribersGained NaN \n",
"subscribersLost NaN \n",
"monetizedPlaybacks NaN \n",
"playbackBasedCpm -0.004878 \n",
"adImpressions NaN \n",
"cpm -0.006848 \n",
"length -0.016498 \n",
"CumulativeSubscribers NaN \n",
"numOfKeywords 0.057401 \n",
"daysFromPublishDateToDataRetrieval -0.281510 \n",
"\n",
" videosRemovedFromPlaylists \\\n",
"grossRevenue NaN \n",
"views NaN \n",
"redViews NaN \n",
"comments NaN \n",
"likes NaN \n",
"dislikes NaN \n",
"shares NaN \n",
"videosAddedToPlaylists NaN \n",
"videosRemovedFromPlaylists NaN \n",
"estimatedMinutesWatched NaN \n",
"estimatedRedMinutesWatched NaN \n",
"averageViewDuration 0.162834 \n",
"averageViewPercentage 0.231090 \n",
"cardClickRate 0.275452 \n",
"cardTeaserClickRate 0.006030 \n",
"cardImpressions 0.173274 \n",
"cardTeaserImpressions 0.460810 \n",
"cardClicks 0.261907 \n",
"cardTeaserClicks 0.214833 \n",
"subscribersGained NaN \n",
"subscribersLost NaN \n",
"monetizedPlaybacks NaN \n",
"playbackBasedCpm -0.005717 \n",
"adImpressions NaN \n",
"cpm -0.007652 \n",
"length -0.034579 \n",
"CumulativeSubscribers 0.497482 \n",
"numOfKeywords 0.093345 \n",
"daysFromPublishDateToDataRetrieval -0.310708 \n",
"\n",
" estimatedMinutesWatched \\\n",
"grossRevenue NaN \n",
"views NaN \n",
"redViews NaN \n",
"comments NaN \n",
"likes NaN \n",
"dislikes NaN \n",
"shares NaN \n",
"videosAddedToPlaylists NaN \n",
"videosRemovedFromPlaylists NaN \n",
"estimatedMinutesWatched NaN \n",
"estimatedRedMinutesWatched NaN \n",
"averageViewDuration 0.233865 \n",
"averageViewPercentage 0.151279 \n",
"cardClickRate 0.218201 \n",
"cardTeaserClickRate 0.003903 \n",
"cardImpressions 0.148387 \n",
"cardTeaserImpressions 0.422584 \n",
"cardClicks 0.240840 \n",
"cardTeaserClicks 0.186930 \n",
"subscribersGained NaN \n",
"subscribersLost NaN \n",
"monetizedPlaybacks NaN \n",
"playbackBasedCpm -0.003422 \n",
"adImpressions NaN \n",
"cpm -0.005394 \n",
"length 0.071267 \n",
"CumulativeSubscribers NaN \n",
"numOfKeywords 0.062330 \n",
"daysFromPublishDateToDataRetrieval -0.240485 \n",
"\n",
" estimatedRedMinutesWatched \\\n",
"grossRevenue NaN \n",
"views NaN \n",
"redViews NaN \n",
"comments NaN \n",
"likes NaN \n",
"dislikes NaN \n",
"shares NaN \n",
"videosAddedToPlaylists NaN \n",
"videosRemovedFromPlaylists NaN \n",
"estimatedMinutesWatched NaN \n",
"estimatedRedMinutesWatched NaN \n",
"averageViewDuration 0.242988 \n",
"averageViewPercentage 0.139952 \n",
"cardClickRate 0.213680 \n",
"cardTeaserClickRate 0.004051 \n",
"cardImpressions 0.119147 \n",
"cardTeaserImpressions 0.398343 \n",
"cardClicks 0.212446 \n",
"cardTeaserClicks 0.155724 \n",
"subscribersGained NaN \n",
"subscribersLost NaN \n",
"monetizedPlaybacks NaN \n",
"playbackBasedCpm -0.003273 \n",
"adImpressions NaN \n",
"cpm -0.005243 \n",
"length 0.087878 \n",
"CumulativeSubscribers NaN \n",
"numOfKeywords 0.086425 \n",
"daysFromPublishDateToDataRetrieval -0.240034 \n",
"\n",
" averageViewDuration \\\n",
"grossRevenue 0.169409 \n",
"views 0.131921 \n",
"redViews 0.142872 \n",
"comments 0.142968 \n",
"likes 0.182742 \n",
"dislikes 0.141513 \n",
"shares 0.159831 \n",
"videosAddedToPlaylists 0.174700 \n",
"videosRemovedFromPlaylists 0.162834 \n",
"estimatedMinutesWatched 0.233865 \n",
"estimatedRedMinutesWatched 0.242988 \n",
"averageViewDuration NaN \n",
"averageViewPercentage 0.438359 \n",
"cardClickRate 0.041112 \n",
"cardTeaserClickRate -0.001747 \n",
"cardImpressions 0.017892 \n",
"cardTeaserImpressions 0.049550 \n",
"cardClicks 0.027353 \n",
"cardTeaserClicks 0.029724 \n",
"subscribersGained 0.074358 \n",
"subscribersLost 0.178998 \n",
"monetizedPlaybacks 0.150762 \n",
"playbackBasedCpm 0.014082 \n",
"adImpressions 0.158249 \n",
"cpm 0.002278 \n",
"length 0.430214 \n",
"CumulativeSubscribers 0.055104 \n",
"numOfKeywords 0.014823 \n",
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"\n",
" averageViewPercentage cardClickRate \\\n",
"grossRevenue 0.186656 0.241542 \n",
"views 0.195644 0.237707 \n",
"redViews 0.191271 0.236057 \n",
"comments 0.147946 0.166525 \n",
"likes 0.209009 0.258220 \n",
"dislikes 0.158386 0.161316 \n",
"shares 0.178684 0.197961 \n",
"videosAddedToPlaylists 0.220386 0.257608 \n",
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"estimatedMinutesWatched 0.151279 0.218201 \n",
"estimatedRedMinutesWatched 0.139952 0.213680 \n",
"averageViewDuration 0.438359 0.041112 \n",
"averageViewPercentage NaN 0.079032 \n",
"cardClickRate 0.079032 NaN \n",
"cardTeaserClickRate 0.003068 0.049340 \n",
"cardImpressions 0.053690 0.048261 \n",
"cardTeaserImpressions 0.122071 0.178478 \n",
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"subscribersGained 0.099669 0.119489 \n",
"subscribersLost 0.143862 0.186541 \n",
"monetizedPlaybacks 0.191253 0.252843 \n",
"playbackBasedCpm 0.009781 -0.001994 \n",
"adImpressions 0.188716 0.247798 \n",
"cpm 0.000798 -0.002400 \n",
"length -0.304512 -0.023350 \n",
"CumulativeSubscribers 0.087455 0.102855 \n",
"numOfKeywords -0.057517 0.045941 \n",
"daysFromPublishDateToDataRetrieval -0.072863 -0.096285 \n",
"\n",
" cardTeaserClickRate cardImpressions \\\n",
"grossRevenue 0.005648 0.180609 \n",
"views 0.004142 0.177861 \n",
"redViews 0.004152 0.143633 \n",
"comments 0.004886 0.116571 \n",
"likes 0.006603 0.200442 \n",
"dislikes 0.003484 0.127363 \n",
"shares 0.005111 0.166836 \n",
"videosAddedToPlaylists 0.005686 0.185523 \n",
"videosRemovedFromPlaylists 0.006030 0.173274 \n",
"estimatedMinutesWatched 0.003903 0.148387 \n",
"estimatedRedMinutesWatched 0.004051 0.119147 \n",
"averageViewDuration -0.001747 0.017892 \n",
"averageViewPercentage 0.003068 0.053690 \n",
"cardClickRate 0.049340 0.048261 \n",
"cardTeaserClickRate NaN 0.019680 \n",
"cardImpressions 0.019680 NaN \n",
"cardTeaserImpressions 0.015473 NaN \n",
"cardClicks 0.021930 NaN \n",
"cardTeaserClicks 0.033766 NaN \n",
"subscribersGained 0.001041 0.106659 \n",
"subscribersLost 0.008124 0.128722 \n",
"monetizedPlaybacks 0.004603 0.180089 \n",
"playbackBasedCpm 0.000179 -0.000714 \n",
"adImpressions 0.004922 0.188038 \n",
"cpm -0.000167 -0.001361 \n",
"length -0.004168 -0.020296 \n",
"CumulativeSubscribers -0.000024 0.097159 \n",
"numOfKeywords -0.014791 -0.033079 \n",
"daysFromPublishDateToDataRetrieval -0.020204 -0.054258 \n",
"\n",
" cardTeaserImpressions cardClicks \\\n",
"grossRevenue 0.487047 0.278366 \n",
"views 0.492966 0.286460 \n",
"redViews 0.481286 0.259902 \n",
"comments 0.363252 0.203246 \n",
"likes 0.446746 0.276990 \n",
"dislikes 0.334572 0.198537 \n",
"shares 0.386598 0.242974 \n",
"videosAddedToPlaylists 0.462071 0.273353 \n",
"videosRemovedFromPlaylists 0.460810 0.261907 \n",
"estimatedMinutesWatched 0.422584 0.240840 \n",
"estimatedRedMinutesWatched 0.398343 0.212446 \n",
"averageViewDuration 0.049550 0.027353 \n",
"averageViewPercentage 0.122071 0.072476 \n",
"cardClickRate 0.178478 0.220629 \n",
"cardTeaserClickRate 0.015473 0.021930 \n",
"cardImpressions NaN NaN \n",
"cardTeaserImpressions NaN NaN \n",
"cardClicks NaN NaN \n",
"cardTeaserClicks NaN NaN \n",
"subscribersGained 0.392459 0.210472 \n",
"subscribersLost 0.385036 0.219306 \n",
"monetizedPlaybacks 0.492794 0.285063 \n",
"playbackBasedCpm -0.001853 -0.001227 \n",
"adImpressions 0.493686 0.287363 \n",
"cpm -0.002880 -0.001876 \n",
"length -0.044392 -0.026338 \n",
"CumulativeSubscribers 0.370041 0.196635 \n",
"numOfKeywords 0.011872 -0.019450 \n",
"daysFromPublishDateToDataRetrieval -0.133061 -0.077111 \n",
"\n",
" cardTeaserClicks subscribersGained \\\n",
"grossRevenue 0.227961 NaN \n",
"views 0.213413 NaN \n",
"redViews 0.177021 NaN \n",
"comments 0.153278 NaN \n",
"likes 0.250792 NaN \n",
"dislikes 0.162012 NaN \n",
"shares 0.211005 NaN \n",
"videosAddedToPlaylists 0.231880 NaN \n",
"videosRemovedFromPlaylists 0.214833 NaN \n",
"estimatedMinutesWatched 0.186930 NaN \n",
"estimatedRedMinutesWatched 0.155724 NaN \n",
"averageViewDuration 0.029724 0.074358 \n",
"averageViewPercentage 0.067598 0.099669 \n",
"cardClickRate 0.077180 0.119489 \n",
"cardTeaserClickRate 0.033766 0.001041 \n",
"cardImpressions NaN 0.106659 \n",
"cardTeaserImpressions NaN 0.392459 \n",
"cardClicks NaN 0.210472 \n",
"cardTeaserClicks NaN 0.123339 \n",
"subscribersGained 0.123339 NaN \n",
"subscribersLost 0.181318 NaN \n",
"monetizedPlaybacks 0.219689 NaN \n",
"playbackBasedCpm -0.000589 -0.002816 \n",
"adImpressions 0.229567 NaN \n",
"cpm -0.001398 -0.003587 \n",
"length -0.020276 -0.008002 \n",
"CumulativeSubscribers 0.107759 NaN \n",
"numOfKeywords -0.048063 0.038908 \n",
"daysFromPublishDateToDataRetrieval -0.070724 -0.137026 \n",
"\n",
" subscribersLost monetizedPlaybacks \\\n",
"grossRevenue NaN NaN \n",
"views NaN NaN \n",
"redViews NaN NaN \n",
"comments NaN NaN \n",
