WeRateDogs.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "fdc70b74",
   "metadata": {},
   "outputs": [],
   "source": [
    "#pip install tweepy"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "6edcd620",
   "metadata": {},
   "outputs": [],
   "source": [
    "import tweepy\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import requests\n",
    "from tweepy import OAuthHandler\n",
    "import json\n",
    "from timeit import default_timer as timer\n",
    "import re"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "6b311058",
   "metadata": {},
   "outputs": [],
   "source": [
    "#pip install matplotlib"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "ae8b277f",
   "metadata": {},
   "outputs": [],
   "source": [
    "url = 'https://d17h27t6h515a5.cloudfront.net/topher/2017/August/599fd2ad_image-predictions/image-predictions.tsv'\n",
    "response = requests.get(url)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "1f09d81b",
   "metadata": {},
   "outputs": [],
   "source": [
    "with open((url.split('/')[-1]), mode='wb') as file:\n",
    "    file.write(response.content)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "93a4721e",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>tweet_id</th>\n",
       "      <th>jpg_url</th>\n",
       "      <th>img_num</th>\n",
       "      <th>p1</th>\n",
       "      <th>p1_conf</th>\n",
       "      <th>p1_dog</th>\n",
       "      <th>p2</th>\n",
       "      <th>p2_conf</th>\n",
       "      <th>p2_dog</th>\n",
       "      <th>p3</th>\n",
       "      <th>p3_conf</th>\n",
       "      <th>p3_dog</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>666020888022790149</td>\n",
       "      <td>https://pbs.twimg.com/media/CT4udn0WwAA0aMy.jpg</td>\n",
       "      <td>1</td>\n",
       "      <td>Welsh_springer_spaniel</td>\n",
       "      <td>0.465074</td>\n",
       "      <td>True</td>\n",
       "      <td>collie</td>\n",
       "      <td>0.156665</td>\n",
       "      <td>True</td>\n",
       "      <td>Shetland_sheepdog</td>\n",
       "      <td>0.061428</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>666029285002620928</td>\n",
       "      <td>https://pbs.twimg.com/media/CT42GRgUYAA5iDo.jpg</td>\n",
       "      <td>1</td>\n",
       "      <td>redbone</td>\n",
       "      <td>0.506826</td>\n",
       "      <td>True</td>\n",
       "      <td>miniature_pinscher</td>\n",
       "      <td>0.074192</td>\n",
       "      <td>True</td>\n",
       "      <td>Rhodesian_ridgeback</td>\n",
       "      <td>0.072010</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>666033412701032449</td>\n",
       "      <td>https://pbs.twimg.com/media/CT4521TWwAEvMyu.jpg</td>\n",
       "      <td>1</td>\n",
       "      <td>German_shepherd</td>\n",
       "      <td>0.596461</td>\n",
       "      <td>True</td>\n",
       "      <td>malinois</td>\n",
       "      <td>0.138584</td>\n",
       "      <td>True</td>\n",
       "      <td>bloodhound</td>\n",
       "      <td>0.116197</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>666044226329800704</td>\n",
       "      <td>https://pbs.twimg.com/media/CT5Dr8HUEAA-lEu.jpg</td>\n",
       "      <td>1</td>\n",
       "      <td>Rhodesian_ridgeback</td>\n",
       "      <td>0.408143</td>\n",
       "      <td>True</td>\n",
       "      <td>redbone</td>\n",
       "      <td>0.360687</td>\n",
       "      <td>True</td>\n",
       "      <td>miniature_pinscher</td>\n",
       "      <td>0.222752</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>666049248165822465</td>\n",
       "      <td>https://pbs.twimg.com/media/CT5IQmsXIAAKY4A.jpg</td>\n",
       "      <td>1</td>\n",
       "      <td>miniature_pinscher</td>\n",
       "      <td>0.560311</td>\n",
       "      <td>True</td>\n",
       "      <td>Rottweiler</td>\n",
       "      <td>0.243682</td>\n",
       "      <td>True</td>\n",
       "      <td>Doberman</td>\n",
       "      <td>0.154629</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "             tweet_id                                          jpg_url  \\\n",
       "0  666020888022790149  https://pbs.twimg.com/media/CT4udn0WwAA0aMy.jpg   \n",
       "1  666029285002620928  https://pbs.twimg.com/media/CT42GRgUYAA5iDo.jpg   \n",
       "2  666033412701032449  https://pbs.twimg.com/media/CT4521TWwAEvMyu.jpg   \n",
       "3  666044226329800704  https://pbs.twimg.com/media/CT5Dr8HUEAA-lEu.jpg   \n",
       "4  666049248165822465  https://pbs.twimg.com/media/CT5IQmsXIAAKY4A.jpg   \n",
       "\n",
       "   img_num                      p1   p1_conf  p1_dog                  p2  \\\n",
       "0        1  Welsh_springer_spaniel  0.465074    True              collie   \n",
       "1        1                 redbone  0.506826    True  miniature_pinscher   \n",
       "2        1         German_shepherd  0.596461    True            malinois   \n",
       "3        1     Rhodesian_ridgeback  0.408143    True             redbone   \n",
       "4        1      miniature_pinscher  0.560311    True          Rottweiler   \n",
       "\n",
       "    p2_conf  p2_dog                   p3   p3_conf  p3_dog  \n",
       "0  0.156665    True    Shetland_sheepdog  0.061428    True  \n",
       "1  0.074192    True  Rhodesian_ridgeback  0.072010    True  \n",
       "2  0.138584    True           bloodhound  0.116197    True  \n",
       "3  0.360687    True   miniature_pinscher  0.222752    True  \n",
       "4  0.243682    True             Doberman  0.154629    True  "
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dog_pred = pd.read_csv('image-predictions.tsv', sep='\\t')\n",
    "\n",
    "dog_pred.head(5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "8bce1ebc",
   "metadata": {},
   "outputs": [],
   "source": [
    "API_key = '***'\n",
    "API_key_secret = '***'\n",
    "access_token = '***'\n",
    "access_token_secret = '***'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "f4a8fe47",
   "metadata": {},
   "outputs": [],
   "source": [
    "import tweepy\n",
    "\n",
    "\n",
    "auth = tweepy.OAuthHandler(API_key, API_key_secret)\n",
    "auth.set_access_token(access_token, access_token_secret)\n",
    "\n",
    "api = tweepy.API(auth, wait_on_rate_limit=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "d3ca25fd",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
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     "text": [
      "Rate limit reached. Sleeping for: 278\n"
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      "1800: 831670449226514432\n",
      "Success\n",
      "1801: 831911600680497154\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Rate limit reached. Sleeping for: 282\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Success\n",
      "1802: 831939777352105988\n",
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     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Success\n",
      "2052: 887473957103951883\n",
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      "Success\n",
      "1995.8494647\n",
      "{680055455951884288: NotFound('404 Not Found\\n144 - No status found with that ID.'), 754011816964026368: NotFound('404 Not Found\\n144 - No status found with that ID.'), 759566828574212096: NotFound('404 Not Found\\n144 - No status found with that ID.'), 759923798737051648: NotFound('404 Not Found\\n144 - No status found with that ID.'), 771004394259247104: Forbidden('403 Forbidden\\n179 - Sorry, you are not authorized to see this status.'), 779123168116150273: NotFound('404 Not Found\\n144 - No status found with that ID.'), 802247111496568832: NotFound('404 Not Found\\n144 - No status found with that ID.'), 829374341691346946: NotFound('404 Not Found\\n144 - No status found with that ID.'), 837012587749474308: NotFound('404 Not Found\\n144 - No status found with that ID.'), 837366284874571778: NotFound('404 Not Found\\n144 - No status found with that ID.'), 842892208864923648: NotFound('404 Not Found\\n144 - No status found with that ID.'), 844704788403113984: NotFound('404 Not Found\\n144 - No status found with that ID.'), 851861385021730816: NotFound('404 Not Found\\n144 - No status found with that ID.'), 851953902622658560: NotFound('404 Not Found\\n144 - No status found with that ID.'), 861769973181624320: NotFound('404 Not Found\\n144 - No status found with that ID.'), 872261713294495745: NotFound('404 Not Found\\n144 - No status found with that ID.'), 873697596434513921: NotFound('404 Not Found\\n144 - No status found with that ID.'), 888202515573088257: NotFound('404 Not Found\\n144 - No status found with that ID.')}\n"
     ]
    }
   ],
   "source": [
    "tweet_ids = dog_pred.tweet_id.values\n",
    "len(tweet_ids)\n",
    "\n",
    "\n",
    "# Query Twitter's API for JSON data for each tweet ID in the Twitter archive\n",
    "count = 0\n",
    "fails_dict = {}\n",
    "start = timer()\n",
    "# Save each tweet's returned JSON as a new line in a .txt file\n",
    "with open('tweet_json.txt', 'w') as outfile:\n",
    "    # This loop will likely take 20-30 minutes to run because of Twitter's rate limit\n",
    "    for tweet_id in tweet_ids:\n",
    "        count += 1\n",
    "        print(str(count) + \": \" + str(tweet_id))\n",
    "        try:\n",
    "            tweet = api.get_status(tweet_id, tweet_mode='extended')\n",
    "            print(\"Success\")\n",
    "            json.dump(tweet._json, outfile)\n",
    "            outfile.write('\\n')\n",
    "        except Exception as e:\n",
    "            print(\"Fail\")\n",
    "            fails_dict[tweet_id] = e\n",
    "            pass\n",
    "end = timer()\n",
    "print(end - start)\n",
    "print(fails_dict)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d1bcae67",
   "metadata": {},
   "source": [
    "**The above scraping was unable to complete due to permission error. Twitter app was later suspended, so i couldn't create the necessary read and write permission**"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3e64b8d9",
   "metadata": {},
   "source": [
    "Using the JSON-txt provided"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "bb840be2",
   "metadata": {},
   "outputs": [],
   "source": [
    "url_txt = \"https://video.udacity-data.com/topher/2018/November/5be5fb7d_tweet-json/tweet-json.txt\"\n",
    "response_json = requests.get(url_txt)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "45ef6c2a",
   "metadata": {},
   "outputs": [],
   "source": [
    "import os\n",
    "foldername = 'tweet_json'\n",
    "if not os.path.exists(foldername):\n",
    "    os.makedirs(foldername)\n",
    "    \n",
    "with open(os.path.join(foldername, url_txt.split('/')[-1]), mode='wb') as file:\n",
    "    file.write(response_json.content)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "c891174a",
   "metadata": {},
   "outputs": [],
   "source": [
    "# reading the Json.txt file line by line into pandas DataFrame with tweet_id, retweet_count and favorite_count\n",
    "\n",
    "df = []\n",
    "\n",
    "for tweet_txt in os.listdir(foldername):\n",
    "    with open(os.path.join(foldername, tweet_txt), 'r') as json_file:\n",
    "        for line in json_file:\n",
    "            tweet = json.loads(line)\n",
    "            tweet_id = tweet['id']\n",
    "            retweet_count = tweet['retweet_count']\n",
    "            favorite_count = tweet['favorite_count']\n",
    "            create_date = tweet['created_at']\n",
    "            df.append({'retweet_count': retweet_count,\n",
    "                      'favorite_count':favorite_count,\n",
    "                      'create_date':create_date,\n",
    "                      'tweet_id':tweet_id})\n",
    "            \n",
    "# storing in a dataframe\n",
    "Tweet_data = pd.DataFrame(df, columns = ['tweet_id', 'retweet_count', 'favorite_count', 'create_date'])\n",
    "        "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "3f0dc7e8",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>tweet_id</th>\n",
       "      <th>retweet_count</th>\n",
       "      <th>favorite_count</th>\n",
       "      <th>create_date</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>892420643555336193</td>\n",
       "      <td>8853</td>\n",
       "      <td>39467</td>\n",
       "      <td>Tue Aug 01 16:23:56 +0000 2017</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>892177421306343426</td>\n",
       "      <td>6514</td>\n",
       "      <td>33819</td>\n",
       "      <td>Tue Aug 01 00:17:27 +0000 2017</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>891815181378084864</td>\n",
       "      <td>4328</td>\n",
       "      <td>25461</td>\n",
       "      <td>Mon Jul 31 00:18:03 +0000 2017</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>891689557279858688</td>\n",
       "      <td>8964</td>\n",
       "      <td>42908</td>\n",
       "      <td>Sun Jul 30 15:58:51 +0000 2017</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>891327558926688256</td>\n",
       "      <td>9774</td>\n",
       "      <td>41048</td>\n",
       "      <td>Sat Jul 29 16:00:24 +0000 2017</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "             tweet_id  retweet_count  favorite_count  \\\n",
       "0  892420643555336193           8853           39467   \n",
       "1  892177421306343426           6514           33819   \n",
