Negative Sentiment Analysis Of YouTube Comments .ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "#TO PERFORM SENTIMENT ANALYSIS OF YOU TUBE COMMENT ANALYSIS\n",
    "\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "b'Skipping line 113225: expected 4 fields, saw 5\\n'\n",
      "b'Skipping line 158379: expected 4 fields, saw 7\\nSkipping line 241590: expected 4 fields, saw 5\\nSkipping line 245637: expected 4 fields, saw 7\\n'\n",
      "b'Skipping line 521402: expected 4 fields, saw 5\\n'\n"
     ]
    }
   ],
   "source": [
    "GB_Comments_original=pd.read_csv(\"D:\\Ishty Folder\\Projects Python\\You Tube/GBcomments.csv\",error_bad_lines=False)\n",
    "GB_Comments = GB_Comments_original"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "The heads of the file contains : \n"
     ]
    },
    {
     "data": {
      "text/html": [
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       "\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>video_id</th>\n",
       "      <th>comment_text</th>\n",
       "      <th>likes</th>\n",
       "      <th>replies</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>jt2OHQh0HoQ</td>\n",
       "      <td>It's more accurate to call it the M+ (1000) be...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>jt2OHQh0HoQ</td>\n",
       "      <td>To be there with a samsung phone\\n😂😂😂</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>jt2OHQh0HoQ</td>\n",
       "      <td>Thank gosh, a place I can watch it without hav...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>jt2OHQh0HoQ</td>\n",
       "      <td>What happened to the home button on the iPhone...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>jt2OHQh0HoQ</td>\n",
       "      <td>Power is the disease.  Care is the cure.  Keep...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      video_id                                       comment_text  likes  \\\n",
       "0  jt2OHQh0HoQ  It's more accurate to call it the M+ (1000) be...      0   \n",
       "1  jt2OHQh0HoQ              To be there with a samsung phone\\n😂😂😂      1   \n",
       "2  jt2OHQh0HoQ  Thank gosh, a place I can watch it without hav...      0   \n",
       "3  jt2OHQh0HoQ  What happened to the home button on the iPhone...      0   \n",
       "4  jt2OHQh0HoQ  Power is the disease.  Care is the cure.  Keep...      0   \n",
       "\n",
       "   replies  \n",
       "0        0  \n",
       "1        0  \n",
       "2        0  \n",
       "3        0  \n",
       "4        0  "
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "print(\"The heads of the file contains : \")\n",
    "GB_Comments.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "The file contains total (718452, 4) rows and columns respectively \n"
     ]
    }
   ],
   "source": [
    "print(\"The file contains total\", GB_Comments.shape, \"rows and columns respectively \" )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "The maximum like containing row is \n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "    .dataframe tbody tr th:only-of-type {\n",
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       "\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>video_id</th>\n",
       "      <th>comment_text</th>\n",
       "      <th>likes</th>\n",
       "      <th>replies</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>16569</th>\n",
       "      <td>WNZTec6BbOU</td>\n",
       "      <td>WE'RE CRUSHING THE CHARTS!!!!! THANK YOU ALL F...</td>\n",
       "      <td>60630</td>\n",
       "      <td>521</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          video_id                                       comment_text  likes  \\\n",
       "16569  WNZTec6BbOU  WE'RE CRUSHING THE CHARTS!!!!! THANK YOU ALL F...  60630   \n",
       "\n",
       "       replies  \n",
       "16569      521  "
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "print(\"The maximum like containing row is \")\n",
    "GB_Comments[GB_Comments[\"likes\"] == GB_Comments[\"likes\"].max()]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "The minimum like is  0\n",
      "The total commments containing minimum likes is 576440\n"
     ]
    }
   ],
   "source": [
    "b=GB_Comments[\"likes\"].min()\n",
    "print(\"The minimum like is \", b)\n",
    "list=[]\n",
    "for i in GB_Comments['likes']:    \n",
    "    if i == b:\n",
    "        list.append(i)\n",
    "print(\"The total commments containing minimum likes is\", len(list))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "The maximum replies containing row is \n"
     ]
    },
    {
     "data": {
      "text/html": [
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       "\n",
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       "        text-align: right;\n",
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>video_id</th>\n",
       "      <th>comment_text</th>\n",
       "      <th>likes</th>\n",
       "      <th>replies</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>16569</th>\n",
       "      <td>WNZTec6BbOU</td>\n",
       "      <td>WE'RE CRUSHING THE CHARTS!!!!! THANK YOU ALL F...</td>\n",
       "      <td>60630</td>\n",
       "      <td>521</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          video_id                                       comment_text  likes  \\\n",
       "16569  WNZTec6BbOU  WE'RE CRUSHING THE CHARTS!!!!! THANK YOU ALL F...  60630   \n",
       "\n",
       "       replies  \n",
       "16569      521  "
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "print(\"The maximum replies containing row is \")\n",
    "GB_Comments[GB_Comments[\"replies\"] == GB_Comments[\"replies\"].max()]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "The minimum number of replies is  0\n",