"likes NaN NaN \n",
"dislikes NaN NaN \n",
"shares NaN NaN \n",
"videosAddedToPlaylists NaN NaN \n",
"videosRemovedFromPlaylists NaN NaN \n",
"estimatedMinutesWatched NaN NaN \n",
"estimatedRedMinutesWatched NaN NaN \n",
"averageViewDuration 0.178998 0.150762 \n",
"averageViewPercentage 0.143862 0.191253 \n",
"cardClickRate 0.186541 0.252843 \n",
"cardTeaserClickRate 0.008124 0.004603 \n",
"cardImpressions 0.128722 0.180089 \n",
"cardTeaserImpressions 0.385036 0.492794 \n",
"cardClicks 0.219306 0.285063 \n",
"cardTeaserClicks 0.181318 0.219689 \n",
"subscribersGained NaN NaN \n",
"subscribersLost NaN NaN \n",
"monetizedPlaybacks NaN NaN \n",
"playbackBasedCpm -0.003617 -0.004319 \n",
"adImpressions NaN NaN \n",
"cpm -0.004993 -0.006174 \n",
"length 0.039117 -0.017044 \n",
"CumulativeSubscribers NaN NaN \n",
"numOfKeywords 0.029166 0.079234 \n",
"daysFromPublishDateToDataRetrieval -0.221032 -0.247356 \n",
"\n",
" playbackBasedCpm adImpressions cpm \\\n",
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"views -0.004962 NaN -0.006601 \n",
"redViews -0.004773 NaN -0.006399 \n",
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"dislikes -0.003291 NaN -0.004600 \n",
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"videosAddedToPlaylists -0.004878 NaN -0.006848 \n",
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"estimatedMinutesWatched -0.003422 NaN -0.005394 \n",
"estimatedRedMinutesWatched -0.003273 NaN -0.005243 \n",
"averageViewDuration 0.014082 0.158249 0.002278 \n",
"averageViewPercentage 0.009781 0.188716 0.000798 \n",
"cardClickRate -0.001994 0.247798 -0.002400 \n",
"cardTeaserClickRate 0.000179 0.004922 -0.000167 \n",
"cardImpressions -0.000714 0.188038 -0.001361 \n",
"cardTeaserImpressions -0.001853 0.493686 -0.002880 \n",
"cardClicks -0.001227 0.287363 -0.001876 \n",
"cardTeaserClicks -0.000589 0.229567 -0.001398 \n",
"subscribersGained -0.002816 NaN -0.003587 \n",
"subscribersLost -0.003617 NaN -0.004993 \n",
"monetizedPlaybacks -0.004319 NaN -0.006174 \n",
"playbackBasedCpm NaN -0.003737 NaN \n",
"adImpressions -0.003737 NaN -0.005816 \n",
"cpm NaN -0.005816 NaN \n",
"length 0.002479 -0.011038 -0.000266 \n",
"CumulativeSubscribers -0.002534 NaN -0.003174 \n",
"numOfKeywords -0.009037 0.073536 -0.011508 \n",
"daysFromPublishDateToDataRetrieval -0.010301 -0.247062 -0.007628 \n",
"\n",
" length CumulativeSubscribers \\\n",
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"views -0.024462 NaN \n",
"redViews -0.011914 NaN \n",
"comments 0.018493 NaN \n",
"likes -0.002401 0.487780 \n",
"dislikes 0.016640 NaN \n",
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"averageViewPercentage -0.304512 0.087455 \n",
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"cardTeaserImpressions -0.044392 0.370041 \n",
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"cardTeaserClicks -0.020276 0.107759 \n",
"subscribersGained -0.008002 NaN \n",
"subscribersLost 0.039117 NaN \n",
"monetizedPlaybacks -0.017044 NaN \n",
"playbackBasedCpm 0.002479 -0.002534 \n",
"adImpressions -0.011038 NaN \n",
"cpm -0.000266 -0.003174 \n",
"length NaN -0.014192 \n",
"CumulativeSubscribers -0.014192 NaN \n",
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"\n",
" numOfKeywords \\\n",
"grossRevenue 0.047816 \n",
"views 0.075308 \n",
"redViews 0.101310 \n",
"comments 0.040434 \n",
"likes 0.050279 \n",
"dislikes 0.011417 \n",
"shares 0.018316 \n",
"videosAddedToPlaylists 0.057401 \n",
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"estimatedRedMinutesWatched 0.086425 \n",
"averageViewDuration 0.014823 \n",
"averageViewPercentage -0.057517 \n",
"cardClickRate 0.045941 \n",
"cardTeaserClickRate -0.014791 \n",
"cardImpressions -0.033079 \n",
"cardTeaserImpressions 0.011872 \n",
"cardClicks -0.019450 \n",
"cardTeaserClicks -0.048063 \n",
"subscribersGained 0.038908 \n",
"subscribersLost 0.029166 \n",
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"length -0.008243 \n",
"CumulativeSubscribers 0.037960 \n",
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"comments -0.205367 \n",
"likes -0.270249 \n",
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"videosAddedToPlaylists -0.281510 \n",
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"estimatedRedMinutesWatched -0.240034 \n",
"averageViewDuration -0.069899 \n",
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"cardClickRate -0.096285 \n",
"cardTeaserClickRate -0.020204 \n",
"cardImpressions -0.054258 \n",
"cardTeaserImpressions -0.133061 \n",
"cardClicks -0.077111 \n",
"cardTeaserClicks -0.070724 \n",
"subscribersGained -0.137026 \n",
"subscribersLost -0.221032 \n",
"monetizedPlaybacks -0.247356 \n",
"playbackBasedCpm -0.010301 \n",
"adImpressions -0.247062 \n",
"cpm -0.007628 \n",
"length 0.065624 \n",
"CumulativeSubscribers -0.116944 \n",
"numOfKeywords -0.134546 \n",
"daysFromPublishDateToDataRetrieval NaN "
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" <td>0.040434</td>\n",
" <td>-0.205367</td>\n",
" </tr>\n",
" <tr>\n",
" <th>likes</th>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>0.182742</td>\n",
" <td>0.209009</td>\n",
" <td>0.258220</td>\n",
" <td>0.006603</td>\n",
" <td>0.200442</td>\n",
" <td>0.446746</td>\n",
" <td>0.276990</td>\n",
" <td>0.250792</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>-0.004530</td>\n",
" <td>NaN</td>\n",
" <td>-0.006517</td>\n",
" <td>-0.002401</td>\n",
" <td>0.487780</td>\n",
" <td>0.050279</td>\n",
" <td>-0.270249</td>\n",
" </tr>\n",
" <tr>\n",
" <th>dislikes</th>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>0.141513</td>\n",
" <td>0.158386</td>\n",
" <td>0.161316</td>\n",
" <td>0.003484</td>\n",
" <td>0.127363</td>\n",
" <td>0.334572</td>\n",
" <td>0.198537</td>\n",
" <td>0.162012</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>-0.003291</td>\n",
" <td>NaN</td>\n",
" <td>-0.004600</td>\n",
" <td>0.016640</td>\n",
" <td>NaN</td>\n",
" <td>0.011417</td>\n",
" <td>-0.193743</td>\n",
" </tr>\n",
" <tr>\n",
" <th>shares</th>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>0.159831</td>\n",
" <td>0.178684</td>\n",
" <td>0.197961</td>\n",
" <td>0.005111</td>\n",
" <td>0.166836</td>\n",
" <td>0.386598</td>\n",
" <td>0.242974</td>\n",
" <td>0.211005</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>-0.004070</td>\n",
" <td>NaN</td>\n",
" <td>-0.005744</td>\n",
" <td>0.003760</td>\n",
" <td>NaN</td>\n",
" <td>0.018316</td>\n",
" <td>-0.224304</td>\n",
" </tr>\n",
" <tr>\n",
" <th>videosAddedToPlaylists</th>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>0.174700</td>\n",
" <td>0.220386</td>\n",
" <td>0.257608</td>\n",
" <td>0.005686</td>\n",
" <td>0.185523</td>\n",
" <td>0.462071</td>\n",
" <td>0.273353</td>\n",
" <td>0.231880</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>-0.004878</td>\n",
" <td>NaN</td>\n",
" <td>-0.006848</td>\n",
" <td>-0.016498</td>\n",
" <td>NaN</td>\n",
" <td>0.057401</td>\n",
" <td>-0.281510</td>\n",
" </tr>\n",
" <tr>\n",
" <th>videosRemovedFromPlaylists</th>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>0.162834</td>\n",
" <td>0.231090</td>\n",
" <td>0.275452</td>\n",
" <td>0.006030</td>\n",
" <td>0.173274</td>\n",
" <td>0.460810</td>\n",
" <td>0.261907</td>\n",
" <td>0.214833</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>-0.005717</td>\n",
" <td>NaN</td>\n",
" <td>-0.007652</td>\n",
" <td>-0.034579</td>\n",
" <td>0.497482</td>\n",
" <td>0.093345</td>\n",
" <td>-0.310708</td>\n",
" </tr>\n",
" <tr>\n",
" <th>estimatedMinutesWatched</th>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>0.233865</td>\n",
" <td>0.151279</td>\n",
" <td>0.218201</td>\n",
" <td>0.003903</td>\n",
" <td>0.148387</td>\n",
" <td>0.422584</td>\n",
" <td>0.240840</td>\n",
" <td>0.186930</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>-0.003422</td>\n",
" <td>NaN</td>\n",
" <td>-0.005394</td>\n",
" <td>0.071267</td>\n",
" <td>NaN</td>\n",
" <td>0.062330</td>\n",
" <td>-0.240485</td>\n",
" </tr>\n",
" <tr>\n",
" <th>estimatedRedMinutesWatched</th>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>0.242988</td>\n",
" <td>0.139952</td>\n",
" <td>0.213680</td>\n",
" <td>0.004051</td>\n",
" <td>0.119147</td>\n",
" <td>0.398343</td>\n",
" <td>0.212446</td>\n",
" <td>0.155724</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>-0.003273</td>\n",
" <td>NaN</td>\n",
" <td>-0.005243</td>\n",
" <td>0.087878</td>\n",
" <td>NaN</td>\n",
" <td>0.086425</td>\n",
" <td>-0.240034</td>\n",
" </tr>\n",
" <tr>\n",
" <th>averageViewDuration</th>\n",
" <td>0.169409</td>\n",
" <td>0.131921</td>\n",
" <td>0.142872</td>\n",
" <td>0.142968</td>\n",
" <td>0.182742</td>\n",
" <td>0.141513</td>\n",
" <td>0.159831</td>\n",
" <td>0.174700</td>\n",