       "2  891815181378084864           4328           25461   \n",
       "3  891689557279858688           8964           42908   \n",
       "4  891327558926688256           9774           41048   \n",
       "\n",
       "                      create_date  \n",
       "0  Tue Aug 01 16:23:56 +0000 2017  \n",
       "1  Tue Aug 01 00:17:27 +0000 2017  \n",
       "2  Mon Jul 31 00:18:03 +0000 2017  \n",
       "3  Sun Jul 30 15:58:51 +0000 2017  \n",
       "4  Sat Jul 29 16:00:24 +0000 2017  "
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Tweet_data.head(5)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6c7bfb6b",
   "metadata": {},
   "source": [
    "Reading in the twitter-archive-enhanced.csv data using pandas"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "d8cc321b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>tweet_id</th>\n",
       "      <th>in_reply_to_status_id</th>\n",
       "      <th>in_reply_to_user_id</th>\n",
       "      <th>timestamp</th>\n",
       "      <th>source</th>\n",
       "      <th>text</th>\n",
       "      <th>retweeted_status_id</th>\n",
       "      <th>retweeted_status_user_id</th>\n",
       "      <th>retweeted_status_timestamp</th>\n",
       "      <th>expanded_urls</th>\n",
       "      <th>rating_numerator</th>\n",
       "      <th>rating_denominator</th>\n",
       "      <th>name</th>\n",
       "      <th>doggo</th>\n",
       "      <th>floofer</th>\n",
       "      <th>pupper</th>\n",
       "      <th>puppo</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>892420643555336193</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2017-08-01 16:23:56 +0000</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>This is Phineas. He's a mystical boy. Only eve...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>https://twitter.com/dog_rates/status/892420643...</td>\n",
       "      <td>13</td>\n",
       "      <td>10</td>\n",
       "      <td>Phineas</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>892177421306343426</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2017-08-01 00:17:27 +0000</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>This is Tilly. She's just checking pup on you....</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>https://twitter.com/dog_rates/status/892177421...</td>\n",
       "      <td>13</td>\n",
       "      <td>10</td>\n",
       "      <td>Tilly</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>891815181378084864</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2017-07-31 00:18:03 +0000</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>This is Archie. He is a rare Norwegian Pouncin...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>https://twitter.com/dog_rates/status/891815181...</td>\n",
       "      <td>12</td>\n",
       "      <td>10</td>\n",
       "      <td>Archie</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "             tweet_id  in_reply_to_status_id  in_reply_to_user_id  \\\n",
       "0  892420643555336193                    NaN                  NaN   \n",
       "1  892177421306343426                    NaN                  NaN   \n",
       "2  891815181378084864                    NaN                  NaN   \n",
       "\n",
       "                   timestamp  \\\n",
       "0  2017-08-01 16:23:56 +0000   \n",
       "1  2017-08-01 00:17:27 +0000   \n",
       "2  2017-07-31 00:18:03 +0000   \n",
       "\n",
       "                                              source  \\\n",
       "0  <a href=\"http://twitter.com/download/iphone\" r...   \n",
       "1  <a href=\"http://twitter.com/download/iphone\" r...   \n",
       "2  <a href=\"http://twitter.com/download/iphone\" r...   \n",
       "\n",
       "                                                text  retweeted_status_id  \\\n",
       "0  This is Phineas. He's a mystical boy. Only eve...                  NaN   \n",
       "1  This is Tilly. She's just checking pup on you....                  NaN   \n",
       "2  This is Archie. He is a rare Norwegian Pouncin...                  NaN   \n",
       "\n",
       "   retweeted_status_user_id retweeted_status_timestamp  \\\n",
       "0                       NaN                        NaN   \n",
       "1                       NaN                        NaN   \n",
       "2                       NaN                        NaN   \n",
       "\n",
       "                                       expanded_urls  rating_numerator  \\\n",
       "0  https://twitter.com/dog_rates/status/892420643...                13   \n",
       "1  https://twitter.com/dog_rates/status/892177421...                13   \n",
       "2  https://twitter.com/dog_rates/status/891815181...                12   \n",
       "\n",
       "   rating_denominator     name doggo floofer pupper puppo  \n",
       "0                  10  Phineas  None    None   None  None  \n",
       "1                  10    Tilly  None    None   None  None  \n",
       "2                  10   Archie  None    None   None  None  "
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Twitter_archive = pd.read_csv('twitter-archive-enhanced.csv')\n",
    "Twitter_archive.head(3)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "55f63fd6",
   "metadata": {},
   "source": [
    "## Assessing the Data"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "8f0ebebd",
   "metadata": {},
   "source": [
    "### **Visual assessment**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "0b0394a5",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "    }\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>tweet_id</th>\n",
       "      <th>jpg_url</th>\n",
       "      <th>img_num</th>\n",
       "      <th>p1</th>\n",
       "      <th>p1_conf</th>\n",
       "      <th>p1_dog</th>\n",
       "      <th>p2</th>\n",
       "      <th>p2_conf</th>\n",
       "      <th>p2_dog</th>\n",
       "      <th>p3</th>\n",
       "      <th>p3_conf</th>\n",
       "      <th>p3_dog</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>666020888022790149</td>\n",
       "      <td>https://pbs.twimg.com/media/CT4udn0WwAA0aMy.jpg</td>\n",
       "      <td>1</td>\n",
       "      <td>Welsh_springer_spaniel</td>\n",
       "      <td>0.465074</td>\n",
       "      <td>True</td>\n",
       "      <td>collie</td>\n",
       "      <td>0.156665</td>\n",
       "      <td>True</td>\n",
       "      <td>Shetland_sheepdog</td>\n",
       "      <td>0.061428</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>666029285002620928</td>\n",
       "      <td>https://pbs.twimg.com/media/CT42GRgUYAA5iDo.jpg</td>\n",
       "      <td>1</td>\n",
       "      <td>redbone</td>\n",
       "      <td>0.506826</td>\n",
       "      <td>True</td>\n",
       "      <td>miniature_pinscher</td>\n",
       "      <td>0.074192</td>\n",
       "      <td>True</td>\n",
       "      <td>Rhodesian_ridgeback</td>\n",
       "      <td>0.072010</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>666033412701032449</td>\n",
       "      <td>https://pbs.twimg.com/media/CT4521TWwAEvMyu.jpg</td>\n",
       "      <td>1</td>\n",
       "      <td>German_shepherd</td>\n",
       "      <td>0.596461</td>\n",
       "      <td>True</td>\n",
       "      <td>malinois</td>\n",
       "      <td>0.138584</td>\n",
       "      <td>True</td>\n",
       "      <td>bloodhound</td>\n",
       "      <td>0.116197</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>666044226329800704</td>\n",
       "      <td>https://pbs.twimg.com/media/CT5Dr8HUEAA-lEu.jpg</td>\n",
       "      <td>1</td>\n",
       "      <td>Rhodesian_ridgeback</td>\n",
       "      <td>0.408143</td>\n",
       "      <td>True</td>\n",
       "      <td>redbone</td>\n",
       "      <td>0.360687</td>\n",
       "      <td>True</td>\n",
       "      <td>miniature_pinscher</td>\n",
       "      <td>0.222752</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>666049248165822465</td>\n",
       "      <td>https://pbs.twimg.com/media/CT5IQmsXIAAKY4A.jpg</td>\n",
       "      <td>1</td>\n",
       "      <td>miniature_pinscher</td>\n",
       "      <td>0.560311</td>\n",
       "      <td>True</td>\n",
       "      <td>Rottweiler</td>\n",
       "      <td>0.243682</td>\n",
       "      <td>True</td>\n",
       "      <td>Doberman</td>\n",
       "      <td>0.154629</td>\n",
       "      <td>True</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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2070</th>\n",
       "      <td>891327558926688256</td>\n",
       "      <td>https://pbs.twimg.com/media/DF6hr6BUMAAzZgT.jpg</td>\n",
       "      <td>2</td>\n",
       "      <td>basset</td>\n",
       "      <td>0.555712</td>\n",
       "      <td>True</td>\n",
       "      <td>English_springer</td>\n",
       "      <td>0.225770</td>\n",
       "      <td>True</td>\n",
       "      <td>German_short-haired_pointer</td>\n",
       "      <td>0.175219</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2071</th>\n",
       "      <td>891689557279858688</td>\n",
       "      <td>https://pbs.twimg.com/media/DF_q7IAWsAEuuN8.jpg</td>\n",
       "      <td>1</td>\n",
       "      <td>paper_towel</td>\n",
       "      <td>0.170278</td>\n",
       "      <td>False</td>\n",
       "      <td>Labrador_retriever</td>\n",
       "      <td>0.168086</td>\n",
       "      <td>True</td>\n",
       "      <td>spatula</td>\n",
       "      <td>0.040836</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2072</th>\n",
       "      <td>891815181378084864</td>\n",
       "      <td>https://pbs.twimg.com/media/DGBdLU1WsAANxJ9.jpg</td>\n",
       "      <td>1</td>\n",
       "      <td>Chihuahua</td>\n",
       "      <td>0.716012</td>\n",
       "      <td>True</td>\n",
       "      <td>malamute</td>\n",
       "      <td>0.078253</td>\n",
       "      <td>True</td>\n",
       "      <td>kelpie</td>\n",
       "      <td>0.031379</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2073</th>\n",
       "      <td>892177421306343426</td>\n",
       "      <td>https://pbs.twimg.com/media/DGGmoV4XsAAUL6n.jpg</td>\n",
       "      <td>1</td>\n",
       "      <td>Chihuahua</td>\n",
       "      <td>0.323581</td>\n",
       "      <td>True</td>\n",
       "      <td>Pekinese</td>\n",
       "      <td>0.090647</td>\n",
       "      <td>True</td>\n",
       "      <td>papillon</td>\n",
       "      <td>0.068957</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2074</th>\n",
       "      <td>892420643555336193</td>\n",
       "      <td>https://pbs.twimg.com/media/DGKD1-bXoAAIAUK.jpg</td>\n",
       "      <td>1</td>\n",
       "      <td>orange</td>\n",
       "      <td>0.097049</td>\n",
       "      <td>False</td>\n",
       "      <td>bagel</td>\n",
       "      <td>0.085851</td>\n",
       "      <td>False</td>\n",
       "      <td>banana</td>\n",
       "      <td>0.076110</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
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       "</div>"
      ],
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       "                tweet_id                                          jpg_url  \\\n",
       "0     666020888022790149  https://pbs.twimg.com/media/CT4udn0WwAA0aMy.jpg   \n",
       "1     666029285002620928  https://pbs.twimg.com/media/CT42GRgUYAA5iDo.jpg   \n",
       "2     666033412701032449  https://pbs.twimg.com/media/CT4521TWwAEvMyu.jpg   \n",
       "3     666044226329800704  https://pbs.twimg.com/media/CT5Dr8HUEAA-lEu.jpg   \n",
       "4     666049248165822465  https://pbs.twimg.com/media/CT5IQmsXIAAKY4A.jpg   \n",
       "...                  ...                                              ...   \n",
       "2070  891327558926688256  https://pbs.twimg.com/media/DF6hr6BUMAAzZgT.jpg   \n",
       "2071  891689557279858688  https://pbs.twimg.com/media/DF_q7IAWsAEuuN8.jpg   \n",
       "2072  891815181378084864  https://pbs.twimg.com/media/DGBdLU1WsAANxJ9.jpg   \n",
       "2073  892177421306343426  https://pbs.twimg.com/media/DGGmoV4XsAAUL6n.jpg   \n",
       "2074  892420643555336193  https://pbs.twimg.com/media/DGKD1-bXoAAIAUK.jpg   \n",
       "\n",
       "      img_num                      p1   p1_conf  p1_dog                  p2  \\\n",
       "0           1  Welsh_springer_spaniel  0.465074    True              collie   \n",
       "1           1                 redbone  0.506826    True  miniature_pinscher   \n",
       "2           1         German_shepherd  0.596461    True            malinois   \n",
       "3           1     Rhodesian_ridgeback  0.408143    True             redbone   \n",
       "4           1      miniature_pinscher  0.560311    True          Rottweiler   \n",
       "...       ...                     ...       ...     ...                 ...   \n",
       "2070        2                  basset  0.555712    True    English_springer   \n",
       "2071        1             paper_towel  0.170278   False  Labrador_retriever   \n",
       "2072        1               Chihuahua  0.716012    True            malamute   \n",
       "2073        1               Chihuahua  0.323581    True            Pekinese   \n",
       "2074        1                  orange  0.097049   False               bagel   \n",
       "\n",
       "       p2_conf  p2_dog                           p3   p3_conf  p3_dog  \n",