      "The total commments containing minimum replies is 673338\n"
     ]
    }
   ],
   "source": [
    "b=GB_Comments[\"replies\"].min()\n",
    "print(\"The minimum number of replies is \", b)\n",
    "list=[]\n",
    "for i in GB_Comments['replies']:    \n",
    "    if i == b:\n",
    "        list.append(i)\n",
    "print(\"The total commments containing minimum replies is\", len(list))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Requirement already satisfied: textblob in c:\\users\\deepanshu\\anaconda3\\lib\\site-packages (0.15.3)\n",
      "Requirement already satisfied: nltk>=3.1 in c:\\users\\deepanshu\\anaconda3\\lib\\site-packages (from textblob) (3.5)\n",
      "Requirement already satisfied: joblib in c:\\users\\deepanshu\\anaconda3\\lib\\site-packages (from nltk>=3.1->textblob) (0.17.0)\n",
      "Requirement already satisfied: click in c:\\users\\deepanshu\\anaconda3\\lib\\site-packages (from nltk>=3.1->textblob) (7.1.2)\n",
      "Requirement already satisfied: tqdm in c:\\users\\deepanshu\\anaconda3\\lib\\site-packages (from nltk>=3.1->textblob) (4.50.2)\n",
      "Requirement already satisfied: regex in c:\\users\\deepanshu\\anaconda3\\lib\\site-packages (from nltk>=3.1->textblob) (2020.10.15)\n",
      "Total number of null values in the data is \n",
      "video_id         0\n",
      "comment_text    28\n",
      "likes            0\n",
      "replies          0\n",
      "dtype: int64\n"
     ]
    }
   ],
   "source": [
    "!pip install textblob \n",
    "from textblob import TextBlob\n",
    "print(\"Total number of null values in the data is \")\n",
    "print(GB_Comments.isna().sum())\n",
    "GB_Comments.dropna(inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "count     718424\n",
       "unique    372844\n",
       "top           Hi\n",
       "freq         348\n",
       "Name: comment_text, dtype: object"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "GB_Comments[\"comment_text\"].describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "count    718424.000000\n",
       "mean          0.381264\n",
       "std           8.968133\n",
       "min           0.000000\n",
       "25%           0.000000\n",
       "50%           0.000000\n",
       "75%           0.000000\n",
       "max         521.000000\n",
       "Name: replies, dtype: float64"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "GB_Comments[\"replies\"].describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "count    718424.000000\n",
       "mean          5.237658\n",
       "std         203.887864\n",
       "min           0.000000\n",
       "25%           0.000000\n",
       "50%           0.000000\n",
       "75%           0.000000\n",
       "max       60630.000000\n",
       "Name: likes, dtype: float64"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "GB_Comments[\"likes\"].describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "#to analize the polarity of all comments\n",
    "\n",
    "polarity=[]\n",
    "for i in GB_Comments['comment_text']:\n",
    "    Pole=TextBlob(i).sentiment.polarity\n",
    "    polarity.append(Pole)\n",
    "GB_Comments['Polarity']=polarity"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>video_id</th>\n",
       "      <th>comment_text</th>\n",
       "      <th>likes</th>\n",
       "      <th>replies</th>\n",
       "      <th>Polarity</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>jt2OHQh0HoQ</td>\n",
       "      <td>It's more accurate to call it the M+ (1000) be...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.450000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>jt2OHQh0HoQ</td>\n",
       "      <td>To be there with a samsung phone\\n😂😂😂</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>jt2OHQh0HoQ</td>\n",
       "      <td>Thank gosh, a place I can watch it without hav...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>jt2OHQh0HoQ</td>\n",
       "      <td>What happened to the home button on the iPhone...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>jt2OHQh0HoQ</td>\n",
       "      <td>Power is the disease.  Care is the cure.  Keep...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>jt2OHQh0HoQ</td>\n",
       "      <td>Keep calm and buy iphone 8 Keep calm and buy i...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.300000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>jt2OHQh0HoQ</td>\n",
       "      <td>i am a big fan of youtube and u !!!!!!!!!!!!!</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>jt2OHQh0HoQ</td>\n",
       "      <td>You will never find Losers who line up and pay...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>-0.100000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>jt2OHQh0HoQ</td>\n",
       "      <td>*APPLE JUST COMMENTED ON MY LAST VIDEO* I'm cr...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.028571</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>jt2OHQh0HoQ</td>\n",
       "      <td>I'm only here to see Emma, I love her so much!...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.500000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>jt2OHQh0HoQ</td>\n",
       "      <td>Mom said: Just one more video before bed</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.500000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>jt2OHQh0HoQ</td>\n",
       "      <td>what is the song?? 39:20</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>jt2OHQh0HoQ</td>\n",
       "      <td>I started crying at 49:01 when Emma's EP showe...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.300000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>jt2OHQh0HoQ</td>\n",
       "      <td>3 years late on wireless charging, 3 years lat...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.026563</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>jt2OHQh0HoQ</td>\n",