" <td>0.162834</td>\n",
" <td>0.233865</td>\n",
" <td>0.242988</td>\n",
" <td>NaN</td>\n",
" <td>0.438359</td>\n",
" <td>0.041112</td>\n",
" <td>-0.001747</td>\n",
" <td>0.017892</td>\n",
" <td>0.049550</td>\n",
" <td>0.027353</td>\n",
" <td>0.029724</td>\n",
" <td>0.074358</td>\n",
" <td>0.178998</td>\n",
" <td>0.150762</td>\n",
" <td>0.014082</td>\n",
" <td>0.158249</td>\n",
" <td>0.002278</td>\n",
" <td>0.430214</td>\n",
" <td>0.055104</td>\n",
" <td>0.014823</td>\n",
" <td>-0.069899</td>\n",
" </tr>\n",
" <tr>\n",
" <th>averageViewPercentage</th>\n",
" <td>0.186656</td>\n",
" <td>0.195644</td>\n",
" <td>0.191271</td>\n",
" <td>0.147946</td>\n",
" <td>0.209009</td>\n",
" <td>0.158386</td>\n",
" <td>0.178684</td>\n",
" <td>0.220386</td>\n",
" <td>0.231090</td>\n",
" <td>0.151279</td>\n",
" <td>0.139952</td>\n",
" <td>0.438359</td>\n",
" <td>NaN</td>\n",
" <td>0.079032</td>\n",
" <td>0.003068</td>\n",
" <td>0.053690</td>\n",
" <td>0.122071</td>\n",
" <td>0.072476</td>\n",
" <td>0.067598</td>\n",
" <td>0.099669</td>\n",
" <td>0.143862</td>\n",
" <td>0.191253</td>\n",
" <td>0.009781</td>\n",
" <td>0.188716</td>\n",
" <td>0.000798</td>\n",
" <td>-0.304512</td>\n",
" <td>0.087455</td>\n",
" <td>-0.057517</td>\n",
" <td>-0.072863</td>\n",
" </tr>\n",
" <tr>\n",
" <th>cardClickRate</th>\n",
" <td>0.241542</td>\n",
" <td>0.237707</td>\n",
" <td>0.236057</td>\n",
" <td>0.166525</td>\n",
" <td>0.258220</td>\n",
" <td>0.161316</td>\n",
" <td>0.197961</td>\n",
" <td>0.257608</td>\n",
" <td>0.275452</td>\n",
" <td>0.218201</td>\n",
" <td>0.213680</td>\n",
" <td>0.041112</td>\n",
" <td>0.079032</td>\n",
" <td>NaN</td>\n",
" <td>0.049340</td>\n",
" <td>0.048261</td>\n",
" <td>0.178478</td>\n",
" <td>0.220629</td>\n",
" <td>0.077180</td>\n",
" <td>0.119489</td>\n",
" <td>0.186541</td>\n",
" <td>0.252843</td>\n",
" <td>-0.001994</td>\n",
" <td>0.247798</td>\n",
" <td>-0.002400</td>\n",
" <td>-0.023350</td>\n",
" <td>0.102855</td>\n",
" <td>0.045941</td>\n",
" <td>-0.096285</td>\n",
" </tr>\n",
" <tr>\n",
" <th>cardTeaserClickRate</th>\n",
" <td>0.005648</td>\n",
" <td>0.004142</td>\n",
" <td>0.004152</td>\n",
" <td>0.004886</td>\n",
" <td>0.006603</td>\n",
" <td>0.003484</td>\n",
" <td>0.005111</td>\n",
" <td>0.005686</td>\n",
" <td>0.006030</td>\n",
" <td>0.003903</td>\n",
" <td>0.004051</td>\n",
" <td>-0.001747</td>\n",
" <td>0.003068</td>\n",
" <td>0.049340</td>\n",
" <td>NaN</td>\n",
" <td>0.019680</td>\n",
" <td>0.015473</td>\n",
" <td>0.021930</td>\n",
" <td>0.033766</td>\n",
" <td>0.001041</td>\n",
" <td>0.008124</td>\n",
" <td>0.004603</td>\n",
" <td>0.000179</td>\n",
" <td>0.004922</td>\n",
" <td>-0.000167</td>\n",
" <td>-0.004168</td>\n",
" <td>-0.000024</td>\n",
" <td>-0.014791</td>\n",
" <td>-0.020204</td>\n",
" </tr>\n",
" <tr>\n",
" <th>cardImpressions</th>\n",
" <td>0.180609</td>\n",
" <td>0.177861</td>\n",
" <td>0.143633</td>\n",
" <td>0.116571</td>\n",
" <td>0.200442</td>\n",
" <td>0.127363</td>\n",
" <td>0.166836</td>\n",
" <td>0.185523</td>\n",
" <td>0.173274</td>\n",
" <td>0.148387</td>\n",
" <td>0.119147</td>\n",
" <td>0.017892</td>\n",
" <td>0.053690</td>\n",
" <td>0.048261</td>\n",
" <td>0.019680</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>0.106659</td>\n",
" <td>0.128722</td>\n",
" <td>0.180089</td>\n",
" <td>-0.000714</td>\n",
" <td>0.188038</td>\n",
" <td>-0.001361</td>\n",
" <td>-0.020296</td>\n",
" <td>0.097159</td>\n",
" <td>-0.033079</td>\n",
" <td>-0.054258</td>\n",
" </tr>\n",
" <tr>\n",
" <th>cardTeaserImpressions</th>\n",
" <td>0.487047</td>\n",
" <td>0.492966</td>\n",
" <td>0.481286</td>\n",
" <td>0.363252</td>\n",
" <td>0.446746</td>\n",
" <td>0.334572</td>\n",
" <td>0.386598</td>\n",
" <td>0.462071</td>\n",
" <td>0.460810</td>\n",
" <td>0.422584</td>\n",
" <td>0.398343</td>\n",
" <td>0.049550</td>\n",
" <td>0.122071</td>\n",
" <td>0.178478</td>\n",
" <td>0.015473</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>0.392459</td>\n",
" <td>0.385036</td>\n",
" <td>0.492794</td>\n",
" <td>-0.001853</td>\n",
" <td>0.493686</td>\n",
" <td>-0.002880</td>\n",
" <td>-0.044392</td>\n",
" <td>0.370041</td>\n",
" <td>0.011872</td>\n",
" <td>-0.133061</td>\n",
" </tr>\n",
" <tr>\n",
" <th>cardClicks</th>\n",
" <td>0.278366</td>\n",
" <td>0.286460</td>\n",
" <td>0.259902</td>\n",
" <td>0.203246</td>\n",
" <td>0.276990</td>\n",
" <td>0.198537</td>\n",
" <td>0.242974</td>\n",
" <td>0.273353</td>\n",
" <td>0.261907</td>\n",
" <td>0.240840</td>\n",
" <td>0.212446</td>\n",
" <td>0.027353</td>\n",
" <td>0.072476</td>\n",
" <td>0.220629</td>\n",
" <td>0.021930</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>0.210472</td>\n",
" <td>0.219306</td>\n",
" <td>0.285063</td>\n",
" <td>-0.001227</td>\n",
" <td>0.287363</td>\n",
" <td>-0.001876</td>\n",
" <td>-0.026338</td>\n",
" <td>0.196635</td>\n",
" <td>-0.019450</td>\n",
" <td>-0.077111</td>\n",
" </tr>\n",
" <tr>\n",
" <th>cardTeaserClicks</th>\n",
" <td>0.227961</td>\n",
" <td>0.213413</td>\n",
" <td>0.177021</td>\n",
" <td>0.153278</td>\n",
" <td>0.250792</td>\n",
" <td>0.162012</td>\n",
" <td>0.211005</td>\n",
" <td>0.231880</td>\n",
" <td>0.214833</td>\n",
" <td>0.186930</td>\n",
" <td>0.155724</td>\n",
" <td>0.029724</td>\n",
" <td>0.067598</td>\n",
" <td>0.077180</td>\n",
" <td>0.033766</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>0.123339</td>\n",
" <td>0.181318</td>\n",
" <td>0.219689</td>\n",
" <td>-0.000589</td>\n",
" <td>0.229567</td>\n",
" <td>-0.001398</td>\n",
" <td>-0.020276</td>\n",
" <td>0.107759</td>\n",
" <td>-0.048063</td>\n",
" <td>-0.070724</td>\n",
" </tr>\n",
" <tr>\n",
" <th>subscribersGained</th>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>0.074358</td>\n",
" <td>0.099669</td>\n",
" <td>0.119489</td>\n",
" <td>0.001041</td>\n",
" <td>0.106659</td>\n",
" <td>0.392459</td>\n",
" <td>0.210472</td>\n",
" <td>0.123339</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>-0.002816</td>\n",
" <td>NaN</td>\n",
" <td>-0.003587</td>\n",
" <td>-0.008002</td>\n",
" <td>NaN</td>\n",
" <td>0.038908</td>\n",
" <td>-0.137026</td>\n",
" </tr>\n",
" <tr>\n",
" <th>subscribersLost</th>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>0.178998</td>\n",
" <td>0.143862</td>\n",
" <td>0.186541</td>\n",
" <td>0.008124</td>\n",
" <td>0.128722</td>\n",
" <td>0.385036</td>\n",
" <td>0.219306</td>\n",
" <td>0.181318</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>-0.003617</td>\n",
" <td>NaN</td>\n",
" <td>-0.004993</td>\n",
" <td>0.039117</td>\n",
" <td>NaN</td>\n",
" <td>0.029166</td>\n",
" <td>-0.221032</td>\n",
" </tr>\n",
" <tr>\n",
" <th>monetizedPlaybacks</th>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>0.150762</td>\n",
" <td>0.191253</td>\n",
" <td>0.252843</td>\n",
" <td>0.004603</td>\n",
" <td>0.180089</td>\n",
" <td>0.492794</td>\n",
" <td>0.285063</td>\n",
" <td>0.219689</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>-0.004319</td>\n",
" <td>NaN</td>\n",
" <td>-0.006174</td>\n",
" <td>-0.017044</td>\n",
" <td>NaN</td>\n",
" <td>0.079234</td>\n",
" <td>-0.247356</td>\n",
" </tr>\n",
" <tr>\n",
" <th>playbackBasedCpm</th>\n",
" <td>-0.000306</td>\n",
" <td>-0.004962</td>\n",
" <td>-0.004773</td>\n",
" <td>-0.003673</td>\n",
" <td>-0.004530</td>\n",
" <td>-0.003291</td>\n",
" <td>-0.004070</td>\n",
" <td>-0.004878</td>\n",
" <td>-0.005717</td>\n",
" <td>-0.003422</td>\n",
" <td>-0.003273</td>\n",
" <td>0.014082</td>\n",
" <td>0.009781</td>\n",
" <td>-0.001994</td>\n",
" <td>0.000179</td>\n",
" <td>-0.000714</td>\n",
" <td>-0.001853</td>\n",
" <td>-0.001227</td>\n",
" <td>-0.000589</td>\n",
" <td>-0.002816</td>\n",
" <td>-0.003617</td>\n",
" <td>-0.004319</td>\n",
" <td>NaN</td>\n",
" <td>-0.003737</td>\n",
" <td>NaN</td>\n",
" <td>0.002479</td>\n",
" <td>-0.002534</td>\n",
" <td>-0.009037</td>\n",
" <td>-0.010301</td>\n",
" </tr>\n",
" <tr>\n",
" <th>adImpressions</th>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>0.158249</td>\n",
" <td>0.188716</td>\n",
" <td>0.247798</td>\n",
" <td>0.004922</td>\n",
" <td>0.188038</td>\n",
" <td>0.493686</td>\n",
" <td>0.287363</td>\n",
" <td>0.229567</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>-0.003737</td>\n",
" <td>NaN</td>\n",
" <td>-0.005816</td>\n",
" <td>-0.011038</td>\n",
" <td>NaN</td>\n",
" <td>0.073536</td>\n",
" <td>-0.247062</td>\n",
" </tr>\n",
" <tr>\n",
" <th>cpm</th>\n",
" <td>-0.002446</td>\n",
" <td>-0.006601</td>\n",
" <td>-0.006399</td>\n",
" <td>-0.005035</td>\n",
" <td>-0.006517</td>\n",
" <td>-0.004600</td>\n",
" <td>-0.005744</td>\n",
" <td>-0.006848</td>\n",
" <td>-0.007652</td>\n",
" <td>-0.005394</td>\n",
" <td>-0.005243</td>\n",
" <td>0.002278</td>\n",
" <td>0.000798</td>\n",
" <td>-0.002400</td>\n",