       "0     0.156665    True            Shetland_sheepdog  0.061428    True  \n",
       "1     0.074192    True          Rhodesian_ridgeback  0.072010    True  \n",
       "2     0.138584    True                   bloodhound  0.116197    True  \n",
       "3     0.360687    True           miniature_pinscher  0.222752    True  \n",
       "4     0.243682    True                     Doberman  0.154629    True  \n",
       "...        ...     ...                          ...       ...     ...  \n",
       "2070  0.225770    True  German_short-haired_pointer  0.175219    True  \n",
       "2071  0.168086    True                      spatula  0.040836   False  \n",
       "2072  0.078253    True                       kelpie  0.031379    True  \n",
       "2073  0.090647    True                     papillon  0.068957    True  \n",
       "2074  0.085851   False                       banana  0.076110   False  \n",
       "\n",
       "[2075 rows x 12 columns]"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dog_pred"
   ]
  },
  {
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   "execution_count": 16,
   "id": "e0052dfc",
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   "outputs": [
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       "                tweet_id  retweet_count  favorite_count  \\\n",
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       "3     891689557279858688           8964           42908   \n",
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       "...                  ...            ...             ...   \n",
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       "\n",
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   "source": [
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  {
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   "execution_count": 17,
   "id": "7be96005",
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   "outputs": [
    {
     "data": {
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       "      <th>tweet_id</th>\n",
       "      <th>in_reply_to_status_id</th>\n",
       "      <th>in_reply_to_user_id</th>\n",
       "      <th>timestamp</th>\n",
       "      <th>source</th>\n",
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       "      <th>name</th>\n",
       "      <th>doggo</th>\n",
       "      <th>floofer</th>\n",
       "      <th>pupper</th>\n",
       "      <th>puppo</th>\n",
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       "      <td>10</td>\n",
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       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
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       "      <td>This is a purebred Piers Morgan. Loves to Netf...</td>\n",
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       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>https://twitter.com/dog_rates/status/666044226...</td>\n",
       "      <td>6</td>\n",
       "      <td>10</td>\n",
       "      <td>a</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
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       "      <th>2353</th>\n",
       "      <td>666033412701032449</td>\n",
       "      <td>NaN</td>\n",
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       "      <td>2015-11-15 23:21:54 +0000</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>Here is a very happy pup. Big fan of well-main...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>https://twitter.com/dog_rates/status/666033412...</td>\n",
       "      <td>9</td>\n",
       "      <td>10</td>\n",
       "      <td>a</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
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       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>This is a western brown Mitsubishi terrier. Up...</td>\n",
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       "      <td>https://twitter.com/dog_rates/status/666029285...</td>\n",
       "      <td>7</td>\n",
       "      <td>10</td>\n",
       "      <td>a</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2355</th>\n",
       "      <td>666020888022790149</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2015-11-15 22:32:08 +0000</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>Here we have a Japanese Irish Setter. Lost eye...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>https://twitter.com/dog_rates/status/666020888...</td>\n",
       "      <td>8</td>\n",
       "      <td>10</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>2356 rows × 17 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                tweet_id  in_reply_to_status_id  in_reply_to_user_id  \\\n",
       "0     892420643555336193                    NaN                  NaN   \n",
       "1     892177421306343426                    NaN                  NaN   \n",
       "2     891815181378084864                    NaN                  NaN   \n",
       "3     891689557279858688                    NaN                  NaN   \n",
       "4     891327558926688256                    NaN                  NaN   \n",
       "...                  ...                    ...                  ...   \n",
       "2351  666049248165822465                    NaN                  NaN   \n",
       "2352  666044226329800704                    NaN                  NaN   \n",
       "2353  666033412701032449                    NaN                  NaN   \n",
       "2354  666029285002620928                    NaN                  NaN   \n",
       "2355  666020888022790149                    NaN                  NaN   \n",
       "\n",
       "                      timestamp  \\\n",
       "0     2017-08-01 16:23:56 +0000   \n",
       "1     2017-08-01 00:17:27 +0000   \n",
       "2     2017-07-31 00:18:03 +0000   \n",
       "3     2017-07-30 15:58:51 +0000   \n",
       "4     2017-07-29 16:00:24 +0000   \n",
       "...                         ...   \n",
       "2351  2015-11-16 00:24:50 +0000   \n",
       "2352  2015-11-16 00:04:52 +0000   \n",
       "2353  2015-11-15 23:21:54 +0000   \n",
       "2354  2015-11-15 23:05:30 +0000   \n",
       "2355  2015-11-15 22:32:08 +0000   \n",
       "\n",
       "                                                 source  \\\n",
       "0     <a href=\"http://twitter.com/download/iphone\" r...   \n",
       "1     <a href=\"http://twitter.com/download/iphone\" r...   \n",
       "2     <a href=\"http://twitter.com/download/iphone\" r...   \n",
       "3     <a href=\"http://twitter.com/download/iphone\" r...   \n",
       "4     <a href=\"http://twitter.com/download/iphone\" r...   \n",
       "...                                                 ...   \n",
       "2351  <a href=\"http://twitter.com/download/iphone\" r...   \n",
       "2352  <a href=\"http://twitter.com/download/iphone\" r...   \n",
       "2353  <a href=\"http://twitter.com/download/iphone\" r...   \n",
       "2354  <a href=\"http://twitter.com/download/iphone\" r...   \n",
       "2355  <a href=\"http://twitter.com/download/iphone\" r...   \n",
       "\n",
       "                                                   text  retweeted_status_id  \\\n",
       "0     This is Phineas. He's a mystical boy. Only eve...                  NaN   \n",
       "1     This is Tilly. She's just checking pup on you....                  NaN   \n",
       "2     This is Archie. He is a rare Norwegian Pouncin...                  NaN   \n",
       "3     This is Darla. She commenced a snooze mid meal...                  NaN   \n",
       "4     This is Franklin. He would like you to stop ca...                  NaN   \n",
       "...                                                 ...                  ...   \n",
       "2351  Here we have a 1949 1st generation vulpix. Enj...                  NaN   \n",
       "2352  This is a purebred Piers Morgan. Loves to Netf...                  NaN   \n",
       "2353  Here is a very happy pup. Big fan of well-main...                  NaN   \n",
       "2354  This is a western brown Mitsubishi terrier. Up...                  NaN   \n",
       "2355  Here we have a Japanese Irish Setter. Lost eye...                  NaN   \n",
       "\n",
       "      retweeted_status_user_id retweeted_status_timestamp  \\\n",
       "0                          NaN                        NaN   \n",
       "1                          NaN                        NaN   \n",
       "2                          NaN                        NaN   \n",
       "3                          NaN                        NaN   \n",
       "4                          NaN                        NaN   \n",
       "...                        ...                        ...   \n",
       "2351                       NaN                        NaN   \n",
       "2352                       NaN                        NaN   \n",
       "2353                       NaN                        NaN   \n",
       "2354                       NaN                        NaN   \n",
       "2355                       NaN                        NaN   \n",
       "\n",
       "                                          expanded_urls  rating_numerator  \\\n",
       "0     https://twitter.com/dog_rates/status/892420643...                13   \n",
       "1     https://twitter.com/dog_rates/status/892177421...                13   \n",
       "2     https://twitter.com/dog_rates/status/891815181...                12   \n",
       "3     https://twitter.com/dog_rates/status/891689557...                13   \n",
       "4     https://twitter.com/dog_rates/status/891327558...                12   \n",
       "...                                                 ...               ...   \n",
       "2351  https://twitter.com/dog_rates/status/666049248...                 5   \n",
       "2352  https://twitter.com/dog_rates/status/666044226...                 6   \n",
       "2353  https://twitter.com/dog_rates/status/666033412...                 9   \n",
       "2354  https://twitter.com/dog_rates/status/666029285...                 7   \n",
       "2355  https://twitter.com/dog_rates/status/666020888...                 8   \n",
       "\n",
       "      rating_denominator      name doggo floofer pupper puppo  \n",
       "0                     10   Phineas  None    None   None  None  \n",
       "1                     10     Tilly  None    None   None  None  \n",
       "2                     10    Archie  None    None   None  None  \n",
       "3                     10     Darla  None    None   None  None  \n",
       "4                     10  Franklin  None    None   None  None  \n",
       "...                  ...       ...   ...     ...    ...   ...  \n",
       "2351                  10      None  None    None   None  None  \n",
       "2352                  10         a  None    None   None  None  \n",
       "2353                  10         a  None    None   None  None  \n",
       "2354                  10         a  None    None   None  None  \n",
       "2355                  10      None  None    None   None  None  \n",
       "\n",
       "[2356 rows x 17 columns]"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Twitter_archive"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b4e01968",
   "metadata": {},
   "source": [
    "### Assessing programmaitically"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "277667c4",
   "metadata": {},
   "source": [
    "####  **Twitter_archive**"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "371829a9",
   "metadata": {},
   "source": [
    "Checking the general info of the dataframe: datatypes, counts of each features, memory usage"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "98d802d6",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 2356 entries, 0 to 2355\n",
      "Data columns (total 17 columns):\n",
      " #   Column                      Non-Null Count  Dtype  \n",
      "---  ------                      --------------  -----  \n",
      " 0   tweet_id                    2356 non-null   int64  \n",
      " 1   in_reply_to_status_id       78 non-null     float64\n",
      " 2   in_reply_to_user_id         78 non-null     float64\n",
      " 3   timestamp                   2356 non-null   object \n",
      " 4   source                      2356 non-null   object \n",
      " 5   text                        2356 non-null   object \n",
      " 6   retweeted_status_id         181 non-null    float64\n",
      " 7   retweeted_status_user_id    181 non-null    float64\n",
      " 8   retweeted_status_timestamp  181 non-null    object \n",
      " 9   expanded_urls               2297 non-null   object \n",
      " 10  rating_numerator            2356 non-null   int64  \n",
      " 11  rating_denominator          2356 non-null   int64  \n",
      " 12  name                        2356 non-null   object \n",
      " 13  doggo                       2356 non-null   object \n",
      " 14  floofer                     2356 non-null   object \n",
      " 15  pupper                      2356 non-null   object \n",
      " 16  puppo                       2356 non-null   object \n",
      "dtypes: float64(4), int64(3), object(10)\n",
      "memory usage: 313.0+ KB\n"
     ]
    }
   ],
   "source": [
    "Twitter_archive.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "f2d9767d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "tweet_id                         0\n",