       "      <td>more one before to bed</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.500000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>jt2OHQh0HoQ</td>\n",
       "      <td>subscribe me if you love your mummy</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.500000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>jt2OHQh0HoQ</td>\n",
       "      <td>They really just took the samsung s8 and named...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.200000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>jt2OHQh0HoQ</td>\n",
       "      <td>so if someone has a twin sibling both can unlo...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.250000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>jt2OHQh0HoQ</td>\n",
       "      <td>For god sake its better than my ps4pro</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.500000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>jt2OHQh0HoQ</td>\n",
       "      <td>7mp cam what kind of standard is this in 2017?</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.300000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       video_id                                       comment_text  likes  \\\n",
       "0   jt2OHQh0HoQ  It's more accurate to call it the M+ (1000) be...      0   \n",
       "1   jt2OHQh0HoQ              To be there with a samsung phone\\n😂😂😂      1   \n",
       "2   jt2OHQh0HoQ  Thank gosh, a place I can watch it without hav...      0   \n",
       "3   jt2OHQh0HoQ  What happened to the home button on the iPhone...      0   \n",
       "4   jt2OHQh0HoQ  Power is the disease.  Care is the cure.  Keep...      0   \n",
       "5   jt2OHQh0HoQ  Keep calm and buy iphone 8 Keep calm and buy i...      0   \n",
       "6   jt2OHQh0HoQ      i am a big fan of youtube and u !!!!!!!!!!!!!      0   \n",
       "7   jt2OHQh0HoQ  You will never find Losers who line up and pay...      0   \n",
       "8   jt2OHQh0HoQ  *APPLE JUST COMMENTED ON MY LAST VIDEO* I'm cr...      0   \n",
       "9   jt2OHQh0HoQ  I'm only here to see Emma, I love her so much!...      0   \n",
       "10  jt2OHQh0HoQ           Mom said: Just one more video before bed      0   \n",
       "11  jt2OHQh0HoQ                           what is the song?? 39:20      0   \n",
       "12  jt2OHQh0HoQ  I started crying at 49:01 when Emma's EP showe...      0   \n",
       "13  jt2OHQh0HoQ  3 years late on wireless charging, 3 years lat...      0   \n",
       "14  jt2OHQh0HoQ                             more one before to bed      0   \n",
       "15  jt2OHQh0HoQ                subscribe me if you love your mummy      0   \n",
       "16  jt2OHQh0HoQ  They really just took the samsung s8 and named...      0   \n",
       "17  jt2OHQh0HoQ  so if someone has a twin sibling both can unlo...      0   \n",
       "18  jt2OHQh0HoQ             For god sake its better than my ps4pro      0   \n",
       "19  jt2OHQh0HoQ     7mp cam what kind of standard is this in 2017?      0   \n",
       "\n",
       "    replies  Polarity  \n",
       "0         0  0.450000  \n",
       "1         0  0.000000  \n",
       "2         0  0.000000  \n",
       "3         0  0.000000  \n",
       "4         0  1.000000  \n",
       "5         0  0.300000  \n",
       "6         0  0.000000  \n",
       "7         0 -0.100000  \n",
       "8         0  0.028571  \n",
       "9         0  0.500000  \n",
       "10        0  0.500000  \n",
       "11        0  0.000000  \n",
       "12        0  0.300000  \n",
       "13        0  0.026563  \n",
       "14        0  0.500000  \n",
       "15        0  0.500000  \n",
       "16        0  0.200000  \n",
       "17        0  0.250000  \n",
       "18        0  0.500000  \n",
       "19        0  0.300000  "
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "GB_Comments.head(20)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "New data contains only positive polarity having head \n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>video_id</th>\n",
       "      <th>comment_text</th>\n",
       "      <th>likes</th>\n",
       "      <th>replies</th>\n",
       "      <th>Polarity</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>jt2OHQh0HoQ</td>\n",
       "      <td>To be there with a samsung phone\\n😂😂😂</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>jt2OHQh0HoQ</td>\n",
       "      <td>Thank gosh, a place I can watch it without hav...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>jt2OHQh0HoQ</td>\n",
       "      <td>What happened to the home button on the iPhone...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>jt2OHQh0HoQ</td>\n",
       "      <td>i am a big fan of youtube and u !!!!!!!!!!!!!</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>jt2OHQh0HoQ</td>\n",
       "      <td>You will never find Losers who line up and pay...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>-0.100000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>153</th>\n",
       "      <td>YPVcg45W0z4</td>\n",
       "      <td>Tbh I'm probs gonna get Alzheimer's my grandad...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>155</th>\n",
       "      <td>YPVcg45W0z4</td>\n",
       "      <td>Give me a thumbs up down below \\nheu heu heu, ...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>-0.477778</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>157</th>\n",
       "      <td>YPVcg45W0z4</td>\n",
       "      <td>It's mystic Meg all over again</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>159</th>\n",
       "      <td>YPVcg45W0z4</td>\n",
       "      <td>But what about your cola addiction back in the...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>160</th>\n",