" <td>-0.000167</td>\n",
" <td>-0.001361</td>\n",
" <td>-0.002880</td>\n",
" <td>-0.001876</td>\n",
" <td>-0.001398</td>\n",
" <td>-0.003587</td>\n",
" <td>-0.004993</td>\n",
" <td>-0.006174</td>\n",
" <td>NaN</td>\n",
" <td>-0.005816</td>\n",
" <td>NaN</td>\n",
" <td>-0.000266</td>\n",
" <td>-0.003174</td>\n",
" <td>-0.011508</td>\n",
" <td>-0.007628</td>\n",
" </tr>\n",
" <tr>\n",
" <th>length</th>\n",
" <td>-0.002389</td>\n",
" <td>-0.024462</td>\n",
" <td>-0.011914</td>\n",
" <td>0.018493</td>\n",
" <td>-0.002401</td>\n",
" <td>0.016640</td>\n",
" <td>0.003760</td>\n",
" <td>-0.016498</td>\n",
" <td>-0.034579</td>\n",
" <td>0.071267</td>\n",
" <td>0.087878</td>\n",
" <td>0.430214</td>\n",
" <td>-0.304512</td>\n",
" <td>-0.023350</td>\n",
" <td>-0.004168</td>\n",
" <td>-0.020296</td>\n",
" <td>-0.044392</td>\n",
" <td>-0.026338</td>\n",
" <td>-0.020276</td>\n",
" <td>-0.008002</td>\n",
" <td>0.039117</td>\n",
" <td>-0.017044</td>\n",
" <td>0.002479</td>\n",
" <td>-0.011038</td>\n",
" <td>-0.000266</td>\n",
" <td>NaN</td>\n",
" <td>-0.014192</td>\n",
" <td>-0.008243</td>\n",
" <td>0.065624</td>\n",
" </tr>\n",
" <tr>\n",
" <th>CumulativeSubscribers</th>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>0.487780</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>0.497482</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>0.055104</td>\n",
" <td>0.087455</td>\n",
" <td>0.102855</td>\n",
" <td>-0.000024</td>\n",
" <td>0.097159</td>\n",
" <td>0.370041</td>\n",
" <td>0.196635</td>\n",
" <td>0.107759</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>-0.002534</td>\n",
" <td>NaN</td>\n",
" <td>-0.003174</td>\n",
" <td>-0.014192</td>\n",
" <td>NaN</td>\n",
" <td>0.037960</td>\n",
" <td>-0.116944</td>\n",
" </tr>\n",
" <tr>\n",
" <th>numOfKeywords</th>\n",
" <td>0.047816</td>\n",
" <td>0.075308</td>\n",
" <td>0.101310</td>\n",
" <td>0.040434</td>\n",
" <td>0.050279</td>\n",
" <td>0.011417</td>\n",
" <td>0.018316</td>\n",
" <td>0.057401</td>\n",
" <td>0.093345</td>\n",
" <td>0.062330</td>\n",
" <td>0.086425</td>\n",
" <td>0.014823</td>\n",
" <td>-0.057517</td>\n",
" <td>0.045941</td>\n",
" <td>-0.014791</td>\n",
" <td>-0.033079</td>\n",
" <td>0.011872</td>\n",
" <td>-0.019450</td>\n",
" <td>-0.048063</td>\n",
" <td>0.038908</td>\n",
" <td>0.029166</td>\n",
" <td>0.079234</td>\n",
" <td>-0.009037</td>\n",
" <td>0.073536</td>\n",
" <td>-0.011508</td>\n",
" <td>-0.008243</td>\n",
" <td>0.037960</td>\n",
" <td>NaN</td>\n",
" <td>-0.134546</td>\n",
" </tr>\n",
" <tr>\n",
" <th>daysFromPublishDateToDataRetrieval</th>\n",
" <td>-0.247163</td>\n",
" <td>-0.243247</td>\n",
" <td>-0.243733</td>\n",
" <td>-0.205367</td>\n",
" <td>-0.270249</td>\n",
" <td>-0.193743</td>\n",
" <td>-0.224304</td>\n",
" <td>-0.281510</td>\n",
" <td>-0.310708</td>\n",
" <td>-0.240485</td>\n",
" <td>-0.240034</td>\n",
" <td>-0.069899</td>\n",
" <td>-0.072863</td>\n",
" <td>-0.096285</td>\n",
" <td>-0.020204</td>\n",
" <td>-0.054258</td>\n",
" <td>-0.133061</td>\n",
" <td>-0.077111</td>\n",
" <td>-0.070724</td>\n",
" <td>-0.137026</td>\n",
" <td>-0.221032</td>\n",
" <td>-0.247356</td>\n",
" <td>-0.010301</td>\n",
" <td>-0.247062</td>\n",
" <td>-0.007628</td>\n",
" <td>0.065624</td>\n",
" <td>-0.116944</td>\n",
" <td>-0.134546</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>\n",
" <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-674f1f44-77f8-4205-86cf-6f61e8e693c8')\"\n",
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" [theme=dark] .colab-df-convert {\n",
" background-color: #3B4455;\n",
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"\n",
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" background-color: #434B5C;\n",
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" <script>\n",
" const buttonEl =\n",
" document.querySelector('#df-674f1f44-77f8-4205-86cf-6f61e8e693c8 button.colab-df-convert');\n",
" buttonEl.style.display =\n",
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"\n",
" async function convertToInteractive(key) {\n",
" const element = document.querySelector('#df-674f1f44-77f8-4205-86cf-6f61e8e693c8');\n",
" const dataTable =\n",
" await google.colab.kernel.invokeFunction('convertToInteractive',\n",
" [key], {});\n",
" if (!dataTable) return;\n",
"\n",
" const docLinkHtml = 'Like what you see? Visit the ' +\n",
" '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
" + ' to learn more about interactive tables.';\n",
" element.innerHTML = '';\n",
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" docLink.innerHTML = docLinkHtml;\n",
" element.appendChild(docLink);\n",
" }\n",
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" "
]
},
"metadata": {},
"execution_count": 155
}
],
"source": [
"corr_df = num_df.corr()\n",
"test_corr_df = corr_df[corr_df<0.5]\n",
"test_corr_df"
]
},
{
"cell_type": "code",
"source": [
"# Drop Columns with <0.5 corr with dependent variable (grossRevenue)\n",
"# variables dropped: playbackBasedCpm, averageViewDuration, averageViewPercentage, \n",
"# cardClickRate, cardTeaserClickRate, cardImpressions, cardTeaserImpressions, cardClicks, cardTeaserClicks,\n",
"# playbackBasedCpm, cpm, length, numOfKeywords, daysFromPublishDateToDataRetrieval\n",
"\n",
"df.drop([\"averageViewDuration\", \"averageViewPercentage\", \n",
"\"cardClickRate\", \"cardTeaserClickRate\", \"cardImpressions\", \"cardTeaserImpressions\", \"cardClicks\", \"cardTeaserClicks\",\n",
"\"playbackBasedCpm\", \"cpm\", \"length\", \"numOfKeywords\", \"daysFromPublishDateToDataRetrieval\"], axis=1, inplace=True, errors='ignore')"
],
"metadata": {
"id": "vEPZdpRgrXUh"
},
"execution_count": null,
"outputs": []
},
{
"cell_type": "markdown",
"source": [
"## Add Dummy Variables for Channels"
],
"metadata": {
"id": "Ik3RpsVhs_gx"
}
},
{
"cell_type": "code",
"source": [
"# Make sure there are only 4 channels\n",
"len(np.where(df['Channel'] == 4, 1, 0)) == len(np.where(df['Channel'] == 3, 1, 0)) == len(np.where(df['Channel'] == 2, 1, 0)) == len(np.where(df['Channel'] == 1, 1, 0))"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "8d6pS1wItLYT",
"outputId": "1e771fc6-77d2-4c7f-bb15-b55dd2cbd56b"
},
"execution_count": null,
"outputs": [
{
"output_type": "execute_result",
"data": {
"text/plain": [
"True"
]
},
"metadata": {},
"execution_count": 157
}
]
},
{
"cell_type": "code",
"source": [
"df['Channel1'] = np.where(df['Channel'] == 1, 1, 0)\n",
"df['Channel2'] = np.where(df['Channel'] == 2, 1, 0)\n",
"df['Channel3'] = np.where(df['Channel'] == 3, 1, 0)\n",
"df['Channel4'] = np.where(df['Channel'] == 4, 1, 0)"
],
"metadata": {
"id": "lElMgxCrtEN7"
},
"execution_count": null,
"outputs": []
},
{
"cell_type": "markdown",
"source": [
"## Drop Monetized Playbacks"
],
"metadata": {
"id": "hJqmMeCEAC_X"
}
},
{
"cell_type": "markdown",
"source": [
"'monetizedPlaybacks' was dropped because it's not as accurate as adImpressions (they're basically the same thing but 'adImpressions' is better)\n",
"\n",
"See example from Google: \"If your video is viewed 10 times, and 8 of those views contained ads, you would have 10 views and 8 estimated monetized playbacks. If one of those estimated monetized playbacks actually had 2 ads, you would have 9 ad impressions.\""
],
"metadata": {
"id": "qZfkGICNAGPv"
}
},
{
"cell_type": "code",
"source": [
"df.drop([\"monetizedPlaybacks\"], axis=1, inplace=True, errors='ignore')"
],
"metadata": {
"id": "WHig_SfZACbe"
},
"execution_count": null,
"outputs": []
},
{
"cell_type": "code",
"source": [
"df.columns"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "_qUj1qcqAQ0J",
"outputId": "f96fb453-29ce-4bb0-c1ab-8f3c1693c2b4"
},
"execution_count": null,
"outputs": [
{
"output_type": "execute_result",
"data": {
"text/plain": [
"Index(['grossRevenue', 'views', 'redViews', 'comments', 'likes', 'dislikes',\n",
" 'shares', 'videosAddedToPlaylists', 'videosRemovedFromPlaylists',\n",
" 'estimatedMinutesWatched', 'estimatedRedMinutesWatched',\n",
" 'subscribersGained', 'subscribersLost', 'adImpressions',\n",
" 'CumulativeSubscribers', 'Channel', 'PlaylistCategory', 'Channel1',\n",
" 'Channel2', 'Channel3', 'Channel4'],\n",
" dtype='object')"
]
},
"metadata": {},
"execution_count": 164
}
]
},
{
"cell_type": "markdown",
"source": [
"## Combine views & redViews"
],
"metadata": {
"id": "QpIF1RPNR5Of"
}
},
{
"cell_type": "code",
"source": [
"df['totalViews'] = df['views'] + df['redViews']"
],
"metadata": {
"id": "FcayFC-9R4pi"
},
"execution_count": null,
"outputs": []
},
{
"cell_type": "code",
"source": [
"df.drop(['views', 'redViews'], axis=1,inplace=True, errors='ignore')"
],
"metadata": {
"id": "8M-zooMDSNnK"
},
"execution_count": null,
"outputs": []
},
{
"cell_type": "markdown",
"source": [