       "in_reply_to_status_id         2278\n",
       "in_reply_to_user_id           2278\n",
       "timestamp                        0\n",
       "source                           0\n",
       "text                             0\n",
       "retweeted_status_id           2175\n",
       "retweeted_status_user_id      2175\n",
       "retweeted_status_timestamp    2175\n",
       "expanded_urls                   59\n",
       "rating_numerator                 0\n",
       "rating_denominator               0\n",
       "name                             0\n",
       "doggo                            0\n",
       "floofer                          0\n",
       "pupper                           0\n",
       "puppo                            0\n",
       "dtype: int64"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Twitter_archive.isnull().sum() # counting number of missing values for each column"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2700dcf4",
   "metadata": {},
   "source": [
    "checking for dog names"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "8808acb9",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array(['Phineas', 'Tilly', 'Archie', 'Darla', 'Franklin', 'None', 'Jax',\n",
       "       'Zoey', 'Cassie', 'Koda', 'Bruno', 'Ted', 'Stuart', 'Oliver',\n",
       "       'Jim', 'Zeke', 'Ralphus', 'Canela', 'Gerald', 'Jeffrey', 'such',\n",
       "       'Maya', 'Mingus', 'Derek', 'Roscoe', 'Waffles', 'Jimbo', 'Maisey',\n",
       "       'Lilly', 'Earl', 'Lola', 'Kevin', 'Yogi', 'Noah', 'Bella',\n",
       "       'Grizzwald', 'Rusty', 'Gus', 'Stanley', 'Alfy', 'Koko', 'Rey',\n",
       "       'Gary', 'a', 'Elliot', 'Louis', 'Jesse', 'Romeo', 'Bailey',\n",
       "       'Duddles', 'Jack', 'Emmy', 'Steven', 'Beau', 'Snoopy', 'Shadow',\n",
       "       'Terrance', 'Aja', 'Penny', 'Dante', 'Nelly', 'Ginger', 'Benedict',\n",
       "       'Venti', 'Goose', 'Nugget', 'Cash', 'Coco', 'Jed', 'Sebastian',\n",
       "       'Walter', 'Sierra', 'Monkey', 'Harry', 'Kody', 'Lassie', 'Rover',\n",
       "       'Napolean', 'Dawn', 'Boomer', 'Cody', 'Rumble', 'Clifford',\n",
       "       'quite', 'Dewey', 'Scout', 'Gizmo', 'Cooper', 'Harold', 'Shikha',\n",
       "       'Jamesy', 'Lili', 'Sammy', 'Meatball', 'Paisley', 'Albus',\n",
       "       'Neptune', 'Quinn', 'Belle', 'Zooey', 'Dave', 'Jersey', 'Hobbes',\n",
       "       'Burt', 'Lorenzo', 'Carl', 'Jordy', 'Milky', 'Trooper', 'Winston',\n",
       "       'Sophie', 'Wyatt', 'Rosie', 'Thor', 'Oscar', 'Luna', 'Callie',\n",
       "       'Cermet', 'George', 'Marlee', 'Arya', 'Einstein', 'Alice',\n",
       "       'Rumpole', 'Benny', 'Aspen', 'Jarod', 'Wiggles', 'General',\n",
       "       'Sailor', 'Astrid', 'Iggy', 'Snoop', 'Kyle', 'Leo', 'Riley',\n",
       "       'Gidget', 'Noosh', 'Odin', 'Jerry', 'Charlie', 'Georgie', 'Rontu',\n",
       "       'Cannon', 'Furzey', 'Daisy', 'Tuck', 'Barney', 'Vixen', 'Jarvis',\n",
       "       'Mimosa', 'Pickles', 'Bungalo', 'Brady', 'Margo', 'Sadie', 'Hank',\n",
       "       'Tycho', 'Stephan', 'Indie', 'Winnie', 'Bentley', 'Ken', 'Max',\n",
       "       'Maddie', 'Pipsy', 'Monty', 'Sojourner', 'Odie', 'Arlo', 'Sunny',\n",
       "       'Vincent', 'Lucy', 'Clark', 'Mookie', 'Meera', 'Buddy', 'Ava',\n",
       "       'Rory', 'Eli', 'Ash', 'Tucker', 'Tobi', 'Chester', 'Wilson',\n",
       "       'Sunshine', 'Lipton', 'Gabby', 'Bronte', 'Poppy', 'Rhino',\n",
       "       'Willow', 'not', 'Orion', 'Eevee', 'Smiley', 'Logan', 'Moreton',\n",
       "       'Klein', 'Miguel', 'Emanuel', 'Kuyu', 'Dutch', 'Pete', 'Scooter',\n",
       "       'Reggie', 'Kyro', 'Samson', 'Loki', 'Mia', 'Malcolm', 'Dexter',\n",
       "       'Alfie', 'Fiona', 'one', 'Mutt', 'Bear', 'Doobert', 'Beebop',\n",
       "       'Alexander', 'Sailer', 'Brutus', 'Kona', 'Boots', 'Ralphie',\n",
       "       'Phil', 'Cupid', 'Pawnd', 'Pilot', 'Ike', 'Mo', 'Toby', 'Sweet',\n",
       "       'Pablo', 'Nala', 'Balto', 'Crawford', 'Gabe', 'Mattie', 'Jimison',\n",
       "       'Hercules', 'Duchess', 'Harlso', 'Sampson', 'Sundance', 'Luca',\n",
       "       'Flash', 'Finn', 'Peaches', 'Howie', 'Jazzy', 'Anna', 'Bo',\n",
       "       'Seamus', 'Wafer', 'Chelsea', 'Tom', 'Moose', 'Florence', 'Autumn',\n",
       "       'Dido', 'Eugene', 'Herschel', 'Strudel', 'Tebow', 'Chloe', 'Betty',\n",
       "       'Timber', 'Binky', 'Dudley', 'Comet', 'Larry', 'Levi', 'Akumi',\n",
       "       'Titan', 'Olivia', 'Alf', 'Oshie', 'Bruce', 'Chubbs', 'Sky',\n",
       "       'Atlas', 'Eleanor', 'Layla', 'Rocky', 'Baron', 'Tyr', 'Bauer',\n",
       "       'Swagger', 'Brandi', 'Mary', 'Moe', 'Halo', 'Augie', 'Craig',\n",
       "       'Sam', 'Hunter', 'Pavlov', 'Maximus', 'Wallace', 'Ito', 'Milo',\n",
       "       'Ollie', 'Cali', 'Lennon', 'incredibly', 'Major', 'Duke',\n",
       "       'Reginald', 'Sansa', 'Shooter', 'Django', 'Diogi', 'Sonny',\n",
       "       'Philbert', 'Marley', 'Severus', 'Ronnie', 'Anakin', 'Bones',\n",
       "       'Mauve', 'Chef', 'Doc', 'Sobe', 'Longfellow', 'Mister', 'Iroh',\n",
       "       'Baloo', 'Stubert', 'Paull', 'Timison', 'Davey', 'Pancake',\n",
       "       'Tyrone', 'Snicku', 'Ruby', 'Brody', 'Rizzy', 'Mack', 'Butter',\n",
       "       'Nimbus', 'Laika', 'Dobby', 'Juno', 'Maude', 'Lily', 'Newt',\n",
       "       'Benji', 'Nida', 'Robin', 'Monster', 'BeBe', 'Remus', 'Mabel',\n",
       "       'Misty', 'Happy', 'Mosby', 'Maggie', 'Leela', 'Ralphy', 'Brownie',\n",
       "       'Meyer', 'Stella', 'mad', 'Frank', 'Tonks', 'Lincoln', 'Oakley',\n",
       "       'Dale', 'Rizzo', 'Arnie', 'Pinot', 'Dallas', 'Hero', 'Frankie',\n",
       "       'Stormy', 'Mairi', 'Loomis', 'Godi', 'Kenny', 'Deacon', 'Timmy',\n",
       "       'Harper', 'Chipson', 'Combo', 'Dash', 'Bell', 'Hurley', 'Jay',\n",
       "       'Mya', 'Strider', 'an', 'Wesley', 'Solomon', 'Huck', 'very', 'O',\n",
       "       'Blue', 'Finley', 'Sprinkles', 'Heinrich', 'Shakespeare', 'Fizz',\n",
       "       'Chip', 'Grey', 'Roosevelt', 'Gromit', 'Willem', 'Dakota', 'Dixie',\n",
       "       'Al', 'Jackson', 'just', 'Carbon', 'DonDon', 'Kirby', 'Lou',\n",
       "       'Nollie', 'Chevy', 'Tito', 'Louie', 'Rupert', 'Rufus', 'Brudge',\n",
       "       'Shadoe', 'Colby', 'Angel', 'Brat', 'Tove', 'my', 'Aubie', 'Kota',\n",
       "       'Eve', 'Glenn', 'Shelby', 'Sephie', 'Bonaparte', 'Albert',\n",
       "       'Wishes', 'Rose', 'Theo', 'Rocco', 'Fido', 'Emma', 'Spencer',\n",
       "       'Lilli', 'Boston', 'Brandonald', 'Corey', 'Leonard', 'Chompsky',\n",
       "       'Beckham', 'Devón', 'Gert', 'Watson', 'Rubio', 'Keith', 'Dex',\n",
       "       'Carly', 'Ace', 'Tayzie', 'Grizzie', 'Fred', 'Gilbert', 'Zoe',\n",
       "       'Stewie', 'Calvin', 'Lilah', 'Spanky', 'Jameson', 'Piper',\n",
       "       'Atticus', 'Blu', 'Dietrich', 'Divine', 'Tripp', 'his', 'Cora',\n",
       "       'Huxley', 'Keurig', 'Bookstore', 'Linus', 'Abby', 'Shaggy',\n",
       "       'Shiloh', 'Gustav', 'Arlen', 'Percy', 'Lenox', 'Sugar', 'Harvey',\n",
       "       'Blanket', 'actually', 'Geno', 'Stark', 'Beya', 'Kilo', 'Kayla',\n",
       "       'Maxaroni', 'Doug', 'Edmund', 'Aqua', 'Theodore', 'Chase',\n",
       "       'getting', 'Rorie', 'Simba', 'Charles', 'Bayley', 'Axel',\n",
       "       'Storkson', 'Remy', 'Chadrick', 'Kellogg', 'Buckley', 'Livvie',\n",
       "       'Terry', 'Hermione', 'Ralpher', 'Aldrick', 'this', 'unacceptable',\n",
       "       'Rooney', 'Crystal', 'Ziva', 'Stefan', 'Pupcasso', 'Puff',\n",
       "       'Flurpson', 'Coleman', 'Enchilada', 'Raymond', 'all', 'Rueben',\n",
       "       'Cilantro', 'Karll', 'Sprout', 'Blitz', 'Bloop', 'Lillie',\n",
       "       'Ashleigh', 'Kreggory', 'Sarge', 'Luther', 'Ivar', 'Jangle',\n",
       "       'Schnitzel', 'Panda', 'Berkeley', 'Ralphé', 'Charleson', 'Clyde',\n",
       "       'Harnold', 'Sid', 'Pippa', 'Otis', 'Carper', 'Bowie',\n",
       "       'Alexanderson', 'Suki', 'Barclay', 'Skittle', 'Ebby', 'Flávio',\n",
       "       'Smokey', 'Link', 'Jennifur', 'Ozzy', 'Bluebert', 'Stephanus',\n",
       "       'Bubbles', 'old', 'Zeus', 'Bertson', 'Nico', 'Michelangelope',\n",
       "       'Siba', 'Calbert', 'Curtis', 'Travis', 'Thumas', 'Kanu', 'Lance',\n",
       "       'Opie', 'Kane', 'Olive', 'Chuckles', 'Staniel', 'Sora', 'Beemo',\n",
       "       'Gunner', 'infuriating', 'Lacy', 'Tater', 'Olaf', 'Cecil', 'Vince',\n",
       "       'Karma', 'Billy', 'Walker', 'Rodney', 'Klevin', 'Malikai',\n",
       "       'Bobble', 'River', 'Jebberson', 'Remington', 'Farfle', 'Jiminus',\n",
       "       'Clarkus', 'Finnegus', 'Cupcake', 'Kathmandu', 'Ellie', 'Katie',\n",
       "       'Kara', 'Adele', 'Zara', 'Ambrose', 'Jimothy', 'Bode', 'Terrenth',\n",
       "       'Reese', 'Chesterson', 'Lucia', 'Bisquick', 'Ralphson', 'Socks',\n",
       "       'Rambo', 'Rudy', 'Fiji', 'Rilo', 'Bilbo', 'Coopson', 'Yoda',\n",
       "       'Millie', 'Chet', 'Crouton', 'Daniel', 'Kaia', 'Murphy', 'Dotsy',\n",
       "       'Eazy', 'Coops', 'Fillup', 'Miley', 'Charl', 'Reagan', 'Yukon',\n",
       "       'CeCe', 'Cuddles', 'Claude', 'Jessiga', 'Carter', 'Ole', 'Pherb',\n",
       "       'Blipson', 'Reptar', 'Trevith', 'Berb', 'Bob', 'Colin', 'Brian',\n",
       "       'Oliviér', 'Grady', 'Kobe', 'Freddery', 'Bodie', 'Dunkin', 'Wally',\n",
       "       'Tupawc', 'Amber', 'Edgar', 'Teddy', 'Kingsley', 'Brockly',\n",
       "       'Richie', 'Molly', 'Vinscent', 'Cedrick', 'Hazel', 'Lolo', 'Eriq',\n",
       "       'Phred', 'the', 'Oddie', 'Maxwell', 'Geoff', 'Covach', 'Durg',\n",
       "       'Fynn', 'Ricky', 'Herald', 'Lucky', 'Ferg', 'Trip', 'Clarence',\n",
       "       'Hamrick', 'Brad', 'Pubert', 'Frönq', 'Derby', 'Lizzie', 'Ember',\n",
       "       'Blakely', 'Opal', 'Marq', 'Kramer', 'Barry', 'Gordon', 'Baxter',\n",
       "       'Mona', 'Horace', 'Crimson', 'Birf', 'Hammond', 'Lorelei', 'Marty',\n",
       "       'Brooks', 'Petrick', 'Hubertson', 'Gerbald', 'Oreo', 'Bruiser',\n",
       "       'Perry', 'Bobby', 'Jeph', 'Obi', 'Tino', 'Kulet', 'Sweets', 'Lupe',\n",
       "       'Tiger', 'Jiminy', 'Griffin', 'Banjo', 'Brandy', 'Lulu', 'Darrel',\n",
       "       'Taco', 'Joey', 'Patrick', 'Kreg', 'Todo', 'Tess', 'Ulysses',\n",
       "       'Toffee', 'Apollo', 'Asher', 'Glacier', 'Chuck', 'Champ', 'Ozzie',\n",
       "       'Griswold', 'Cheesy', 'Moofasa', 'Hector', 'Goliath', 'Kawhi',\n",
       "       'by', 'Emmie', 'Penelope', 'Willie', 'Rinna', 'Mike', 'William',\n",
       "       'Dwight', 'Evy', 'officially', 'Rascal', 'Linda', 'Tug', 'Tango',\n",
       "       'Grizz', 'Jerome', 'Crumpet', 'Jessifer', 'Izzy', 'Ralph', 'Sandy',\n",
       "       'Humphrey', 'Tassy', 'Juckson', 'Chuq', 'Tyrus', 'Karl',\n",
       "       'Godzilla', 'Vinnie', 'Kenneth', 'Herm', 'Bert', 'Striker',\n",
       "       'Donny', 'Pepper', 'Bernie', 'Buddah', 'Lenny', 'Arnold', 'Zuzu',\n",
       "       'Mollie', 'Laela', 'Tedders', 'Superpup', 'Rufio', 'Jeb', 'Rodman',\n",
       "       'Jonah', 'Chesney', 'life', 'Henry', 'Bobbay', 'Mitch', 'Kaiya',\n",
       "       'Acro', 'Aiden', 'Obie', 'Dot', 'Shnuggles', 'Kendall', 'Jeffri',\n",
       "       'Steve', 'Mac', 'Fletcher', 'Kenzie', 'Pumpkin', 'Schnozz',\n",
       "       'Gustaf', 'Cheryl', 'Ed', 'Leonidas', 'Norman', 'Caryl', 'Scott',\n",
       "       'Taz', 'Darby', 'Jackie', 'light', 'Jazz', 'Franq', 'Pippin',\n",
       "       'Rolf', 'Snickers', 'Ridley', 'Cal', 'Bradley', 'Bubba', 'Tuco',\n",
       "       'Patch', 'Mojo', 'Batdog', 'Dylan', 'space', 'Mark', 'JD',\n",
       "       'Alejandro', 'Scruffers', 'Pip', 'Julius', 'Tanner', 'Sparky',\n",
       "       'Anthony', 'Holly', 'Jett', 'Amy', 'Sage', 'Andy', 'Mason',\n",
       "       'Trigger', 'Antony', 'Creg', 'Traviss', 'Gin', 'Jeffrie', 'Danny',\n",
       "       'Ester', 'Pluto', 'Bloo', 'Edd', 'Willy', 'Herb', 'Damon',\n",
       "       'Peanut', 'Nigel', 'Butters', 'Sandra', 'Fabio', 'Randall', 'Liam',\n",
       "       'Tommy', 'Ben', 'Raphael', 'Julio', 'Andru', 'Kloey', 'Shawwn',\n",
       "       'Skye', 'Kollin', 'Ronduh', 'Billl', 'Saydee', 'Dug', 'Tessa',\n",
       "       'Sully', 'Kirk', 'Ralf', 'Clarq', 'Jaspers', 'Samsom', 'Harrison',\n",
       "       'Chaz', 'Jeremy', 'Jaycob', 'Lambeau', 'Ruffles', 'Amélie', 'Bobb',\n",
       "       'Banditt', 'Kevon', 'Winifred', 'Hanz', 'Churlie', 'Zeek',\n",
       "       'Timofy', 'Maks', 'Jomathan', 'Kallie', 'Marvin', 'Spark',\n",
       "       'Gòrdón', 'Jo', 'DayZ', 'Jareld', 'Torque', 'Ron', 'Skittles',\n",
       "       'Cleopatricia', 'Erik', 'Stu', 'Tedrick', 'Filup', 'Kial',\n",
       "       'Naphaniel', 'Dook', 'Hall', 'Philippe', 'Biden', 'Fwed',\n",
       "       'Genevieve', 'Joshwa', 'Bradlay', 'Clybe', 'Keet', 'Carll',\n",
       "       'Jockson', 'Josep', 'Lugan', 'Christoper'], dtype=object)"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Twitter_archive['name'].unique()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "a229b8a0",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "None          745\n",
       "a              55\n",
       "Charlie        12\n",
       "Cooper         11\n",
       "Lucy           11\n",
       "             ... \n",
       "Dex             1\n",