       "      <td>YPVcg45W0z4</td>\n",
       "      <td>Now I'm curious about my DNA...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>-0.100000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>100 rows × 5 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "        video_id                                       comment_text  likes  \\\n",
       "1    jt2OHQh0HoQ              To be there with a samsung phone\\n😂😂😂      1   \n",
       "2    jt2OHQh0HoQ  Thank gosh, a place I can watch it without hav...      0   \n",
       "3    jt2OHQh0HoQ  What happened to the home button on the iPhone...      0   \n",
       "6    jt2OHQh0HoQ      i am a big fan of youtube and u !!!!!!!!!!!!!      0   \n",
       "7    jt2OHQh0HoQ  You will never find Losers who line up and pay...      0   \n",
       "..           ...                                                ...    ...   \n",
       "153  YPVcg45W0z4  Tbh I'm probs gonna get Alzheimer's my grandad...      0   \n",
       "155  YPVcg45W0z4  Give me a thumbs up down below \\nheu heu heu, ...      0   \n",
       "157  YPVcg45W0z4                     It's mystic Meg all over again      0   \n",
       "159  YPVcg45W0z4  But what about your cola addiction back in the...      0   \n",
       "160  YPVcg45W0z4                    Now I'm curious about my DNA...      0   \n",
       "\n",
       "     replies  Polarity  \n",
       "1          0  0.000000  \n",
       "2          0  0.000000  \n",
       "3          0  0.000000  \n",
       "6          0  0.000000  \n",
       "7          0 -0.100000  \n",
       "..       ...       ...  \n",
       "153        0  0.000000  \n",
       "155        0 -0.477778  \n",
       "157        0  0.000000  \n",
       "159        0  0.000000  \n",
       "160        0 -0.100000  \n",
       "\n",
       "[100 rows x 5 columns]"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "GB_Comments_Positive_Polarity=GB_Comments[GB_Comments ['Polarity']<=0]\n",
    "print(\"New data contains only positive polarity having head \")\n",
    "GB_Comments_Positive_Polarity.head(100)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "The new data contains (391142, 5) rows and columns respectively\n"
     ]
    }
   ],
   "source": [
    "print(\"The new data contains\", GB_Comments_Positive_Polarity.shape , \"rows and columns respectively\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Requirement already satisfied: wordcloud in c:\\users\\deepanshu\\anaconda3\\lib\\site-packages (1.8.1)\n",
      "Requirement already satisfied: numpy>=1.6.1 in c:\\users\\deepanshu\\anaconda3\\lib\\site-packages (from wordcloud) (1.19.2)\n",
      "Requirement already satisfied: pillow in c:\\users\\deepanshu\\anaconda3\\lib\\site-packages (from wordcloud) (8.0.1)\n",
      "Requirement already satisfied: matplotlib in c:\\users\\deepanshu\\anaconda3\\lib\\site-packages (from wordcloud) (3.3.2)\n",
      "Requirement already satisfied: python-dateutil>=2.1 in c:\\users\\deepanshu\\anaconda3\\lib\\site-packages (from matplotlib->wordcloud) (2.8.1)\n",
      "Requirement already satisfied: certifi>=2020.06.20 in c:\\users\\deepanshu\\anaconda3\\lib\\site-packages (from matplotlib->wordcloud) (2020.6.20)\n",
      "Requirement already satisfied: pyparsing!=2.0.4,!=2.1.2,!=2.1.6,>=2.0.3 in c:\\users\\deepanshu\\anaconda3\\lib\\site-packages (from matplotlib->wordcloud) (2.4.7)\n",
      "Requirement already satisfied: kiwisolver>=1.0.1 in c:\\users\\deepanshu\\anaconda3\\lib\\site-packages (from matplotlib->wordcloud) (1.3.0)\n",
      "Requirement already satisfied: cycler>=0.10 in c:\\users\\deepanshu\\anaconda3\\lib\\site-packages (from matplotlib->wordcloud) (0.10.0)\n",
      "Requirement already satisfied: six>=1.5 in c:\\users\\deepanshu\\anaconda3\\lib\\site-packages (from python-dateutil>=2.1->matplotlib->wordcloud) (1.15.0)\n",
      "The stopwords are used by library as \n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "{'a',\n",
       " 'about',\n",
       " 'above',\n",
       " 'after',\n",
       " 'again',\n",
       " 'against',\n",
       " 'all',\n",
       " 'also',\n",
       " 'am',\n",
       " 'an',\n",
       " 'and',\n",
       " 'any',\n",
       " 'are',\n",
       " \"aren't\",\n",
       " 'as',\n",
       " 'at',\n",
       " 'be',\n",
       " 'because',\n",
       " 'been',\n",
       " 'before',\n",
       " 'being',\n",
       " 'below',\n",
       " 'between',\n",
       " 'both',\n",
       " 'but',\n",
       " 'by',\n",
       " 'can',\n",
       " \"can't\",\n",
       " 'cannot',\n",
       " 'com',\n",
       " 'could',\n",
       " \"couldn't\",\n",
       " 'did',\n",
       " \"didn't\",\n",
       " 'do',\n",
       " 'does',\n",
       " \"doesn't\",\n",
       " 'doing',\n",
       " \"don't\",\n",
       " 'down',\n",
       " 'during',\n",
       " 'each',\n",
       " 'else',\n",
       " 'ever',\n",
       " 'few',\n",
       " 'for',\n",
       " 'from',\n",
       " 'further',\n",
       " 'get',\n",
       " 'had',\n",
       " \"hadn't\",\n",
       " 'has',\n",
       " \"hasn't\",\n",
       " 'have',\n",
       " \"haven't\",\n",
       " 'having',\n",
       " 'he',\n",
       " \"he'd\",\n",
       " \"he'll\",\n",
       " \"he's\",\n",
       " 'hence',\n",
       " 'her',\n",
       " 'here',\n",
       " \"here's\",\n",
       " 'hers',\n",
       " 'herself',\n",
       " 'him',\n",
       " 'himself',\n",
       " 'his',\n",
       " 'how',\n",
       " \"how's\",\n",
       " 'however',\n",
       " 'http',\n",
       " 'i',\n",
       " \"i'd\",\n",
       " \"i'll\",\n",
       " \"i'm\",\n",
       " \"i've\",\n",
       " 'if',\n",
       " 'in',\n",
       " 'into',\n",
       " 'is',\n",
       " \"isn't\",\n",
       " 'it',\n",
       " \"it's\",\n",