"## Combine estimatedRedMinutesWatched & estimatedMinutesWatched"
],
"metadata": {
"id": "LEQvvFOzSAmX"
}
},
{
"cell_type": "code",
"source": [
"df['estimatedTotalMinutesWatched'] = df['estimatedMinutesWatched'] + df['estimatedRedMinutesWatched']"
],
"metadata": {
"id": "puXEmvaMSTGw"
},
"execution_count": null,
"outputs": []
},
{
"cell_type": "code",
"source": [
"df.drop(['estimatedMinutesWatched', 'estimatedRedMinutesWatched'], axis=1,inplace=True, errors='ignore')"
],
"metadata": {
"id": "g72irYlNSANH"
},
"execution_count": null,
"outputs": []
},
{
"cell_type": "markdown",
"source": [
"# Save to CSV"
],
"metadata": {
"id": "tbgQVqqJtAxW"
}
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"id": "Tngg-wgsqqi2"
},
"outputs": [],
"source": [
"df.reset_index(drop=True, inplace=True)\n",
"df.to_csv(\"FinalCleanedData.csv\", index=False)"
]
},
{
"cell_type": "markdown",
"source": [
"# Read CSV"
],
"metadata": {
"id": "Lll6Q3w67DTX"
}
},
{
"cell_type": "code",
"source": [
"df = pd.read_csv('FinalCleanedData.csv')\n",
"df.sample(n=5)"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
"height": 270
},
"id": "0uKAD-7QfTtT",
"outputId": "22daca38-3904-46ab-db70-decdc451a490"
},
"execution_count": null,
"outputs": [
{
"output_type": "execute_result",
"data": {
"text/plain": [
" grossRevenue comments likes dislikes shares \\\n",
"38752 0.008 0.0 0.22 0.0 0.0 \n",
"29083 0.003 0.0 0.00 0.0 0.0 \n",
"1544 153.021 137.0 1371.00 12.0 124.0 \n",
"3665 2.366 1.0 7.11 0.0 2.0 \n",
"34809 528.442 44.0 3114.00 41.0 190.0 \n",
"\n",
" videosAddedToPlaylists videosRemovedFromPlaylists subscribersGained \\\n",
"38752 1.0 3.0 0.0 \n",
"29083 0.0 0.0 0.0 \n",
"1544 195.0 104.0 9.0 \n",
"3665 5.0 11.0 0.0 \n",
"34809 351.0 184.0 37.0 \n",
"\n",
" subscribersLost adImpressions CumulativeSubscribers \\\n",
"38752 0.0 1.0 0.0 \n",
"29083 0.0 2.0 0.0 \n",
"1544 3.0 27684.0 6.0 \n",
"3665 0.0 752.0 0.0 \n",
"34809 6.0 97850.0 31.0 \n",
"\n",
" PlaylistCategory Channel1 Channel2 Channel3 Channel4 totalViews \\\n",
"38752 19.0 0 1 0 0 4.0 \n",
"29083 15.0 0 1 0 0 2.0 \n",
"1544 45.0 1 0 0 0 20655.0 \n",
"3665 32.0 1 0 0 0 733.0 \n",
"34809 19.0 0 1 0 0 51624.0 \n",
"\n",
" estimatedTotalMinutesWatched Channel \n",
"38752 26.0 2 \n",
"29083 11.0 2 \n",
"1544 95039.0 1 \n",
"3665 3146.0 1 \n",
"34809 390742.0 2 "
],
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" <td>0.008</td>\n",
" <td>0.0</td>\n",
" <td>0.22</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>1.0</td>\n",
" <td>3.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>1.0</td>\n",
" <td>0.0</td>\n",
" <td>19.0</td>\n",
" <td>0</td>\n",
" <td>1</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>4.0</td>\n",
" <td>26.0</td>\n",
" <td>2</td>\n",
" </tr>\n",
" <tr>\n",
" <th>29083</th>\n",
" <td>0.003</td>\n",
" <td>0.0</td>\n",
" <td>0.00</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>2.0</td>\n",
" <td>0.0</td>\n",
" <td>15.0</td>\n",
" <td>0</td>\n",
" <td>1</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>2.0</td>\n",
" <td>11.0</td>\n",
" <td>2</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1544</th>\n",
" <td>153.021</td>\n",
" <td>137.0</td>\n",
" <td>1371.00</td>\n",
" <td>12.0</td>\n",
" <td>124.0</td>\n",
" <td>195.0</td>\n",
" <td>104.0</td>\n",
" <td>9.0</td>\n",
" <td>3.0</td>\n",
" <td>27684.0</td>\n",
" <td>6.0</td>\n",
" <td>45.0</td>\n",
" <td>1</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>20655.0</td>\n",
" <td>95039.0</td>\n",
" <td>1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3665</th>\n",
" <td>2.366</td>\n",
" <td>1.0</td>\n",
" <td>7.11</td>\n",
" <td>0.0</td>\n",
" <td>2.0</td>\n",
" <td>5.0</td>\n",
" <td>11.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>752.0</td>\n",
" <td>0.0</td>\n",
" <td>32.0</td>\n",
" <td>1</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>733.0</td>\n",
" <td>3146.0</td>\n",
" <td>1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>34809</th>\n",
" <td>528.442</td>\n",
" <td>44.0</td>\n",
" <td>3114.00</td>\n",
" <td>41.0</td>\n",
" <td>190.0</td>\n",
" <td>351.0</td>\n",
" <td>184.0</td>\n",
" <td>37.0</td>\n",
" <td>6.0</td>\n",
" <td>97850.0</td>\n",
" <td>31.0</td>\n",
" <td>19.0</td>\n",
" <td>0</td>\n",
" <td>1</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>51624.0</td>\n",
" <td>390742.0</td>\n",
" <td>2</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
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]
},
"metadata": {},
"execution_count": 84
}
]
},
{
"cell_type": "code",
"source": [
"unimputed_df = df #Fix later"
],
"metadata": {
"id": "Ms-5TCwDsbLs"
},
"execution_count": null,
"outputs": []
},
{
"cell_type": "markdown",
"source": [
"# EDA Pandas Profiling for Fully Cleaned Data"
],
"metadata": {
"id": "hcJokSWm7LZc"
}
},
{
"cell_type": "code",
"source": [
"profile = ProfileReport(df)\n",
"profile.to_file(\"fully-cleaned-df-report.html\")"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
"referenced_widgets": [
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},
"id": "GoqlWdET7Nwm",
"outputId": "be0f7775-4426-4271-c2c0-1ac42fa121c8"
},
"execution_count": null,
"outputs": [
{
"output_type": "display_data",
"data": {
"text/plain": [
"Summarize dataset: 0%| | 0/5 [00:00<?, ?it/s]"
],
"application/vnd.jupyter.widget-view+json": {
"version_major": 2,
"version_minor": 0,
"model_id": "4fe0357e74c64e57af494c3aec01ccef"
}
},
"metadata": {}
},
{
"output_type": "display_data",
"data": {
"text/plain": [
"Generate report structure: 0%| | 0/1 [00:00<?, ?it/s]"
],
"application/vnd.jupyter.widget-view+json": {
"version_major": 2,
"version_minor": 0,
"model_id": "3e00fe44eacc48eda35a1766256b93f3"
}
},
"metadata": {}
},
{
"output_type": "display_data",
"data": {
"text/plain": [
"Render HTML: 0%| | 0/1 [00:00<?, ?it/s]"
],
"application/vnd.jupyter.widget-view+json": {
"version_major": 2,
"version_minor": 0,
"model_id": "958a3cd40fa24a5780e4de63916afedc"
}
},
"metadata": {}
},
{
"output_type": "display_data",
"data": {
"text/plain": [
"Export report to file: 0%| | 0/1 [00:00<?, ?it/s]"
],
"application/vnd.jupyter.widget-view+json": {
"version_major": 2,
"version_minor": 0,
"model_id": "a93a8c222f26426793c393a902857555"
}
},
"metadata": {}
}
]
},
{
"cell_type": "markdown",
"source": [
"# EDA "
],
"metadata": {
"id": "WQupsHEwk5WK"
}
},
{
"cell_type": "code",
"source": [
"df.describe(include='all')"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "tgoA-AOLl1R4",
"outputId": "f5892123-0fcd-4bbd-8011-006b1c68db5f"
},
"execution_count": null,
"outputs": [
{
"output_type": "execute_result",
"data": {
"text/plain": [
" grossRevenue comments likes dislikes shares \\\n",
"count 62916.000000 62916.000000 62916.000000 62916.000000 62916.000000 \n",
"mean 31.362255 8.553420 254.550769 2.923346 25.006739 \n",
"std 102.604443 33.817388 767.177603 11.929330 89.005026 \n",
"min 0.000000 0.000000 0.000000 0.000000 0.000000 \n",
"25% 0.014000 0.000000 0.050000 0.000000 0.000000 \n",
"50% 0.068000 0.000000 0.350000 0.000000 0.000000 \n",
"75% 0.618000 0.000000 2.000000 0.000000 1.000000 \n",
"max 1864.061000 3041.000000 18001.000000 1638.000000 2952.000000 \n",
"\n",
" videosAddedToPlaylists videosRemovedFromPlaylists subscribersGained \\\n",
"count 62916.000000 62916.000000 62916.000000 \n",
"mean 31.809524 19.324146 3.927936 \n",
"std 90.355063 47.906060 22.575875 \n",
"min 0.000000 0.000000 0.000000 \n",
"25% 0.000000 0.000000 0.000000 \n",
"50% 0.000000 1.000000 0.000000 \n",
"75% 1.000000 5.000000 0.000000 \n",
"max 1819.000000 1675.000000 1268.000000 \n",
"\n",
" subscribersLost adImpressions CumulativeSubscribers \\\n",
"count 62916.000000 62916.000000 62916.000000 \n",
"mean 0.811828 6859.033251 3.116107 \n",
"std 2.953472 22356.882830 20.870433 \n",
"min 0.000000 1.000000 -105.000000 \n",
"25% 0.000000 4.000000 0.000000 \n",
"50% 0.000000 14.000000 0.000000 \n",
"75% 0.000000 134.000000 0.000000 \n",
"max 159.000000 427568.000000 1208.000000 \n",
"\n",
" PlaylistCategory Channel1 Channel2 Channel3 \\\n",
"count 62916.000000 62916.000000 62916.000000 62916.000000 \n",
"mean 27.234424 0.327039 0.620383 0.020964 \n",
"std 12.685139 0.469135 0.485296 0.143266 \n",
"min 1.000000 0.000000 0.000000 0.000000 \n",
"25% 19.000000 0.000000 0.000000 0.000000 \n",
"50% 29.000000 0.000000 1.000000 0.000000 \n",
"75% 37.000000 1.000000 1.000000 0.000000 \n",
"max 45.000000 1.000000 1.000000 1.000000 \n",
"\n",
" Channel4 totalViews estimatedTotalMinutesWatched Channel \n",
"count 62916.000000 62916.000000 6.291600e+04 62916.000000 \n",
"mean 0.031614 4687.546220 3.669695e+04 1.757152 \n",
"std 0.174970 15339.538687 1.232509e+05 0.644585 \n",
"min 0.000000 1.000000 0.000000e+00 1.000000 \n",