       "Ace             1\n",
       "Tayzie          1\n",
       "Grizzie         1\n",
       "Christoper      1\n",
       "Name: name, Length: 957, dtype: int64"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# counting for individual unique name\n",
    "Twitter_archive['name'].value_counts()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "cb674568",
   "metadata": {},
   "source": [
    "Note that irrelevant names like by, the, a...... start with lowercase. Further assessing names that start with lowercase"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "356c8802",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['a',\n",
       " 'the',\n",
       " 'an',\n",
       " 'very',\n",
       " 'just',\n",
       " 'quite',\n",
       " 'one',\n",
       " 'getting',\n",
       " 'actually',\n",
       " 'mad',\n",
       " 'not',\n",
       " 'old',\n",
       " 'life',\n",
       " 'officially',\n",
       " 'light',\n",
       " 'by',\n",
       " 'infuriating',\n",
       " 'such',\n",
       " 'all',\n",
       " 'unacceptable',\n",
       " 'this',\n",
       " 'his',\n",
       " 'my',\n",
       " 'incredibly',\n",
       " 'space']"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "list(Twitter_archive[Twitter_archive['name'].str.islower()].name.value_counts().index)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "5957f392",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "None     2259\n",
       "doggo      97\n",
       "Name: doggo, dtype: int64"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Twitter_archive['doggo'].value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "897c37ef",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "None       2346\n",
       "floofer      10\n",
       "Name: floofer, dtype: int64"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Twitter_archive['floofer'].value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "c45745ff",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "None      2099\n",
       "pupper     257\n",
       "Name: pupper, dtype: int64"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Twitter_archive['pupper'].value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "887f5222",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "None     2326\n",
       "puppo      30\n",
       "Name: puppo, dtype: int64"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Twitter_archive['puppo'].value_counts()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c265bd2d",
   "metadata": {},
   "source": [
    "Further investigating if dog has more than 1 stage"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "a9359c96",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>tweet_id</th>\n",
       "      <th>in_reply_to_status_id</th>\n",
       "      <th>in_reply_to_user_id</th>\n",
       "      <th>timestamp</th>\n",
       "      <th>source</th>\n",
       "      <th>text</th>\n",
       "      <th>retweeted_status_id</th>\n",
       "      <th>retweeted_status_user_id</th>\n",
       "      <th>retweeted_status_timestamp</th>\n",
       "      <th>expanded_urls</th>\n",
       "      <th>rating_numerator</th>\n",
       "      <th>rating_denominator</th>\n",
       "      <th>name</th>\n",
       "      <th>doggo</th>\n",
       "      <th>floofer</th>\n",
       "      <th>pupper</th>\n",
       "      <th>puppo</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>200</th>\n",
       "      <td>854010172552949760</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2017-04-17 16:34:26 +0000</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>At first I thought this was a shy doggo, but i...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>https://twitter.com/dog_rates/status/854010172...</td>\n",
       "      <td>11</td>\n",
       "      <td>10</td>\n",
       "      <td>None</td>\n",
       "      <td>doggo</td>\n",
       "      <td>floofer</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "               tweet_id  in_reply_to_status_id  in_reply_to_user_id  \\\n",
       "200  854010172552949760                    NaN                  NaN   \n",
       "\n",
       "                     timestamp  \\\n",
       "200  2017-04-17 16:34:26 +0000   \n",
       "\n",
       "                                                source  \\\n",
       "200  <a href=\"http://twitter.com/download/iphone\" r...   \n",
       "\n",
       "                                                  text  retweeted_status_id  \\\n",
       "200  At first I thought this was a shy doggo, but i...                  NaN   \n",
       "\n",
       "     retweeted_status_user_id retweeted_status_timestamp  \\\n",
       "200                       NaN                        NaN   \n",
       "\n",
       "                                         expanded_urls  rating_numerator  \\\n",
       "200  https://twitter.com/dog_rates/status/854010172...                11   \n",
       "\n",
       "     rating_denominator  name  doggo  floofer pupper puppo  \n",
       "200                  10  None  doggo  floofer   None  None  "
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Twitter_archive.query('doggo == \"doggo\" & floofer!=\"None\"')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "7114fe07",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>tweet_id</th>\n",
       "      <th>in_reply_to_status_id</th>\n",
       "      <th>in_reply_to_user_id</th>\n",
       "      <th>timestamp</th>\n",
       "      <th>source</th>\n",
       "      <th>text</th>\n",
       "      <th>retweeted_status_id</th>\n",
       "      <th>retweeted_status_user_id</th>\n",
       "      <th>retweeted_status_timestamp</th>\n",
       "      <th>expanded_urls</th>\n",
       "      <th>rating_numerator</th>\n",
       "      <th>rating_denominator</th>\n",
       "      <th>name</th>\n",
       "      <th>doggo</th>\n",
       "      <th>floofer</th>\n",
       "      <th>pupper</th>\n",
       "      <th>puppo</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>191</th>\n",
       "      <td>855851453814013952</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2017-04-22 18:31:02 +0000</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>Here's a puppo participating in the #ScienceMa...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>https://twitter.com/dog_rates/status/855851453...</td>\n",
       "      <td>13</td>\n",
       "      <td>10</td>\n",
       "      <td>None</td>\n",
       "      <td>doggo</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>puppo</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "               tweet_id  in_reply_to_status_id  in_reply_to_user_id  \\\n",
       "191  855851453814013952                    NaN                  NaN   \n",
       "\n",
       "                     timestamp  \\\n",
       "191  2017-04-22 18:31:02 +0000   \n",
       "\n",
       "                                                source  \\\n",
       "191  <a href=\"http://twitter.com/download/iphone\" r...   \n",
       "\n",
       "                                                  text  retweeted_status_id  \\\n",
       "191  Here's a puppo participating in the #ScienceMa...                  NaN   \n",
       "\n",
       "     retweeted_status_user_id retweeted_status_timestamp  \\\n",
       "191                       NaN                        NaN   \n",
       "\n",
       "                                         expanded_urls  rating_numerator  \\\n",
       "191  https://twitter.com/dog_rates/status/855851453...                13   \n",
       "\n",
       "     rating_denominator  name  doggo floofer pupper  puppo  \n",
       "191                  10  None  doggo    None   None  puppo  "
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Twitter_archive.query('doggo == \"doggo\" & puppo!=\"None\"')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "ecbf4374",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>tweet_id</th>\n",
       "      <th>in_reply_to_status_id</th>\n",
       "      <th>in_reply_to_user_id</th>\n",
       "      <th>timestamp</th>\n",
       "      <th>source</th>\n",
       "      <th>text</th>\n",
       "      <th>retweeted_status_id</th>\n",
       "      <th>retweeted_status_user_id</th>\n",
       "      <th>retweeted_status_timestamp</th>\n",
       "      <th>expanded_urls</th>\n",
       "      <th>rating_numerator</th>\n",
       "      <th>rating_denominator</th>\n",
       "      <th>name</th>\n",
       "      <th>doggo</th>\n",
       "      <th>floofer</th>\n",
       "      <th>pupper</th>\n",
       "      <th>puppo</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>460</th>\n",
       "      <td>817777686764523521</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2017-01-07 16:59:28 +0000</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>This is Dido. She's playing the lead role in \"...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>https://twitter.com/dog_rates/status/817777686...</td>\n",
       "      <td>13</td>\n",
       "      <td>10</td>\n",
       "      <td>Dido</td>\n",
       "      <td>doggo</td>\n",
       "      <td>None</td>\n",
       "      <td>pupper</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>531</th>\n",
       "      <td>808106460588765185</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2016-12-12 00:29:28 +0000</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>Here we have Burke (pupper) and Dexter (doggo)...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>https://twitter.com/dog_rates/status/808106460...</td>\n",
       "      <td>12</td>\n",
       "      <td>10</td>\n",
       "      <td>None</td>\n",
       "      <td>doggo</td>\n",
       "      <td>None</td>\n",
       "      <td>pupper</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>565</th>\n",
       "      <td>802265048156610565</td>\n",
       "      <td>7.331095e+17</td>\n",
       "      <td>4.196984e+09</td>\n",
       "      <td>2016-11-25 21:37:47 +0000</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>Like doggo, like pupper version 2. Both 11/10 ...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>https://twitter.com/dog_rates/status/802265048...</td>\n",
       "      <td>11</td>\n",
       "      <td>10</td>\n",
       "      <td>None</td>\n",
       "      <td>doggo</td>\n",
       "      <td>None</td>\n",
       "      <td>pupper</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>575</th>\n",
       "      <td>801115127852503040</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2016-11-22 17:28:25 +0000</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>This is Bones. He's being haunted by another d...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>https://twitter.com/dog_rates/status/801115127...</td>\n",
       "      <td>12</td>\n",
       "      <td>10</td>\n",
       "      <td>Bones</td>\n",
       "      <td>doggo</td>\n",
       "      <td>None</td>\n",
       "      <td>pupper</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>705</th>\n",
       "      <td>785639753186217984</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2016-10-11 00:34:48 +0000</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>This is Pinot. He's a sophisticated doggo. You...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>https://twitter.com/dog_rates/status/785639753...</td>\n",
       "      <td>10</td>\n",
       "      <td>10</td>\n",
       "      <td>Pinot</td>\n",
       "      <td>doggo</td>\n",
       "      <td>None</td>\n",
       "      <td>pupper</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>733</th>\n",
       "      <td>781308096455073793</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2016-09-29 01:42:20 +0000</td>\n",
       "      <td>&lt;a href=\"http://vine.co\" rel=\"nofollow\"&gt;Vine -...</td>\n",
       "      <td>Pupper butt 1, Doggo 0. Both 12/10 https://t.c...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>https://vine.co/v/5rgu2Law2ut</td>\n",
       "      <td>12</td>\n",
       "      <td>10</td>\n",
       "      <td>None</td>\n",
       "      <td>doggo</td>\n",
       "      <td>None</td>\n",
       "      <td>pupper</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>778</th>\n",
       "      <td>775898661951791106</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2016-09-14 03:27:11 +0000</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>RT @dog_rates: Like father (doggo), like son (...</td>\n",
       "      <td>7.331095e+17</td>\n",
       "      <td>4.196984e+09</td>\n",
       "      <td>2016-05-19 01:38:16 +0000</td>\n",
       "      <td>https://twitter.com/dog_rates/status/733109485...</td>\n",
       "      <td>12</td>\n",
       "      <td>10</td>\n",
       "      <td>None</td>\n",
       "      <td>doggo</td>\n",
       "      <td>None</td>\n",
       "      <td>pupper</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>822</th>\n",
       "      <td>770093767776997377</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2016-08-29 03:00:36 +0000</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>RT @dog_rates: This is just downright precious...</td>\n",
       "      <td>7.410673e+17</td>\n",
       "      <td>4.196984e+09</td>\n",
       "      <td>2016-06-10 00:39:48 +0000</td>\n",
       "      <td>https://twitter.com/dog_rates/status/741067306...</td>\n",