       " 'its',\n",
       " 'itself',\n",
       " 'just',\n",
       " 'k',\n",
       " \"let's\",\n",
       " 'like',\n",
       " 'me',\n",
       " 'more',\n",
       " 'most',\n",
       " \"mustn't\",\n",
       " 'my',\n",
       " 'myself',\n",
       " 'no',\n",
       " 'nor',\n",
       " 'not',\n",
       " 'of',\n",
       " 'off',\n",
       " 'on',\n",
       " 'once',\n",
       " 'only',\n",
       " 'or',\n",
       " 'other',\n",
       " 'otherwise',\n",
       " 'ought',\n",
       " 'our',\n",
       " 'ours',\n",
       " 'ourselves',\n",
       " 'out',\n",
       " 'over',\n",
       " 'own',\n",
       " 'r',\n",
       " 'same',\n",
       " 'shall',\n",
       " \"shan't\",\n",
       " 'she',\n",
       " \"she'd\",\n",
       " \"she'll\",\n",
       " \"she's\",\n",
       " 'should',\n",
       " \"shouldn't\",\n",
       " 'since',\n",
       " 'so',\n",
       " 'some',\n",
       " 'such',\n",
       " 'than',\n",
       " 'that',\n",
       " \"that's\",\n",
       " 'the',\n",
       " 'their',\n",
       " 'theirs',\n",
       " 'them',\n",
       " 'themselves',\n",
       " 'then',\n",
       " 'there',\n",
       " \"there's\",\n",
       " 'therefore',\n",
       " 'these',\n",
       " 'they',\n",
       " \"they'd\",\n",
       " \"they'll\",\n",
       " \"they're\",\n",
       " \"they've\",\n",
       " 'this',\n",
       " 'those',\n",
       " 'through',\n",
       " 'to',\n",
       " 'too',\n",
       " 'under',\n",
       " 'until',\n",
       " 'up',\n",
       " 'very',\n",
       " 'was',\n",
       " \"wasn't\",\n",
       " 'we',\n",
       " \"we'd\",\n",
       " \"we'll\",\n",
       " \"we're\",\n",
       " \"we've\",\n",
       " 'were',\n",
       " \"weren't\",\n",
       " 'what',\n",
       " \"what's\",\n",
       " 'when',\n",
       " \"when's\",\n",
       " 'where',\n",
       " \"where's\",\n",
       " 'which',\n",
       " 'while',\n",
       " 'who',\n",
       " \"who's\",\n",
       " 'whom',\n",
       " 'why',\n",
       " \"why's\",\n",
       " 'with',\n",
       " \"won't\",\n",
       " 'would',\n",
       " \"wouldn't\",\n",
       " 'www',\n",
       " 'you',\n",
       " \"you'd\",\n",
       " \"you'll\",\n",
       " \"you're\",\n",
       " \"you've\",\n",
       " 'your',\n",
       " 'yours',\n",
       " 'yourself',\n",
       " 'yourselves'}"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "!pip install wordcloud\n",
    "from wordcloud import WordCloud, STOPWORDS\n",
    "stopwords = set(STOPWORDS)\n",
    "print(\"The stopwords are used by library as \")\n",
    "stopwords"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [],
   "source": [
    "Total_Comments = (' '.join(GB_Comments_Positive_Polarity[\"comment_text\"])).lower()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [],
   "source": [
    "wordcloud = WordCloud(width=1000, height=500, stopwords=stopwords).generate(Total_Comments)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "The plot of wordcloud is \n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "(-0.5, 999.5, 499.5, -0.5)"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "print(\"The plot of wordcloud is \")\n",
    "plt.figure(figsize=(15,5))\n",
    "plt.imshow(wordcloud)\n",
    "plt.axis(\"off\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "The total number of words in positive polarity comments are  4387204\n"
     ]
    }
   ],
   "source": [
    "Total=(' '.join(GB_Comments_Positive_Polarity[\"comment_text\"])).split()\n",
    "a=len(Total)\n",
    "print(\"The total number of words in positive polarity comments are \",a)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "The count of top 100 letters common from stopwords are \n",
      "Word: the, count: 147436\n",
      "Word: i, count: 97957\n",
      "Word: a, count: 95156\n",
      "Word: to, count: 81960\n",
      "Word: and, count: 69981\n",
      "Word: is, count: 69629\n",
      "Word: you, count: 60756\n",
      "Word: this, count: 52764\n",
      "Word: of, count: 51247\n",
      "Word: in, count: 45642\n",
      "Word: that, count: 40737\n",
      "Word: it, count: 39199\n",
      "Word: for, count: 32130\n",
      "Word: on, count: 31568\n",
      "Word: my, count: 30127\n",
      "Word: like, count: 29033\n",
      "Word: was, count: 25462\n",
      "Word: with, count: 23893\n",
      "Word: so, count: 22963\n",
      "Word: are, count: 22357\n",
      "Word: have, count: 21305\n",
      "Word: do, count: 20671\n",
      "Word: not, count: 20362\n",
      "Word: just, count: 20243\n",
      "Word: he, count: 19862\n",
      "Word: your, count: 19605\n",
      "Word: but, count: 19575\n",
      "Word: me, count: 19424\n",
      "Word: what, count: 19084\n",
      "Word: be, count: 18890\n",
      "Word: they, count: 16565\n",
      "Word: at, count: 15886\n",
      "Word: all, count: 15589\n",
      "Word: can, count: 15520\n",
      "Word: if, count: 14701\n",
      "Word: when, count: 13905\n",
      "Word: get, count: 13840\n",
      "Word: or, count: 12645\n",
      "Word: no, count: 12377\n",
      "Word: how, count: 12258\n",
      "Word: about, count: 12184\n",
      "Word: from, count: 12159\n",
      "Word: why, count: 11997\n",
      "Word: i'm, count: 11794\n",
      "Word: as, count: 11401\n",
      "Word: she, count: 10840\n",
      "Word: we, count: 10754\n",
      "Word: out, count: 10527\n",
      "Word: it's, count: 10509\n",
      "Word: who, count: 9911\n",
      "Word: his, count: 9908\n",
      "Word: up, count: 9853\n",
      "Word: don't, count: 9558\n",
      "Word: would, count: 8813\n",
      "Word: an, count: 8665\n",
      "Word: did, count: 8421\n",
      "Word: has, count: 8242\n",
      "Word: her, count: 8217\n",
      "Word: should, count: 8200\n",