"25% 0.000000 4.000000 1.500000e+01 1.000000 \n",
"50% 0.000000 14.000000 6.000000e+01 2.000000 \n",
"75% 0.000000 118.000000 6.822500e+02 2.000000 \n",
"max 1.000000 763210.000000 2.628919e+06 4.000000 "
],
"text/html": [
"\n",
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"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>grossRevenue</th>\n",
" <th>comments</th>\n",
" <th>likes</th>\n",
" <th>dislikes</th>\n",
" <th>shares</th>\n",
" <th>videosAddedToPlaylists</th>\n",
" <th>videosRemovedFromPlaylists</th>\n",
" <th>subscribersGained</th>\n",
" <th>subscribersLost</th>\n",
" <th>adImpressions</th>\n",
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" <th>PlaylistCategory</th>\n",
" <th>Channel1</th>\n",
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" <th>Channel</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>count</th>\n",
" <td>62916.000000</td>\n",
" <td>62916.000000</td>\n",
" <td>62916.000000</td>\n",
" <td>62916.000000</td>\n",
" <td>62916.000000</td>\n",
" <td>62916.000000</td>\n",
" <td>62916.000000</td>\n",
" <td>62916.000000</td>\n",
" <td>62916.000000</td>\n",
" <td>62916.000000</td>\n",
" <td>62916.000000</td>\n",
" <td>62916.000000</td>\n",
" <td>62916.000000</td>\n",
" <td>62916.000000</td>\n",
" <td>62916.000000</td>\n",
" <td>62916.000000</td>\n",
" <td>62916.000000</td>\n",
" <td>6.291600e+04</td>\n",
" <td>62916.000000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>mean</th>\n",
" <td>31.362255</td>\n",
" <td>8.553420</td>\n",
" <td>254.550769</td>\n",
" <td>2.923346</td>\n",
" <td>25.006739</td>\n",
" <td>31.809524</td>\n",
" <td>19.324146</td>\n",
" <td>3.927936</td>\n",
" <td>0.811828</td>\n",
" <td>6859.033251</td>\n",
" <td>3.116107</td>\n",
" <td>27.234424</td>\n",
" <td>0.327039</td>\n",
" <td>0.620383</td>\n",
" <td>0.020964</td>\n",
" <td>0.031614</td>\n",
" <td>4687.546220</td>\n",
" <td>3.669695e+04</td>\n",
" <td>1.757152</td>\n",
" </tr>\n",
" <tr>\n",
" <th>std</th>\n",
" <td>102.604443</td>\n",
" <td>33.817388</td>\n",
" <td>767.177603</td>\n",
" <td>11.929330</td>\n",
" <td>89.005026</td>\n",
" <td>90.355063</td>\n",
" <td>47.906060</td>\n",
" <td>22.575875</td>\n",
" <td>2.953472</td>\n",
" <td>22356.882830</td>\n",
" <td>20.870433</td>\n",
" <td>12.685139</td>\n",
" <td>0.469135</td>\n",
" <td>0.485296</td>\n",
" <td>0.143266</td>\n",
" <td>0.174970</td>\n",
" <td>15339.538687</td>\n",
" <td>1.232509e+05</td>\n",
" <td>0.644585</td>\n",
" </tr>\n",
" <tr>\n",
" <th>min</th>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>1.000000</td>\n",
" <td>-105.000000</td>\n",
" <td>1.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>1.000000</td>\n",
" <td>0.000000e+00</td>\n",
" <td>1.000000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>25%</th>\n",
" <td>0.014000</td>\n",
" <td>0.000000</td>\n",
" <td>0.050000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>4.000000</td>\n",
" <td>0.000000</td>\n",
" <td>19.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>4.000000</td>\n",
" <td>1.500000e+01</td>\n",
" <td>1.000000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>50%</th>\n",
" <td>0.068000</td>\n",
" <td>0.000000</td>\n",
" <td>0.350000</td>\n",
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" <td>0.618000</td>\n",
" <td>0.000000</td>\n",
" <td>2.000000</td>\n",
" <td>0.000000</td>\n",
" <td>1.000000</td>\n",
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" <td>1638.000000</td>\n",
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" <td>1819.000000</td>\n",
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" <td>159.000000</td>\n",
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" <td>1.000000</td>\n",
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" <td>1.000000</td>\n",
" <td>763210.000000</td>\n",
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},
"metadata": {},
"execution_count": 78
}
]
},
{
"cell_type": "code",
"source": [
"df[df['grossRevenue'] <=1]"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "ud1WbM5GmFcp",
"outputId": "0e1c2b22-d07c-4e32-a668-ab8419114f6c"
},
"execution_count": null,
"outputs": [
{
"output_type": "execute_result",
"data": {
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" grossRevenue comments likes dislikes shares \\\n",
"11 0.661 2.0 18.00 0.0 3.0 \n",
"13 0.840 1.0 7.00 0.0 1.0 \n",
"14 0.734 2.0 6.00 0.0 3.0 \n",
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"... ... ... ... ... ... \n",
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"62915 0.012 0.0 0.29 0.0 0.0 \n",
"\n",
" videosAddedToPlaylists videosRemovedFromPlaylists subscribersGained \\\n",
"11 2.0 5.0 3.0 \n",
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" subscribersLost adImpressions CumulativeSubscribers \\\n",
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"\n",
" PlaylistCategory Channel1 Channel2 Channel3 Channel4 totalViews \\\n",
"11 45.0 1 0 0 0 354.0 \n",
"13 45.0 1 0 0 0 213.0 \n",
"14 45.0 1 0 0 0 170.0 \n",
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"\n",
" estimatedTotalMinutesWatched Channel \n",
"11 1192.0 1 \n",
"13 757.0 1 \n",
"14 555.0 1 \n",
"15 686.0 1 \n",
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"... ... ... \n",
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"62915 13.0 4 \n",
"\n",
"[48876 rows x 19 columns]"
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"df[df['grossRevenue'] > 1]"
],
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" grossRevenue comments likes dislikes shares \\\n",
"0 953.390 3041.0 6959.00 99.0 920.0 \n",
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"metadata": {},
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{
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"data": {
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},
"metadata": {},
"execution_count": 81
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{
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\n"
},
"metadata": {
"needs_background": "light"
}
}
]
},
{
"cell_type": "code",
"source": [
"sns.barplot(data=df, y='grossRevenue', x='Channel')"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "NaGSQM9mnhIo",
"outputId": "671d32c2-81d2-450a-8d46-d800fef974f0"
},
"execution_count": null,
"outputs": [
{
"output_type": "execute_result",
"data": {
"text/plain": [
"<matplotlib.axes._subplots.AxesSubplot at 0x7f71f6ff3b80>"
]
},
"metadata": {},
"execution_count": 82
},
{
"output_type": "display_data",
"data": {
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
],
"image/png": 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\n"
},
"metadata": {
"needs_background": "light"
}
}
]
},
{
"cell_type": "code",
"source": [
"df.corr()"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "IsENSgJUX_Tp",
"outputId": "65e4098f-3971-4be8-bc4a-7c12bdc1da2b"
},
"execution_count": null,
"outputs": [
{
"output_type": "execute_result",
"data": {
"text/plain": [
" grossRevenue comments likes dislikes \\\n",
"grossRevenue 1.000000 0.693357 0.904362 0.675779 \n",
"comments 0.693357 1.000000 0.697669 0.642609 \n",
"likes 0.904362 0.697669 1.000000 0.697455 \n",
"dislikes 0.675779 0.642609 0.697455 1.000000 \n",
"shares 0.818165 0.722934 0.881143 0.707118 \n",
"videosAddedToPlaylists 0.911066 0.713733 0.965812 0.690591 \n",
"videosRemovedFromPlaylists 0.871958 0.687493 0.922696 0.644885 \n",
"subscribersGained 0.667617 0.615336 0.550869 0.631346 \n",
"subscribersLost 0.734069 0.688951 0.763905 0.629282 \n",
"adImpressions 0.985759 0.703339 0.916127 0.678270 \n",
"CumulativeSubscribers 0.618290 0.568122 0.487780 0.593884 \n",
"PlaylistCategory -0.081244 -0.058306 -0.064416 -0.049354 \n",
"Channel1 0.024227 0.118919 -0.028601 0.031853 \n",
"Channel2 -0.002283 -0.096802 0.047370 -0.018276 \n",
"Channel3 -0.041575 -0.031691 -0.039084 -0.027776 \n",
"Channel4 -0.024583 -0.024412 -0.022697 -0.011974 \n",
"totalViews 0.896132 0.750383 0.879689 0.824336 \n",
"estimatedTotalMinutesWatched 0.905490 0.754634 0.910473 0.714789 \n",
"Channel -0.040219 -0.106847 -0.000192 -0.035858 \n",
"\n",
" shares videosAddedToPlaylists \\\n",
"grossRevenue 0.818165 0.911066 \n",
"comments 0.722934 0.713733 \n",
"likes 0.881143 0.965812 \n",
"dislikes 0.707118 0.690591 \n",
"shares 1.000000 0.892757 \n",
"videosAddedToPlaylists 0.892757 1.000000 \n",
"videosRemovedFromPlaylists 0.809781 0.966756 \n",
"subscribersGained 0.625167 0.602464 \n",
"subscribersLost 0.723906 0.770275 \n",
"adImpressions 0.833160 0.922974 \n",
"CumulativeSubscribers 0.573809 0.542689 \n",
"PlaylistCategory -0.038594 -0.077892 \n",
"Channel1 -0.002509 0.008913 \n",
"Channel2 0.019933 0.009698 \n",
"Channel3 -0.036420 -0.034106 \n",
"Channel4 -0.018738 -0.022870 \n",