       "      <td>12</td>\n",
       "      <td>10</td>\n",
       "      <td>just</td>\n",
       "      <td>doggo</td>\n",
       "      <td>None</td>\n",
       "      <td>pupper</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>889</th>\n",
       "      <td>759793422261743616</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2016-07-31 16:50:42 +0000</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>Meet Maggie &amp;amp; Lila. Maggie is the doggo, L...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>https://twitter.com/dog_rates/status/759793422...</td>\n",
       "      <td>12</td>\n",
       "      <td>10</td>\n",
       "      <td>Maggie</td>\n",
       "      <td>doggo</td>\n",
       "      <td>None</td>\n",
       "      <td>pupper</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>956</th>\n",
       "      <td>751583847268179968</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2016-07-09 01:08:47 +0000</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>Please stop sending it pictures that don't eve...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>https://twitter.com/dog_rates/status/751583847...</td>\n",
       "      <td>5</td>\n",
       "      <td>10</td>\n",
       "      <td>None</td>\n",
       "      <td>doggo</td>\n",
       "      <td>None</td>\n",
       "      <td>pupper</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1063</th>\n",
       "      <td>741067306818797568</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2016-06-10 00:39:48 +0000</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>This is just downright precious af. 12/10 for ...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>https://twitter.com/dog_rates/status/741067306...</td>\n",
       "      <td>12</td>\n",
       "      <td>10</td>\n",
       "      <td>just</td>\n",
       "      <td>doggo</td>\n",
       "      <td>None</td>\n",
       "      <td>pupper</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1113</th>\n",
       "      <td>733109485275860992</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2016-05-19 01:38:16 +0000</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>Like father (doggo), like son (pupper). Both 1...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>https://twitter.com/dog_rates/status/733109485...</td>\n",
       "      <td>12</td>\n",
       "      <td>10</td>\n",
       "      <td>None</td>\n",
       "      <td>doggo</td>\n",
       "      <td>None</td>\n",
       "      <td>pupper</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                tweet_id  in_reply_to_status_id  in_reply_to_user_id  \\\n",
       "460   817777686764523521                    NaN                  NaN   \n",
       "531   808106460588765185                    NaN                  NaN   \n",
       "565   802265048156610565           7.331095e+17         4.196984e+09   \n",
       "575   801115127852503040                    NaN                  NaN   \n",
       "705   785639753186217984                    NaN                  NaN   \n",
       "733   781308096455073793                    NaN                  NaN   \n",
       "778   775898661951791106                    NaN                  NaN   \n",
       "822   770093767776997377                    NaN                  NaN   \n",
       "889   759793422261743616                    NaN                  NaN   \n",
       "956   751583847268179968                    NaN                  NaN   \n",
       "1063  741067306818797568                    NaN                  NaN   \n",
       "1113  733109485275860992                    NaN                  NaN   \n",
       "\n",
       "                      timestamp  \\\n",
       "460   2017-01-07 16:59:28 +0000   \n",
       "531   2016-12-12 00:29:28 +0000   \n",
       "565   2016-11-25 21:37:47 +0000   \n",
       "575   2016-11-22 17:28:25 +0000   \n",
       "705   2016-10-11 00:34:48 +0000   \n",
       "733   2016-09-29 01:42:20 +0000   \n",
       "778   2016-09-14 03:27:11 +0000   \n",
       "822   2016-08-29 03:00:36 +0000   \n",
       "889   2016-07-31 16:50:42 +0000   \n",
       "956   2016-07-09 01:08:47 +0000   \n",
       "1063  2016-06-10 00:39:48 +0000   \n",
       "1113  2016-05-19 01:38:16 +0000   \n",
       "\n",
       "                                                 source  \\\n",
       "460   <a href=\"http://twitter.com/download/iphone\" r...   \n",
       "531   <a href=\"http://twitter.com/download/iphone\" r...   \n",
       "565   <a href=\"http://twitter.com/download/iphone\" r...   \n",
       "575   <a href=\"http://twitter.com/download/iphone\" r...   \n",
       "705   <a href=\"http://twitter.com/download/iphone\" r...   \n",
       "733   <a href=\"http://vine.co\" rel=\"nofollow\">Vine -...   \n",
       "778   <a href=\"http://twitter.com/download/iphone\" r...   \n",
       "822   <a href=\"http://twitter.com/download/iphone\" r...   \n",
       "889   <a href=\"http://twitter.com/download/iphone\" r...   \n",
       "956   <a href=\"http://twitter.com/download/iphone\" r...   \n",
       "1063  <a href=\"http://twitter.com/download/iphone\" r...   \n",
       "1113  <a href=\"http://twitter.com/download/iphone\" r...   \n",
       "\n",
       "                                                   text  retweeted_status_id  \\\n",
       "460   This is Dido. She's playing the lead role in \"...                  NaN   \n",
       "531   Here we have Burke (pupper) and Dexter (doggo)...                  NaN   \n",
       "565   Like doggo, like pupper version 2. Both 11/10 ...                  NaN   \n",
       "575   This is Bones. He's being haunted by another d...                  NaN   \n",
       "705   This is Pinot. He's a sophisticated doggo. You...                  NaN   \n",
       "733   Pupper butt 1, Doggo 0. Both 12/10 https://t.c...                  NaN   \n",
       "778   RT @dog_rates: Like father (doggo), like son (...         7.331095e+17   \n",
       "822   RT @dog_rates: This is just downright precious...         7.410673e+17   \n",
       "889   Meet Maggie &amp; Lila. Maggie is the doggo, L...                  NaN   \n",
       "956   Please stop sending it pictures that don't eve...                  NaN   \n",
       "1063  This is just downright precious af. 12/10 for ...                  NaN   \n",
       "1113  Like father (doggo), like son (pupper). Both 1...                  NaN   \n",
       "\n",
       "      retweeted_status_user_id retweeted_status_timestamp  \\\n",
       "460                        NaN                        NaN   \n",
       "531                        NaN                        NaN   \n",
       "565                        NaN                        NaN   \n",
       "575                        NaN                        NaN   \n",
       "705                        NaN                        NaN   \n",
       "733                        NaN                        NaN   \n",
       "778               4.196984e+09  2016-05-19 01:38:16 +0000   \n",
       "822               4.196984e+09  2016-06-10 00:39:48 +0000   \n",
       "889                        NaN                        NaN   \n",
       "956                        NaN                        NaN   \n",
       "1063                       NaN                        NaN   \n",
       "1113                       NaN                        NaN   \n",
       "\n",
       "                                          expanded_urls  rating_numerator  \\\n",
       "460   https://twitter.com/dog_rates/status/817777686...                13   \n",
       "531   https://twitter.com/dog_rates/status/808106460...                12   \n",
       "565   https://twitter.com/dog_rates/status/802265048...                11   \n",
       "575   https://twitter.com/dog_rates/status/801115127...                12   \n",
       "705   https://twitter.com/dog_rates/status/785639753...                10   \n",
       "733                       https://vine.co/v/5rgu2Law2ut                12   \n",
       "778   https://twitter.com/dog_rates/status/733109485...                12   \n",
       "822   https://twitter.com/dog_rates/status/741067306...                12   \n",
       "889   https://twitter.com/dog_rates/status/759793422...                12   \n",
       "956   https://twitter.com/dog_rates/status/751583847...                 5   \n",
       "1063  https://twitter.com/dog_rates/status/741067306...                12   \n",
       "1113  https://twitter.com/dog_rates/status/733109485...                12   \n",
       "\n",
       "      rating_denominator    name  doggo floofer  pupper puppo  \n",
       "460                   10    Dido  doggo    None  pupper  None  \n",
       "531                   10    None  doggo    None  pupper  None  \n",
       "565                   10    None  doggo    None  pupper  None  \n",
       "575                   10   Bones  doggo    None  pupper  None  \n",
       "705                   10   Pinot  doggo    None  pupper  None  \n",
       "733                   10    None  doggo    None  pupper  None  \n",
       "778                   10    None  doggo    None  pupper  None  \n",
       "822                   10    just  doggo    None  pupper  None  \n",
       "889                   10  Maggie  doggo    None  pupper  None  \n",
       "956                   10    None  doggo    None  pupper  None  \n",
       "1063                  10    just  doggo    None  pupper  None  \n",
       "1113                  10    None  doggo    None  pupper  None  "
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Twitter_archive.query('doggo == \"doggo\" & pupper!=\"None\"')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "id": "f2907333",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "12"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(Twitter_archive.query('doggo == \"doggo\" & pupper!=\"None\"')) # counting how many rows has both doggo and pupper"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b49ce618",
   "metadata": {},
   "source": [
    "checking for duplicated text"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "id": "6fa99dbc",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sum(Twitter_archive['text'].duplicated())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "id": "71604ae2",
   "metadata": {},
   "outputs": [],
   "source": [
    "#Twitter_archive['text'].sample(5)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c742b19c",
   "metadata": {},
   "source": [
    "checking for unique source of tweets"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "id": "71e449c9",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array(['<a href=\"http://twitter.com/download/iphone\" rel=\"nofollow\">Twitter for iPhone</a>',\n",
       "       '<a href=\"http://twitter.com\" rel=\"nofollow\">Twitter Web Client</a>',\n",
       "       '<a href=\"http://vine.co\" rel=\"nofollow\">Vine - Make a Scene</a>',\n",
       "       '<a href=\"https://about.twitter.com/products/tweetdeck\" rel=\"nofollow\">TweetDeck</a>'],\n",
       "      dtype=object)"
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Twitter_archive['source'].unique()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "id": "4a14e6bf",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<a href=\"http://twitter.com/download/iphone\" rel=\"nofollow\">Twitter for iPhone</a>     2221\n",
       "<a href=\"http://vine.co\" rel=\"nofollow\">Vine - Make a Scene</a>                          91\n",
       "<a href=\"http://twitter.com\" rel=\"nofollow\">Twitter Web Client</a>                       33\n",
       "<a href=\"https://about.twitter.com/products/tweetdeck\" rel=\"nofollow\">TweetDeck</a>      11\n",
       "Name: source, dtype: int64"
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Twitter_archive['source'].value_counts()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f1c74b9e",
   "metadata": {},
   "source": [
    "assessing rating_numerator and rating_denominator"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "id": "92f1e58e",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([  13,   12,   14,    5,   17,   11,   10,  420,  666,    6,   15,\n",
       "        182,  960,    0,   75,    7,   84,    9,   24,    8,    1,   27,\n",
       "          3,    4,  165, 1776,  204,   50,   99,   80,   45,   60,   44,\n",
       "        143,  121,   20,   26,    2,  144,   88], dtype=int64)"
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Twitter_archive['rating_numerator'].unique()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "id": "bae27471",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([ 10,   0,  15,  70,   7,  11, 150, 170,  20,  50,  90,  80,  40,\n",
       "       130, 110,  16, 120,   2], dtype=int64)"
      ]
     },
     "execution_count": 36,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Twitter_archive['rating_denominator'].unique()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a803499f",
   "metadata": {},
   "source": [
    "Checking minimum and maximum value of rating_numerator, rating_denominator"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "id": "2c82242b",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "maximum numerator rating is 1776\n",
      "minimum numerator rating is 0\n",