      "Word: because, count: 7103\n",
      "Word: only, count: 7005\n",
      "Word: there, count: 6764\n",
      "Word: by, count: 6533\n",
      "Word: where, count: 6523\n",
      "Word: had, count: 6344\n",
      "Word: some, count: 6004\n",
      "Word: been, count: 5840\n",
      "Word: can't, count: 5789\n",
      "Word: these, count: 5566\n",
      "Word: does, count: 5242\n",
      "Word: their, count: 4942\n",
      "Word: am, count: 4921\n",
      "Word: them, count: 4915\n",
      "Word: could, count: 4800\n",
      "Word: its, count: 4777\n",
      "Word: him, count: 4600\n",
      "Word: were, count: 4526\n",
      "Word: then, count: 4459\n",
      "Word: here, count: 4350\n",
      "Word: those, count: 4008\n",
      "Word: same, count: 3941\n",
      "Word: any, count: 3787\n",
      "Word: over, count: 3776\n",
      "Word: that's, count: 3746\n",
      "Word: too, count: 3732\n",
      "Word: didn't, count: 3668\n",
      "Word: other, count: 3629\n",
      "Word: off, count: 3594\n",
      "Word: being, count: 3423\n",
      "Word: before, count: 3401\n",
      "Word: after, count: 3328\n",
      "Word: you're, count: 3279\n",
      "Word: into, count: 3241\n",
      "Word: than, count: 3020\n",
      "Word: ever, count: 2942\n",
      "Word: i've, count: 2872\n",
      "Word: he's, count: 2870\n",
      "Word: also, count: 2779\n",
      "Word: our, count: 2734\n",
      "Word: else, count: 2692\n"
     ]
    }
   ],
   "source": [
    "import collections\n",
    "Common_words = [word for word in Total_Comments.split() if word in stopwords]\n",
    "Count_Common_Words = collections.Counter(Common_words)\n",
    "\n",
    "Common = {}\n",
    "\n",
    "for letter, count in Count_Common_Words.most_common(100):\n",
    "    Common[letter] = count\n",
    "    \n",
    "print(\"The count of top 100 letters common from stopwords are \")\n",
    "    \n",
    "for i,j in Common.items():\n",
    "        print('Word: {0}, count: {1}'.format(i,j))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "The percentage of 100 letters coomon from stopwords are \n",
      "Word: the, count: 3.3605913926044924\n",
      "Word: i, count: 2.2327888103676052\n",
      "Word: a, count: 2.168944047279315\n",
      "Word: to, count: 1.868160222319272\n",
      "Word: and, count: 1.5951161605432524\n",
      "Word: is, count: 1.5870928272311933\n",
      "Word: you, count: 1.3848455645098792\n",
      "Word: this, count: 1.202679428629259\n",
      "Word: of, count: 1.1681015972815487\n",
      "Word: in, count: 1.0403436904233312\n",
      "Word: that, count: 0.9285412759470497\n",
      "Word: it, count: 0.8934847798278812\n",
      "Word: for, count: 0.7323571003308713\n",
      "Word: on, count: 0.7195471193042311\n",
      "Word: my, count: 0.6867015985579882\n",
      "Word: like, count: 0.6617654433210765\n",
      "Word: was, count: 0.5803696386126562\n",
      "Word: with, count: 0.5446065421165736\n",
      "Word: so, count: 0.5234085308091441\n",
      "Word: are, count: 0.5095956331184964\n",
      "Word: have, count: 0.48561680742450086\n",
      "Word: do, count: 0.4711656900385758\n",
      "Word: not, count: 0.46412247982997823\n",
      "Word: just, count: 0.4614100461250491\n",
      "Word: he, count: 0.4527256995571667\n",
      "Word: your, count: 0.4468677544969416\n",
      "Word: but, count: 0.4461839476805729\n",
      "Word: me, count: 0.4427421200381838\n",
      "Word: what, count: 0.4349923094526719\n",
      "Word: be, count: 0.43057035870682103\n",
      "Word: they, count: 0.3775753304382472\n",
      "Word: at, count: 0.3620985028277691\n",
      "Word: all, count: 0.35532881534571903\n",
      "Word: can, count: 0.35375605966807105\n",
      "Word: if, count: 0.3350881335812057\n",
      "Word: when, count: 0.3169444593868897\n",
      "Word: get, count: 0.3154628779514242\n",
      "Word: or, count: 0.2882245730994046\n",
      "Word: no, count: 0.28211589887317756\n",
      "Word: how, count: 0.2794034651682484\n",
      "Word: about, count: 0.27771674168787225\n",
      "Word: from, count: 0.2771469026742317\n",
      "Word: why, count: 0.2734543458658408\n",
      "Word: i'm, count: 0.26882725307507926\n",
      "Word: as, count: 0.25986938378064933\n",
      "Word: she, count: 0.2470821963145548\n",
      "Word: we, count: 0.24512195010763121\n",
      "Word: out, count: 0.23994781186377473\n",
      "Word: it's, count: 0.23953752777395354\n",
      "Word: who, count: 0.2259069785676709\n",
      "Word: his, count: 0.22583859788603403\n",
      "Word: up, count: 0.22458495205602474\n",
      "Word: don't, count: 0.21786085169506592\n",
      "Word: would, count: 0.20087964908857667\n",
      "Word: an, count: 0.19750620212782444\n",
      "Word: did, count: 0.19194457335469242\n",
      "Word: has, count: 0.18786452601702588\n",
      "Word: her, count: 0.1872946870033853\n",
      "Word: should, count: 0.1869071964741097\n",
      "Word: because, count: 0.16190266055556113\n",
      "Word: only, count: 0.15966889162209005\n",
      "Word: there, count: 0.15417564353059487\n",
      "Word: by, count: 0.14891033104455592\n",
      "Word: where, count: 0.14868239543909972\n",
      "Word: had, count: 0.14460234810143316\n",
      "Word: some, count: 0.1368525375159213\n",
      "Word: been, count: 0.13311439358643912\n",
      "Word: can't, count: 0.13195192199861233\n",
      "Word: these, count: 0.12686895799693837\n",
      "Word: does, count: 0.11948384438015647\n",
      "Word: their, count: 0.11264577621646953\n",
      "Word: am, count: 0.11216711144501144\n",
      "Word: them, count: 0.11203035008173771\n",
      "Word: could, count: 0.10940909061899105\n",
      "Word: its, count: 0.10888483872644171\n",
      "Word: him, count: 0.10485037850986642\n",