"totalViews 0.830410 0.893240 \n",
"estimatedTotalMinutesWatched 0.843971 0.901585 \n",
"Channel -0.016442 -0.026483 \n",
"\n",
" videosRemovedFromPlaylists subscribersGained \\\n",
"grossRevenue 0.871958 0.667617 \n",
"comments 0.687493 0.615336 \n",
"likes 0.922696 0.550869 \n",
"dislikes 0.644885 0.631346 \n",
"shares 0.809781 0.625167 \n",
"videosAddedToPlaylists 0.966756 0.602464 \n",
"videosRemovedFromPlaylists 1.000000 0.555688 \n",
"subscribersGained 0.555688 1.000000 \n",
"subscribersLost 0.732187 0.621038 \n",
"adImpressions 0.889937 0.681202 \n",
"CumulativeSubscribers 0.497482 0.993830 \n",
"PlaylistCategory -0.104589 -0.066481 \n",
"Channel1 0.031648 0.074388 \n",
"Channel2 -0.008283 -0.076628 \n",
"Channel3 -0.039512 -0.022035 \n",
"Channel4 -0.029529 0.031125 \n",
"totalViews 0.869696 0.771318 \n",
"estimatedTotalMinutesWatched 0.847158 0.664153 \n",
"Channel -0.047847 -0.042140 \n",
"\n",
" subscribersLost adImpressions \\\n",
"grossRevenue 0.734069 0.985759 \n",
"comments 0.688951 0.703339 \n",
"likes 0.763905 0.916127 \n",
"dislikes 0.629282 0.678270 \n",
"shares 0.723906 0.833160 \n",
"videosAddedToPlaylists 0.770275 0.922974 \n",
"videosRemovedFromPlaylists 0.732187 0.889937 \n",
"subscribersGained 0.621038 0.681202 \n",
"subscribersLost 1.000000 0.738978 \n",
"adImpressions 0.738978 1.000000 \n",
"CumulativeSubscribers 0.530272 0.632291 \n",
"PlaylistCategory -0.049073 -0.092141 \n",
"Channel1 0.069147 0.014739 \n",
"Channel2 -0.057945 0.005673 \n",
"Channel3 -0.032786 -0.041732 \n",
"Channel4 0.002161 -0.021084 \n",
"totalViews 0.749347 0.922549 \n",
"estimatedTotalMinutesWatched 0.804993 0.910116 \n",
"Channel -0.056440 -0.031449 \n",
"\n",
" CumulativeSubscribers PlaylistCategory \\\n",
"grossRevenue 0.618290 -0.081244 \n",
"comments 0.568122 -0.058306 \n",
"likes 0.487780 -0.064416 \n",
"dislikes 0.593884 -0.049354 \n",
"shares 0.573809 -0.038594 \n",
"videosAddedToPlaylists 0.542689 -0.077892 \n",
"videosRemovedFromPlaylists 0.497482 -0.104589 \n",
"subscribersGained 0.993830 -0.066481 \n",
"subscribersLost 0.530272 -0.049073 \n",
"adImpressions 0.632291 -0.092141 \n",
"CumulativeSubscribers 1.000000 -0.064969 \n",
"PlaylistCategory -0.064969 1.000000 \n",
"Channel1 0.070681 0.014579 \n",
"Channel2 -0.074689 0.093781 \n",
"Channel3 -0.019196 -0.044991 \n",
"Channel4 0.033363 -0.262360 \n",
"totalViews 0.728303 -0.093282 \n",
"estimatedTotalMinutesWatched 0.604506 -0.057773 \n",
"Channel -0.037597 -0.163044 \n",
"\n",
" Channel1 Channel2 Channel3 Channel4 \\\n",
"grossRevenue 0.024227 -0.002283 -0.041575 -0.024583 \n",
"comments 0.118919 -0.096802 -0.031691 -0.024412 \n",
"likes -0.028601 0.047370 -0.039084 -0.022697 \n",
"dislikes 0.031853 -0.018276 -0.027776 -0.011974 \n",
"shares -0.002509 0.019933 -0.036420 -0.018738 \n",
"videosAddedToPlaylists 0.008913 0.009698 -0.034106 -0.022870 \n",
"videosRemovedFromPlaylists 0.031648 -0.008283 -0.039512 -0.029529 \n",
"subscribersGained 0.074388 -0.076628 -0.022035 0.031125 \n",
"subscribersLost 0.069147 -0.057945 -0.032786 0.002161 \n",
"adImpressions 0.014739 0.005673 -0.041732 -0.021084 \n",
"CumulativeSubscribers 0.070681 -0.074689 -0.019196 0.033363 \n",
"PlaylistCategory 0.014579 0.093781 -0.044991 -0.262360 \n",
"Channel1 1.000000 -0.891173 -0.102011 -0.125956 \n",
"Channel2 -0.891173 1.000000 -0.187068 -0.230977 \n",
"Channel3 -0.102011 -0.187068 1.000000 -0.026440 \n",
"Channel4 -0.125956 -0.230977 -0.026440 1.000000 \n",
"totalViews 0.047014 -0.026994 -0.041286 -0.017381 \n",
"estimatedTotalMinutesWatched 0.020453 0.002441 -0.041360 -0.027745 \n",
"Channel -0.818864 0.481631 0.282152 0.628689 \n",
"\n",
" totalViews estimatedTotalMinutesWatched \\\n",
"grossRevenue 0.896132 0.905490 \n",
"comments 0.750383 0.754634 \n",
"likes 0.879689 0.910473 \n",
"dislikes 0.824336 0.714789 \n",
"shares 0.830410 0.843971 \n",
"videosAddedToPlaylists 0.893240 0.901585 \n",
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" background-color: #434B5C;\n",
" box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
" filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
" fill: #FFFFFF;\n",
" }\n",
" </style>\n",
"\n",
" <script>\n",
" const buttonEl =\n",
" document.querySelector('#df-12a2556e-37a4-4b18-b065-e06eea9d3229 button.colab-df-convert');\n",
" buttonEl.style.display =\n",
" google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
"\n",
" async function convertToInteractive(key) {\n",
" const element = document.querySelector('#df-12a2556e-37a4-4b18-b065-e06eea9d3229');\n",
" const dataTable =\n",
" await google.colab.kernel.invokeFunction('convertToInteractive',\n",
" [key], {});\n",
" if (!dataTable) return;\n",
"\n",
" const docLinkHtml = 'Like what you see? Visit the ' +\n",
" '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
" + ' to learn more about interactive tables.';\n",
" element.innerHTML = '';\n",
" dataTable['output_type'] = 'display_data';\n",
" await google.colab.output.renderOutput(dataTable, element);\n",
" const docLink = document.createElement('div');\n",
" docLink.innerHTML = docLinkHtml;\n",
" element.appendChild(docLink);\n",
" }\n",
" </script>\n",
" </div>\n",
" </div>\n",
" "
]
},
"metadata": {},
"execution_count": 83
}
]
},
{
"cell_type": "code",
"source": [
"corr_df = df.corr()\n",
"test_corr_df = corr_df[abs(corr_df)>=0.7]\n",
"test_corr_df"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "P9C6CTPnDJx4",
"outputId": "9b730b30-28de-4a2e-c87b-199c7db514d4"
},
"execution_count": null,
"outputs": [
{
"output_type": "execute_result",
"data": {
"text/plain": [
" grossRevenue comments likes dislikes \\\n",
"grossRevenue 1.000000 NaN 0.904362 NaN \n",
"comments NaN 1.000000 NaN NaN \n",
"likes 0.904362 NaN 1.000000 NaN \n",
"dislikes NaN NaN NaN 1.000000 \n",
"shares 0.818165 0.722934 0.881143 0.707118 \n",
"videosAddedToPlaylists 0.911066 0.713733 0.965812 NaN \n",
"videosRemovedFromPlaylists 0.871958 NaN 0.922696 NaN \n",
"subscribersGained NaN NaN NaN NaN \n",
"subscribersLost 0.734069 NaN 0.763905 NaN \n",
"adImpressions 0.985759 0.703339 0.916127 NaN \n",
"CumulativeSubscribers NaN NaN NaN NaN \n",
"PlaylistCategory NaN NaN NaN NaN \n",
"Channel1 NaN NaN NaN NaN \n",
"Channel2 NaN NaN NaN NaN \n",
"Channel3 NaN NaN NaN NaN \n",
"Channel4 NaN NaN NaN NaN \n",
"totalViews 0.896132 0.750383 0.879689 0.824336 \n",
"estimatedTotalMinutesWatched 0.905490 0.754634 0.910473 0.714789 \n",
"Channel NaN NaN NaN NaN \n",
"\n",
" shares videosAddedToPlaylists \\\n",
"grossRevenue 0.818165 0.911066 \n",
"comments 0.722934 0.713733 \n",
"likes 0.881143 0.965812 \n",
"dislikes 0.707118 NaN \n",
"shares 1.000000 0.892757 \n",
"videosAddedToPlaylists 0.892757 1.000000 \n",
"videosRemovedFromPlaylists 0.809781 0.966756 \n",
"subscribersGained NaN NaN \n",
"subscribersLost 0.723906 0.770275 \n",
"adImpressions 0.833160 0.922974 \n",
"CumulativeSubscribers NaN NaN \n",
"PlaylistCategory NaN NaN \n",
"Channel1 NaN NaN \n",
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"totalViews 0.830410 0.893240 \n",
"estimatedTotalMinutesWatched 0.843971 0.901585 \n",
"Channel NaN NaN \n",
"\n",
" videosRemovedFromPlaylists subscribersGained \\\n",
"grossRevenue 0.871958 NaN \n",
"comments NaN NaN \n",
"likes 0.922696 NaN \n",
"dislikes NaN NaN \n",
"shares 0.809781 NaN \n",
"videosAddedToPlaylists 0.966756 NaN \n",
"videosRemovedFromPlaylists 1.000000 NaN \n",
"subscribersGained NaN 1.000000 \n",
"subscribersLost 0.732187 NaN \n",
"adImpressions 0.889937 NaN \n",
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"PlaylistCategory NaN NaN \n",
"Channel1 NaN NaN \n",
"Channel2 NaN NaN \n",
"Channel3 NaN NaN \n",
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"totalViews 0.869696 0.771318 \n",
"estimatedTotalMinutesWatched 0.847158 NaN \n",
"Channel NaN NaN \n",
"\n",
" subscribersLost adImpressions \\\n",
"grossRevenue 0.734069 0.985759 \n",
"comments NaN 0.703339 \n",
"likes 0.763905 0.916127 \n",
"dislikes NaN NaN \n",
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"videosAddedToPlaylists 0.770275 0.922974 \n",
"videosRemovedFromPlaylists 0.732187 0.889937 \n",
"subscribersGained NaN NaN \n",
"subscribersLost 1.000000 0.738978 \n",
"adImpressions 0.738978 1.000000 \n",
"CumulativeSubscribers NaN NaN \n",
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"Channel NaN NaN \n",
"\n",
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"\n",
" Channel1 Channel2 Channel3 Channel4 \\\n",
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"Channel -0.818864 NaN NaN NaN \n",
"\n",
" totalViews estimatedTotalMinutesWatched \\\n",
"grossRevenue 0.896132 0.905490 \n",
"comments 0.750383 0.754634 \n",