      "maximum denominator rating is 170\n",
      "minimum denominator rating is 0\n"
     ]
    }
   ],
   "source": [
    "print('maximum numerator rating is {}'.format(Twitter_archive['rating_numerator'].max()))\n",
    "print('minimum numerator rating is {}'.format(Twitter_archive['rating_numerator'].min()))\n",
    "\n",
    "print('maximum denominator rating is {}'.format(Twitter_archive['rating_denominator'].max()))\n",
    "print('minimum denominator rating is {}'.format(Twitter_archive['rating_denominator'].min()))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "487ae91f",
   "metadata": {},
   "source": [
    "assessing expanded_urls"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "id": "dd906ee0",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "2219"
      ]
     },
     "execution_count": 38,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(Twitter_archive['expanded_urls'].unique())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "id": "453895e7",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "137"
      ]
     },
     "execution_count": 39,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#checking for duplicated value\n",
    "sum(Twitter_archive['expanded_urls'].duplicated()) "
   ]
  },
  {
   "cell_type": "markdown",
   "id": "933e7ee8",
   "metadata": {},
   "source": [
    "#### **Tweet_data**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "id": "d4b404cd",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>tweet_id</th>\n",
       "      <th>retweet_count</th>\n",
       "      <th>favorite_count</th>\n",
       "      <th>create_date</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>892420643555336193</td>\n",
       "      <td>8853</td>\n",
       "      <td>39467</td>\n",
       "      <td>Tue Aug 01 16:23:56 +0000 2017</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>892177421306343426</td>\n",
       "      <td>6514</td>\n",
       "      <td>33819</td>\n",
       "      <td>Tue Aug 01 00:17:27 +0000 2017</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>891815181378084864</td>\n",
       "      <td>4328</td>\n",
       "      <td>25461</td>\n",
       "      <td>Mon Jul 31 00:18:03 +0000 2017</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>891689557279858688</td>\n",
       "      <td>8964</td>\n",
       "      <td>42908</td>\n",
       "      <td>Sun Jul 30 15:58:51 +0000 2017</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "             tweet_id  retweet_count  favorite_count  \\\n",
       "0  892420643555336193           8853           39467   \n",
       "1  892177421306343426           6514           33819   \n",
       "2  891815181378084864           4328           25461   \n",
       "3  891689557279858688           8964           42908   \n",
       "\n",
       "                      create_date  \n",
       "0  Tue Aug 01 16:23:56 +0000 2017  \n",
       "1  Tue Aug 01 00:17:27 +0000 2017  \n",
       "2  Mon Jul 31 00:18:03 +0000 2017  \n",
       "3  Sun Jul 30 15:58:51 +0000 2017  "
      ]
     },
     "execution_count": 40,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Tweet_data.head(4)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "id": "c9eed5b3",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 2354 entries, 0 to 2353\n",
      "Data columns (total 4 columns):\n",
      " #   Column          Non-Null Count  Dtype \n",
      "---  ------          --------------  ----- \n",
      " 0   tweet_id        2354 non-null   int64 \n",
      " 1   retweet_count   2354 non-null   int64 \n",
      " 2   favorite_count  2354 non-null   int64 \n",
      " 3   create_date     2354 non-null   object\n",
      "dtypes: int64(3), object(1)\n",
      "memory usage: 73.7+ KB\n"
     ]
    }
   ],
   "source": [
    "Tweet_data.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "id": "f0bbeef0",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>tweet_id</th>\n",
       "      <th>retweet_count</th>\n",
       "      <th>favorite_count</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>2.354000e+03</td>\n",
       "      <td>2354.000000</td>\n",
       "      <td>2354.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>7.426978e+17</td>\n",
       "      <td>3164.797366</td>\n",
       "      <td>8080.968564</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>6.852812e+16</td>\n",
       "      <td>5284.770364</td>\n",
       "      <td>11814.771334</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>6.660209e+17</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>6.783975e+17</td>\n",
       "      <td>624.500000</td>\n",
       "      <td>1415.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>7.194596e+17</td>\n",
       "      <td>1473.500000</td>\n",
       "      <td>3603.500000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>7.993058e+17</td>\n",
       "      <td>3652.000000</td>\n",
       "      <td>10122.250000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>8.924206e+17</td>\n",
       "      <td>79515.000000</td>\n",
       "      <td>132810.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "           tweet_id  retweet_count  favorite_count\n",
       "count  2.354000e+03    2354.000000     2354.000000\n",
       "mean   7.426978e+17    3164.797366     8080.968564\n",
       "std    6.852812e+16    5284.770364    11814.771334\n",
       "min    6.660209e+17       0.000000        0.000000\n",
       "25%    6.783975e+17     624.500000     1415.000000\n",
       "50%    7.194596e+17    1473.500000     3603.500000\n",
       "75%    7.993058e+17    3652.000000    10122.250000\n",
       "max    8.924206e+17   79515.000000   132810.000000"
      ]
     },
     "execution_count": 42,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Tweet_data.describe()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b6c010be",
   "metadata": {},
   "source": [
    "#### dog_pred"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "id": "1a402fe9",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "        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>tweet_id</th>\n",
       "      <th>jpg_url</th>\n",
       "      <th>img_num</th>\n",
       "      <th>p1</th>\n",
       "      <th>p1_conf</th>\n",
       "      <th>p1_dog</th>\n",
       "      <th>p2</th>\n",
       "      <th>p2_conf</th>\n",
       "      <th>p2_dog</th>\n",
       "      <th>p3</th>\n",
       "      <th>p3_conf</th>\n",
       "      <th>p3_dog</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>666020888022790149</td>\n",
       "      <td>https://pbs.twimg.com/media/CT4udn0WwAA0aMy.jpg</td>\n",
       "      <td>1</td>\n",
       "      <td>Welsh_springer_spaniel</td>\n",
       "      <td>0.465074</td>\n",
       "      <td>True</td>\n",
       "      <td>collie</td>\n",
       "      <td>0.156665</td>\n",
       "      <td>True</td>\n",
       "      <td>Shetland_sheepdog</td>\n",
       "      <td>0.061428</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>666029285002620928</td>\n",
       "      <td>https://pbs.twimg.com/media/CT42GRgUYAA5iDo.jpg</td>\n",
       "      <td>1</td>\n",
       "      <td>redbone</td>\n",
       "      <td>0.506826</td>\n",
       "      <td>True</td>\n",
       "      <td>miniature_pinscher</td>\n",
       "      <td>0.074192</td>\n",
       "      <td>True</td>\n",
       "      <td>Rhodesian_ridgeback</td>\n",
       "      <td>0.072010</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>666033412701032449</td>\n",
       "      <td>https://pbs.twimg.com/media/CT4521TWwAEvMyu.jpg</td>\n",
       "      <td>1</td>\n",
       "      <td>German_shepherd</td>\n",
       "      <td>0.596461</td>\n",
       "      <td>True</td>\n",
       "      <td>malinois</td>\n",
       "      <td>0.138584</td>\n",
       "      <td>True</td>\n",
       "      <td>bloodhound</td>\n",
       "      <td>0.116197</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "             tweet_id                                          jpg_url  \\\n",
       "0  666020888022790149  https://pbs.twimg.com/media/CT4udn0WwAA0aMy.jpg   \n",
       "1  666029285002620928  https://pbs.twimg.com/media/CT42GRgUYAA5iDo.jpg   \n",
       "2  666033412701032449  https://pbs.twimg.com/media/CT4521TWwAEvMyu.jpg   \n",
       "\n",
       "   img_num                      p1   p1_conf  p1_dog                  p2  \\\n",
       "0        1  Welsh_springer_spaniel  0.465074    True              collie   \n",
       "1        1                 redbone  0.506826    True  miniature_pinscher   \n",
       "2        1         German_shepherd  0.596461    True            malinois   \n",
       "\n",
       "    p2_conf  p2_dog                   p3   p3_conf  p3_dog  \n",
       "0  0.156665    True    Shetland_sheepdog  0.061428    True  \n",
       "1  0.074192    True  Rhodesian_ridgeback  0.072010    True  \n",
       "2  0.138584    True           bloodhound  0.116197    True  "
      ]
     },
     "execution_count": 43,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dog_pred.head(3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "id": "09f43e09",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 2075 entries, 0 to 2074\n",
      "Data columns (total 12 columns):\n",
      " #   Column    Non-Null Count  Dtype  \n",
      "---  ------    --------------  -----  \n",
      " 0   tweet_id  2075 non-null   int64  \n",
      " 1   jpg_url   2075 non-null   object \n",
      " 2   img_num   2075 non-null   int64  \n",
      " 3   p1        2075 non-null   object \n",
      " 4   p1_conf   2075 non-null   float64\n",
      " 5   p1_dog    2075 non-null   bool   \n",
      " 6   p2        2075 non-null   object \n",
      " 7   p2_conf   2075 non-null   float64\n",
      " 8   p2_dog    2075 non-null   bool   \n",
      " 9   p3        2075 non-null   object \n",
      " 10  p3_conf   2075 non-null   float64\n",
      " 11  p3_dog    2075 non-null   bool   \n",
      "dtypes: bool(3), float64(3), int64(2), object(4)\n",
      "memory usage: 152.1+ KB\n"
     ]
    }
   ],
   "source": [
    "# checking the general informationof the data\n",
    "dog_pred.info()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "230b1ef3",
   "metadata": {},
   "source": [
    "Checking rows with all false dog prediction "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "id": "e97d8c14",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
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       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
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       "    }\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>tweet_id</th>\n",
       "      <th>jpg_url</th>\n",
       "      <th>img_num</th>\n",
       "      <th>p1</th>\n",
       "      <th>p1_conf</th>\n",
       "      <th>p1_dog</th>\n",
       "      <th>p2</th>\n",
       "      <th>p2_conf</th>\n",
       "      <th>p2_dog</th>\n",
       "      <th>p3</th>\n",
       "      <th>p3_conf</th>\n",
       "      <th>p3_dog</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>666051853826850816</td>\n",
       "      <td>https://pbs.twimg.com/media/CT5KoJ1WoAAJash.jpg</td>\n",
       "      <td>1</td>\n",
       "      <td>box_turtle</td>\n",
       "      <td>0.933012</td>\n",
       "      <td>False</td>\n",
       "      <td>mud_turtle</td>\n",
       "      <td>0.045885</td>\n",
       "      <td>False</td>\n",
       "      <td>terrapin</td>\n",
       "      <td>0.017885</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>666104133288665088</td>\n",
       "      <td>https://pbs.twimg.com/media/CT56LSZWoAAlJj2.jpg</td>\n",
       "      <td>1</td>\n",
       "      <td>hen</td>\n",
       "      <td>0.965932</td>\n",
       "      <td>False</td>\n",
       "      <td>cock</td>\n",
       "      <td>0.033919</td>\n",
       "      <td>False</td>\n",
       "      <td>partridge</td>\n",
       "      <td>0.000052</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>666268910803644416</td>\n",
       "      <td>https://pbs.twimg.com/media/CT8QCd1WEAADXws.jpg</td>\n",
       "      <td>1</td>\n",
       "      <td>desktop_computer</td>\n",
       "      <td>0.086502</td>\n",
       "      <td>False</td>\n",
       "      <td>desk</td>\n",
       "      <td>0.085547</td>\n",
       "      <td>False</td>\n",
       "      <td>bookcase</td>\n",
       "      <td>0.079480</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>666293911632134144</td>\n",
       "      <td>https://pbs.twimg.com/media/CT8mx7KW4AEQu8N.jpg</td>\n",
       "      <td>1</td>\n",
       "      <td>three-toed_sloth</td>\n",
       "      <td>0.914671</td>\n",
       "      <td>False</td>\n",
       "      <td>otter</td>\n",
       "      <td>0.015250</td>\n",
       "      <td>False</td>\n",
       "      <td>great_grey_owl</td>\n",
       "      <td>0.013207</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>666362758909284353</td>\n",
       "      <td>https://pbs.twimg.com/media/CT9lXGsUcAAyUFt.jpg</td>\n",
       "      <td>1</td>\n",
       "      <td>guinea_pig</td>\n",
       "      <td>0.996496</td>\n",
       "      <td>False</td>\n",
       "      <td>skunk</td>\n",
       "      <td>0.002402</td>\n",
       "      <td>False</td>\n",
       "      <td>hamster</td>\n",
       "      <td>0.000461</td>\n",