      "Word: were, count: 0.1031636550294903\n",
      "Word: then, count: 0.10163648647293355\n",
      "Word: here, count: 0.09915198837346063\n",
      "Word: those, count: 0.09135659066685753\n",
      "Word: same, count: 0.08982942211030077\n",
      "Word: any, count: 0.08631921378627481\n",
      "Word: over, count: 0.08606848462027296\n",
      "Word: that's, count: 0.08538467780390425\n",
      "Word: too, count: 0.08506556795626553\n",
      "Word: didn't, count: 0.08360678008134566\n",
      "Word: other, count: 0.08271783122006636\n",
      "Word: off, count: 0.08192005660096954\n",
      "Word: being, count: 0.07802235774766798\n",
      "Word: before, count: 0.07752089941566428\n",
      "Word: after, count: 0.07585696949583379\n",
      "Word: you're, count: 0.07474008502909825\n",
      "Word: into, count: 0.07387392972836458\n",
      "Word: than, count: 0.06883655284778187\n",
      "Word: ever, count: 0.06705865512522326\n",
      "Word: i've, count: 0.06546310588702965\n",
      "Word: he's, count: 0.0654175187659384\n",
      "Word: also, count: 0.06334330475628669\n",
      "Word: our, count: 0.06231759453173365\n",
      "Word: else, count: 0.061360264988817484\n"
     ]
    }
   ],
   "source": [
    "Common_words = [word for word in Total_Comments.split() if word in stopwords]\n",
    "Count_Common_Words = collections.Counter(Common_words)\n",
    "\n",
    "Common = {}\n",
    "\n",
    "for letter, count in Count_Common_Words.most_common(100):\n",
    "    Common[letter] = (count/a)*100\n",
    "    \n",
    "print(\"The percentage of 100 letters coomon from stopwords are \")\n",
    "    \n",
    "for i,j in Common.items():\n",
    "        print('Word: {0}, count: {1}'.format(i,j))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "The count of top 100 letters which are not in stopwords are \n",
      "Word: one, count: 11783\n",
      "Word: video, count: 9906\n",
      "Word: make, count: 9776\n",
      "Word: people, count: 9493\n",
      "Word: will, count: 8975\n",
      "Word: know, count: 8812\n",
      "Word: please, count: 7579\n",
      "Word: see, count: 7383\n",
      "Word: got, count: 7195\n",
      "Word: want, count: 6845\n",
      "Word: fuck, count: 6702\n",
      "Word: think, count: 6587\n",
      "Word: go, count: 6471\n",
      "Word: u, count: 6189\n",
      "Word: fucking, count: 6131\n",
      "Word: now, count: 5940\n",
      "Word: look, count: 5824\n",
      "Word: need, count: 5823\n",
      "Word: shit, count: 5724\n",
      "Word: going, count: 5698\n",
      "Word: even, count: 5694\n",
      "Word: looks, count: 5533\n",
      "Word: time, count: 5326\n",
      "Word: song, count: 5208\n",
      "Word: still, count: 5188\n",
      "Word: never, count: 4991\n",
      "Word: back, count: 4830\n",
      "Word: bad, count: 4490\n",
      "Word: que, count: 4397\n",
      "Word: really, count: 4383\n",
      "Word: de, count: 4374\n",
      "Word: watch, count: 4352\n",
      "Word: say, count: 4198\n",
      "Word: feel, count: 3988\n",
      "Word: anyone, count: 3972\n",
      "Word: omg, count: 3865\n",
      "Word: always, count: 3860\n",
      "Word: thought, count: 3859\n",
      "Word: man, count: 3788\n",
      "Word: trending, count: 3744\n",
      "Word: made, count: 3736\n",
      "Word: come, count: 3681\n",
      "Word: every, count: 3665\n",
      "Word: 😂, count: 3659\n",
      "Word: way, count: 3655\n",
      "Word: game, count: 3590\n",
      "Word: something, count: 3588\n",
      "Word: guy, count: 3575\n",
      "Word: hate, count: 3485\n",
      "Word: oh, count: 3394\n",
      "Word: little, count: 3353\n",
      "Word: -, count: 3343\n",
      "Word: said, count: 3336\n",
      "Word: take, count: 3319\n",
      "Word: la, count: 3317\n",
      "Word: black, count: 3313\n",
      "Word: im, count: 3278\n",
      "Word: it., count: 3212\n",
      "Word: stop, count: 3191\n",
      "Word: watching, count: 3083\n",
      "Word: thank, count: 3060\n",
      "Word: put, count: 3055\n",
      "Word: guys, count: 3025\n",
      "Word: y, count: 2988\n",
      "Word: ͡°, count: 2987\n",
      "Word: god, count: 2969\n",
      "Word: someone, count: 2966\n",
      "Word: actually, count: 2930\n",
      "Word: 2, count: 2930\n",
      "Word: thing, count: 2921\n",
      "Word: gonna, count: 2917\n",
      "Word: well, count: 2866\n",
      "Word: us, count: 2853\n",
      "Word: wait, count: 2852\n",
      "Word: white, count: 2847\n",
      "Word: movie, count: 2841\n",
      "Word: last, count: 2788\n",
      "Word: life, count: 2788\n",
      "Word: ?, count: 2786\n",
      "Word: use, count: 2764\n",
      "Word: give, count: 2763\n",
      "Word: next, count: 2740\n",
      "Word: big, count: 2693\n",
      "Word: wiggle, count: 2686\n",
      "Word: show, count: 2678\n",
      "Word: try, count: 2641\n",
      "Word: el, count: 2634\n",
      "Word: day, count: 2614\n",
      "Word: wiggle\\n, count: 2597\n",
      "Word: ,, count: 2565\n",
      "Word: music, count: 2527\n",
      "Word: keep, count: 2473\n",
      "Word: love, count: 2439\n",
      "Word: wrong, count: 2409\n",
      "Word: tell, count: 2396\n",
      "Word: getting, count: 2375\n",
      "Word: makes, count: 2371\n",
      "Word: videos, count: 2360\n",
      "Word: another, count: 2360\n",
      "Word: much, count: 2337\n"
     ]
    }
   ],
   "source": [
    "Common_words = [word for word in Total_Comments.split() if word not in stopwords]\n",
    "Count_Common_Words = collections.Counter(Common_words)\n",
    "\n",
    "Common = {}\n",
    "\n",
    "for letter, count in Count_Common_Words.most_common(100):\n",
    "    Common[letter] = count\n",
    "    \n",
    "print(\"The count of top 100 letters which are not in stopwords are \")\n",
    "    \n",