"likes 0.879689 0.910473 \n",
"dislikes 0.824336 0.714789 \n",
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"subscribersGained 0.771318 NaN \n",
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" vertical-align: middle;\n",
" }\n",
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"</style>\n",
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" <td>0.750383</td>\n",
" <td>0.879689</td>\n",
" <td>0.824336</td>\n",
" <td>0.830410</td>\n",
" <td>0.893240</td>\n",
" <td>0.869696</td>\n",
" <td>0.771318</td>\n",
" <td>0.749347</td>\n",
" <td>0.922549</td>\n",
" <td>0.728303</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>1.000000</td>\n",
" <td>0.878284</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>estimatedTotalMinutesWatched</th>\n",
" <td>0.905490</td>\n",
" <td>0.754634</td>\n",
" <td>0.910473</td>\n",
" <td>0.714789</td>\n",
" <td>0.843971</td>\n",
" <td>0.901585</td>\n",
" <td>0.847158</td>\n",
" <td>NaN</td>\n",
" <td>0.804993</td>\n",
" <td>0.910116</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>0.878284</td>\n",
" <td>1.000000</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Channel</th>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>-0.818864</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>1.000000</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>\n",
" <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-e094a78a-f7cb-4f39-987f-6396a7dfc284')\"\n",
" title=\"Convert this dataframe to an interactive table.\"\n",
" style=\"display:none;\">\n",
" \n",
" <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
" width=\"24px\">\n",
" <path d=\"M0 0h24v24H0V0z\" fill=\"none\"/>\n",
" <path d=\"M18.56 5.44l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94zm-11 1L8.5 8.5l.94-2.06 2.06-.94-2.06-.94L8.5 2.5l-.94 2.06-2.06.94zm10 10l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94z\"/><path d=\"M17.41 7.96l-1.37-1.37c-.4-.4-.92-.59-1.43-.59-.52 0-1.04.2-1.43.59L10.3 9.45l-7.72 7.72c-.78.78-.78 2.05 0 2.83L4 21.41c.39.39.9.59 1.41.59.51 0 1.02-.2 1.41-.59l7.78-7.78 2.81-2.81c.8-.78.8-2.07 0-2.86zM5.41 20L4 18.59l7.72-7.72 1.47 1.35L5.41 20z\"/>\n",
" </svg>\n",
" </button>\n",
" \n",
" <style>\n",
" .colab-df-container {\n",
" display:flex;\n",
" flex-wrap:wrap;\n",
" gap: 12px;\n",
" }\n",
"\n",
" .colab-df-convert {\n",
" background-color: #E8F0FE;\n",
" border: none;\n",
" border-radius: 50%;\n",
" cursor: pointer;\n",
" display: none;\n",
" fill: #1967D2;\n",
" height: 32px;\n",
" padding: 0 0 0 0;\n",
" width: 32px;\n",
" }\n",
"\n",
" .colab-df-convert:hover {\n",
" background-color: #E2EBFA;\n",
" box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
" fill: #174EA6;\n",
" }\n",
"\n",
" [theme=dark] .colab-df-convert {\n",
" background-color: #3B4455;\n",
" fill: #D2E3FC;\n",
" }\n",
"\n",
" [theme=dark] .colab-df-convert:hover {\n",
" background-color: #434B5C;\n",
" box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
" filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
" fill: #FFFFFF;\n",
" }\n",
" </style>\n",
"\n",
" <script>\n",
" const buttonEl =\n",
" document.querySelector('#df-e094a78a-f7cb-4f39-987f-6396a7dfc284 button.colab-df-convert');\n",
" buttonEl.style.display =\n",
" google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
"\n",
" async function convertToInteractive(key) {\n",
" const element = document.querySelector('#df-e094a78a-f7cb-4f39-987f-6396a7dfc284');\n",
" const dataTable =\n",
" await google.colab.kernel.invokeFunction('convertToInteractive',\n",
" [key], {});\n",
" if (!dataTable) return;\n",
"\n",
" const docLinkHtml = 'Like what you see? Visit the ' +\n",
" '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
" + ' to learn more about interactive tables.';\n",
" element.innerHTML = '';\n",
" dataTable['output_type'] = 'display_data';\n",
" await google.colab.output.renderOutput(dataTable, element);\n",
" const docLink = document.createElement('div');\n",
" docLink.innerHTML = docLinkHtml;\n",
" element.appendChild(docLink);\n",
" }\n",
" </script>\n",
" </div>\n",
" </div>\n",
" "
]
},
"metadata": {},
"execution_count": 84
}
]
},
{
"cell_type": "code",
"source": [
"sns.heatmap(test_corr_df, cmap='crest')"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "6IOgPRfgDPdj",
"outputId": "f3d166f4-bfac-4bea-9e62-c11bbe49d659"
},
"execution_count": null,
"outputs": [
{
"output_type": "execute_result",
"data": {
"text/plain": [
"<matplotlib.axes._subplots.AxesSubplot at 0x7f71f9303370>"
]
},
"metadata": {},
"execution_count": 85
},
{
"output_type": "display_data",
"data": {
"text/plain": [
"<Figure size 432x288 with 2 Axes>"
],
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\n"
},
"metadata": {
"needs_background": "light"
}
}
]
},
{
"cell_type": "code",
"source": [
"for i in df: \n",
" if i == \"const\":\n",
" continue\n",
" print(i)\n",
" sns.displot(x=df[i], bins=50, kde=True)\n",
" plt.show()"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "iKcYjX5DkLjS",
"outputId": "a1a0086f-29d4-4c88-e1f2-042a42b51978"
},
"execution_count": null,
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
"grossRevenue\n"
]
},
{
"output_type": "display_data",
"data": {
"text/plain": [
"<Figure size 360x360 with 1 Axes>"
],
"image/png": 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\n"
},
"metadata": {
"needs_background": "light"
}
},
{
"output_type": "stream",
"name": "stdout",
"text": [
"comments\n"
]
},
{
"output_type": "display_data",
"data": {
"text/plain": [
"<Figure size 360x360 with 1 Axes>"
],
"image/png": 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\n"
},
"metadata": {
"needs_background": "light"
}
},
{
"output_type": "stream",
"name": "stdout",
"text": [
"likes\n"
]
},
{
"output_type": "display_data",
"data": {
"text/plain": [
"<Figure size 360x360 with 1 Axes>"
],
"image/png": "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\n"
},
"metadata": {
"needs_background": "light"
}
},
{
"output_type": "stream",
"name": "stdout",
"text": [
"dislikes\n"
]
},
{
"output_type": "display_data",
"data": {
"text/plain": [
"<Figure size 360x360 with 1 Axes>"
],
"image/png": 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\n"
},
"metadata": {
"needs_background": "light"
}
},
{
"output_type": "stream",
"name": "stdout",
"text": [
"shares\n"
]
},
{
"output_type": "display_data",
"data": {
"text/plain": [
"<Figure size 360x360 with 1 Axes>"
],
"image/png": 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\n"
},
"metadata": {
"needs_background": "light"
}
},
{
"output_type": "stream",
"name": "stdout",
"text": [
"videosAddedToPlaylists\n"
]
},
{
"output_type": "display_data",
"data": {
"text/plain": [
"<Figure size 360x360 with 1 Axes>"
],
"image/png": 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\n"
},
"metadata": {
"needs_background": "light"
}
},
{
"output_type": "stream",
"name": "stdout",
"text": [
"videosRemovedFromPlaylists\n"
]
},
{
"output_type": "display_data",
"data": {
"text/plain": [
"<Figure size 360x360 with 1 Axes>"
],
"image/png": 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\n"
},
"metadata": {
"needs_background": "light"
}
},
{
"output_type": "stream",
"name": "stdout",
"text": [
"subscribersGained\n"
]
},
{
"output_type": "display_data",
"data": {
"text/plain": [
"<Figure size 360x360 with 1 Axes>"
],
"image/png": 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\n"
},
"metadata": {
"needs_background": "light"
}
},
{
"output_type": "stream",
"name": "stdout",
"text": [
"subscribersLost\n"
]
},
{
"output_type": "display_data",
"data": {
"text/plain": [
"<Figure size 360x360 with 1 Axes>"
],
"image/png": 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\n"
},
"metadata": {
"needs_background": "light"
}
},
{
"output_type": "stream",
"name": "stdout",
"text": [
"adImpressions\n"
]
},
{
"output_type": "display_data",
"data": {
"text/plain": [
"<Figure size 360x360 with 1 Axes>"
],
"image/png": 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\n"
},
"metadata": {
"needs_background": "light"
}
},
{
"output_type": "stream",
"name": "stdout",
"text": [
"CumulativeSubscribers\n"
]
},
{
"output_type": "display_data",
"data": {
"text/plain": [
"<Figure size 360x360 with 1 Axes>"
],
"image/png": "iVBORw0KGgoAAAANSUhEUgAAAWAAAAFgCAYAAACFYaNMAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAALEgAACxIB0t1+/AAAADh0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uMy4yLjIsIGh0dHA6Ly9tYXRwbG90bGliLm9yZy+WH4yJAAAgAElEQVR4nO3de5hdVZ3m8e9buZAglwSI6ZjQTWgzTkdaECKE1vFBmQ6B0Y5OIw3tSFrRdI8wI9rtCM08jZf2ae2LONgKomQIDi0g4pC2IzFCkKf7kZhwEQiIlFxMIobcCAghJNRv/tjrVO0qqiqVpE7tNbXej895ap+199lnnYP11sraa62
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