    "for i,j in Common.items():\n",
    "        print('Word: {0}, count: {1}'.format(i,j))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "The percentage of top 100 letters not in stopwords are \n",
      "Word: one, count: 0.26857652390907744\n",
      "Word: video, count: 0.22579301076494276\n",
      "Word: make, count: 0.22282984789401178\n",
      "Word: people, count: 0.21637927025960044\n",
      "Word: will, count: 0.20457220589696762\n",
      "Word: know, count: 0.20085685552803106\n",
      "Word: please, count: 0.17275239537527773\n",
      "Word: see, count: 0.1682848575083356\n",
      "Word: got, count: 0.16399966812575845\n",
      "Word: want, count: 0.15602192193479036\n",
      "Word: fuck, count: 0.15276244277676623\n",
      "Word: think, count: 0.1501411833140196\n",
      "Word: go, count: 0.1474971302907273\n",
      "Word: u, count: 0.1410693462168616\n",
      "Word: fucking, count: 0.13974731970521542\n",
      "Word: now, count: 0.13539374964100143\n",
      "Word: look, count: 0.13274969661770913\n",
      "Word: need, count: 0.1327269030571635\n",
      "Word: shit, count: 0.13047034056314682\n",
      "Word: going, count: 0.12987770798896064\n",
      "Word: even, count: 0.12978653374677815\n",
      "Word: looks, count: 0.1261167704989328\n",
      "Word: time, count: 0.12139850346598881\n",
      "Word: song, count: 0.1187088633216053\n",
      "Word: still, count: 0.11825299211069282\n",
      "Word: never, count: 0.11376266068320506\n",
      "Word: back, count: 0.11009289743535976\n",
      "Word: bad, count: 0.10234308684984787\n",
      "Word: que, count: 0.10022328571910492\n",
      "Word: really, count: 0.0999041758714662\n",
      "Word: de, count: 0.0996990338265556\n",
      "Word: watch, count: 0.09919757549455188\n",
      "Word: say, count: 0.09568736717052592\n",
      "Word: feel, count: 0.09090071945594506\n",
      "Word: anyone, count: 0.09053602248721508\n",
      "Word: omg, count: 0.08809711150883343\n",
      "Word: always, count: 0.0879831437061053\n",
      "Word: thought, count: 0.08796035014555967\n",
      "Word: man, count: 0.08634200734682043\n",
      "Word: trending, count: 0.08533909068281302\n",
      "Word: made, count: 0.08515674219844803\n",
      "Word: come, count: 0.08390309636843875\n",
      "Word: every, count: 0.08353839939970878\n",
      "Word: 😂, count: 0.08340163803643505\n",
      "Word: way, count: 0.08331046379425257\n",
      "Word: game, count: 0.08182888235878706\n",
      "Word: something, count: 0.08178329523769581\n",
      "Word: guy, count: 0.08148697895060271\n",
      "Word: hate, count: 0.07943555850149663\n",
      "Word: oh, count: 0.07736134449184492\n",
      "Word: little, count: 0.07642680850947436\n",
      "Word: -, count: 0.07619887290401814\n",
      "Word: said, count: 0.07603931798019878\n",
      "Word: take, count: 0.07565182745092318\n",
      "Word: la, count: 0.07560624032983194\n",
      "Word: black, count: 0.07551506608764945\n",
      "Word: im, count: 0.07471729146855263\n",
      "Word: it., count: 0.07321291647254151\n",
      "Word: stop, count: 0.07273425170108343\n",
      "Word: watching, count: 0.07027254716215613\n",
      "Word: thank, count: 0.06974829526960678\n",
      "Word: put, count: 0.06963432746687867\n",
      "Word: guys, count: 0.06895052065050998\n",
      "Word: y, count: 0.06810715891032192\n",
      "Word: ͡°, count: 0.0680843653497763\n",
      "Word: god, count: 0.0676740812599551\n",
      "Word: someone, count: 0.06760570057831822\n",
      "Word: actually, count: 0.06678513239867578\n",
      "Word: 2, count: 0.06678513239867578\n",
      "Word: thing, count: 0.06657999035376518\n",
      "Word: gonna, count: 0.06648881611158268\n",
      "Word: well, count: 0.06532634452375591\n",
      "Word: us, count: 0.0650300282366628\n",
      "Word: wait, count: 0.06500723467611717\n",
      "Word: white, count: 0.06489326687338907\n",
      "Word: movie, count: 0.06475650551011533\n",
      "Word: last, count: 0.0635484468011973\n",
      "Word: life, count: 0.0635484468011973\n",
      "Word: ?, count: 0.06350285968010605\n",
      "Word: use, count: 0.06300140134810234\n",
      "Word: give, count: 0.06297860778755672\n",
      "Word: next, count: 0.06245435589500739\n",
      "Word: big, count: 0.0613830585493631\n",
      "Word: wiggle, count: 0.06122350362554374\n",
      "Word: show, count: 0.061041155141178756\n",
      "Word: try, count: 0.060197793400990705\n",
      "Word: el, count: 0.06003823847717134\n",
      "Word: day, count: 0.05958236726625887\n",
      "Word: wiggle\\n, count: 0.05919487673698329\n",
      "Word: ,, count: 0.05846548279952334\n",
      "Word: music, count: 0.05759932749878966\n",
      "Word: keep, count: 0.05636847522932601\n",
      "Word: love, count: 0.055593494170774825\n",
      "Word: wrong, count: 0.05490968735440613\n",
      "Word: tell, count: 0.05461337106731303\n",
      "Word: getting, count: 0.05413470629585495\n",
      "Word: makes, count: 0.05404353205367246\n",
      "Word: videos, count: 0.0537928028876706\n",
      "Word: another, count: 0.0537928028876706\n",
      "Word: much, count: 0.05326855099512126\n"
     ]
    }
   ],
   "source": [
    "Common_words = [word for word in Total_Comments.split() if word not in stopwords]\n",
    "Count_Common_Words = collections.Counter(Common_words)\n",
    "\n",
    "Common = {}\n",
    "\n",
    "for letter, count in Count_Common_Words.most_common(100):\n",
    "    Common[letter] = (count/a)*100\n",
    "    \n",
    "print(\"The percentage of top 100 letters not in stopwords are \")\n",
    "    \n",
    "for i,j in Common.items():\n",
    "        print('Word: {0}, count: {1}'.format(i,j))"
   ]
  }
 ],
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