       "      <td>False</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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021</th>\n",
       "      <td>880935762899988482</td>\n",
       "      <td>https://pbs.twimg.com/media/DDm2Z5aXUAEDS2u.jpg</td>\n",
       "      <td>1</td>\n",
       "      <td>street_sign</td>\n",
       "      <td>0.251801</td>\n",
       "      <td>False</td>\n",
       "      <td>umbrella</td>\n",
       "      <td>0.115123</td>\n",
       "      <td>False</td>\n",
       "      <td>traffic_light</td>\n",
       "      <td>0.069534</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022</th>\n",
       "      <td>881268444196462592</td>\n",
       "      <td>https://pbs.twimg.com/media/DDrk-f9WAAI-WQv.jpg</td>\n",
       "      <td>1</td>\n",
       "      <td>tusker</td>\n",
       "      <td>0.473303</td>\n",
       "      <td>False</td>\n",
       "      <td>Indian_elephant</td>\n",
       "      <td>0.245646</td>\n",
       "      <td>False</td>\n",
       "      <td>ibex</td>\n",
       "      <td>0.055661</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2046</th>\n",
       "      <td>886680336477933568</td>\n",
       "      <td>https://pbs.twimg.com/media/DE4fEDzWAAAyHMM.jpg</td>\n",
       "      <td>1</td>\n",
       "      <td>convertible</td>\n",
       "      <td>0.738995</td>\n",
       "      <td>False</td>\n",
       "      <td>sports_car</td>\n",
       "      <td>0.139952</td>\n",
       "      <td>False</td>\n",
       "      <td>car_wheel</td>\n",
       "      <td>0.044173</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2052</th>\n",
       "      <td>887517139158093824</td>\n",
       "      <td>https://pbs.twimg.com/ext_tw_video_thumb/88751...</td>\n",
       "      <td>1</td>\n",
       "      <td>limousine</td>\n",
       "      <td>0.130432</td>\n",
       "      <td>False</td>\n",
       "      <td>tow_truck</td>\n",
       "      <td>0.029175</td>\n",
       "      <td>False</td>\n",
       "      <td>shopping_cart</td>\n",
       "      <td>0.026321</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2074</th>\n",
       "      <td>892420643555336193</td>\n",
       "      <td>https://pbs.twimg.com/media/DGKD1-bXoAAIAUK.jpg</td>\n",
       "      <td>1</td>\n",
       "      <td>orange</td>\n",
       "      <td>0.097049</td>\n",
       "      <td>False</td>\n",
       "      <td>bagel</td>\n",
       "      <td>0.085851</td>\n",
       "      <td>False</td>\n",
       "      <td>banana</td>\n",
       "      <td>0.076110</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>324 rows × 12 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                tweet_id                                            jpg_url  \\\n",
       "6     666051853826850816    https://pbs.twimg.com/media/CT5KoJ1WoAAJash.jpg   \n",
       "17    666104133288665088    https://pbs.twimg.com/media/CT56LSZWoAAlJj2.jpg   \n",
       "18    666268910803644416    https://pbs.twimg.com/media/CT8QCd1WEAADXws.jpg   \n",
       "21    666293911632134144    https://pbs.twimg.com/media/CT8mx7KW4AEQu8N.jpg   \n",
       "25    666362758909284353    https://pbs.twimg.com/media/CT9lXGsUcAAyUFt.jpg   \n",
       "...                  ...                                                ...   \n",
       "2021  880935762899988482    https://pbs.twimg.com/media/DDm2Z5aXUAEDS2u.jpg   \n",
       "2022  881268444196462592    https://pbs.twimg.com/media/DDrk-f9WAAI-WQv.jpg   \n",
       "2046  886680336477933568    https://pbs.twimg.com/media/DE4fEDzWAAAyHMM.jpg   \n",
       "2052  887517139158093824  https://pbs.twimg.com/ext_tw_video_thumb/88751...   \n",
       "2074  892420643555336193    https://pbs.twimg.com/media/DGKD1-bXoAAIAUK.jpg   \n",
       "\n",
       "      img_num                p1   p1_conf  p1_dog               p2   p2_conf  \\\n",
       "6           1        box_turtle  0.933012   False       mud_turtle  0.045885   \n",
       "17          1               hen  0.965932   False             cock  0.033919   \n",
       "18          1  desktop_computer  0.086502   False             desk  0.085547   \n",
       "21          1  three-toed_sloth  0.914671   False            otter  0.015250   \n",
       "25          1        guinea_pig  0.996496   False            skunk  0.002402   \n",
       "...       ...               ...       ...     ...              ...       ...   \n",
       "2021        1       street_sign  0.251801   False         umbrella  0.115123   \n",
       "2022        1            tusker  0.473303   False  Indian_elephant  0.245646   \n",
       "2046        1       convertible  0.738995   False       sports_car  0.139952   \n",
       "2052        1         limousine  0.130432   False        tow_truck  0.029175   \n",
       "2074        1            orange  0.097049   False            bagel  0.085851   \n",
       "\n",
       "      p2_dog              p3   p3_conf  p3_dog  \n",
       "6      False        terrapin  0.017885   False  \n",
       "17     False       partridge  0.000052   False  \n",
       "18     False        bookcase  0.079480   False  \n",
       "21     False  great_grey_owl  0.013207   False  \n",
       "25     False         hamster  0.000461   False  \n",
       "...      ...             ...       ...     ...  \n",
       "2021   False   traffic_light  0.069534   False  \n",
       "2022   False            ibex  0.055661   False  \n",
       "2046   False       car_wheel  0.044173   False  \n",
       "2052   False   shopping_cart  0.026321   False  \n",
       "2074   False          banana  0.076110   False  \n",
       "\n",
       "[324 rows x 12 columns]"
      ]
     },
     "execution_count": 45,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dog_pred.query('(p1_dog == False) & (p2_dog == False) & (p3_dog == False)')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "66b602bb",
   "metadata": {},
   "source": [
    "checking duplicated image url"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "id": "f72aa4af",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "66"
      ]
     },
     "execution_count": 46,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sum(dog_pred['jpg_url'].duplicated())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "id": "fe326aef",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1    1780\n",
       "2     198\n",
       "3      66\n",
       "4      31\n",
       "Name: img_num, dtype: int64"
      ]
     },
     "execution_count": 47,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#counting individual value in img_num\n",
    "dog_pred['img_num'].value_counts()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "837d196b",
   "metadata": {},
   "source": [
    "#### QUALITY"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "16d139f2",
   "metadata": {},
   "source": [
    "**Twitter_archive**"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0738da75",
   "metadata": {},
   "source": [
    "--Timestamp and retweeted_status_timestamp datatype should be datatime\n",
    "\n",
    "--[tweet_id, retweeted_status_id, retweeted_status_user_id] should be object and not float[avoid operation being perform]\n",
    "\n",
    "--floofe, pupper,puppo,doggo has alot of missing value, indicated as None instead of NaN\n",
    "\n",
    "--Name has irrelevant names like \"a\",\"not\",\"all\",\"by\",\"the\",\"my\" etc\n",
    "\n",
    "--there are more than 1 dog stage e.g doggo and pupper(12), doggo and floofer(1), doggo and puppo(1)\n",
    "\n",
    "--Duplicated value in expanded_url"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "1e4bc060",
   "metadata": {},
   "source": [
    "**Tweet_data**"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "78cc2bd8",
   "metadata": {},
   "source": [
    "--tweet_id, create_date has incorrect datatype"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "663702ed",
   "metadata": {},
   "source": [
    "**dod_pred**"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a114726b",
   "metadata": {},
   "source": [
    "--duplicated values in jpg_url"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "86b1f529",
   "metadata": {},
   "source": [
    "#### TIDINESS"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "db830b06",
   "metadata": {},
   "source": [
    "**Twitter_archive**"
   ]
  },
  {
   "cell_type": "raw",
   "id": "2030a0c9",
   "metadata": {},
   "source": [
    "--[Doggo, puppo, pupper,floofer] should be in one column as \"stages\"\n",
    "\n",
    "--source having unnecessary html tags '<a href=\"http://twitter.com/download/iphone\" rel=\"nofollow\">Twitter for iPhone</a>'\n",
    "\n",
    "--in_reply_to_status_id and in_reply_to_user_id are not original data\n",
    "\n",
    "--Only the original tweet is needed, drop all retweet columnsi.e retweeted_status_id, retweeted_status_user_id, retweeted_status_timestamp"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3becc3d6",
   "metadata": {},
   "source": [
    "**Tweet_data**"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4e6bb7d4",
   "metadata": {},
   "source": [
    "--create_date exist in Twitter_archive as timestamp. therefore, create date should be drop"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b7024fae",
   "metadata": {},
   "source": [
    "**dog_pred**"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "21fc1382",
   "metadata": {},
   "source": [
    "--Ensure that all rows contain at least one true prediction"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7bbd1448",
   "metadata": {},
   "source": [
    "## Cleaning Data"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b2ad38a3",
   "metadata": {},
   "source": [
    "duplicate the three dataset"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "id": "af096059",
   "metadata": {},
   "outputs": [],
   "source": [
    "Twitter_archive_df= Twitter_archive.copy()\n",
    "Tweet_data_df = Tweet_data.copy()\n",
    "dog_pred_df = dog_pred.copy()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d2560710",
   "metadata": {},
   "source": [
    "**Quality issue 1 --Timestamp and retweeted_status_timestamp datatype should be datatime**"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0643d167",
   "metadata": {},
   "source": [
    "Define:\n",
    "changing the timestamp and retweeted_status_timestamp to datetime using .to_datetime function\n",
    "\n",
    "code"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "id": "3a3233fc",
   "metadata": {},
   "outputs": [],
   "source": [
    "Twitter_archive_df['timestamp'] = pd.to_datetime(Twitter_archive_df['timestamp'])\n",
    "Twitter_archive_df['retweeted_status_timestamp'] = pd.to_datetime(Twitter_archive_df['retweeted_status_timestamp'])"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "04df1be5",
   "metadata": {},
   "source": [
    "test"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "id": "724d1f8b",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 2356 entries, 0 to 2355\n",
      "Data columns (total 17 columns):\n",
      " #   Column                      Non-Null Count  Dtype              \n",
      "---  ------                      --------------  -----              \n",
      " 0   tweet_id                    2356 non-null   int64              \n",
      " 1   in_reply_to_status_id       78 non-null     float64            \n",
      " 2   in_reply_to_user_id         78 non-null     float64            \n",
      " 3   timestamp                   2356 non-null   datetime64[ns, UTC]\n",
      " 4   source                      2356 non-null   object             \n",
      " 5   text                        2356 non-null   object             \n",
      " 6   retweeted_status_id         181 non-null    float64            \n",
      " 7   retweeted_status_user_id    181 non-null    float64            \n",
      " 8   retweeted_status_timestamp  181 non-null    datetime64[ns, UTC]\n",
      " 9   expanded_urls               2297 non-null   object             \n",
      " 10  rating_numerator            2356 non-null   int64              \n",
      " 11  rating_denominator          2356 non-null   int64              \n",
      " 12  name                        2356 non-null   object             \n",
      " 13  doggo                       2356 non-null   object             \n",
      " 14  floofer                     2356 non-null   object             \n",
      " 15  pupper                      2356 non-null   object             \n",
      " 16  puppo                       2356 non-null   object             \n",
      "dtypes: datetime64[ns, UTC](2), float64(4), int64(3), object(8)\n",
      "memory usage: 313.0+ KB\n"
     ]
    }
   ],
   "source": [
    "Twitter_archive_df.info()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "bb949630",
   "metadata": {},
   "source": [
    "**Quality issue 2 --[tweet_id, retweeted_status_id, retweeted_status_user_id, in_reply_to_status_id, in_reply_to_user_id] should be object and not float[avoid operation being perform]**\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5965f06d",
   "metadata": {},
   "source": [
    "Define:\n",
    "change the datatype to object using .astype(object)\n",
    "\n",
    "code"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "id": "5163909e",
   "metadata": {},
   "outputs": [],
   "source": [
    "Twitter_archive_df['tweet_id'] = Twitter_archive_df['tweet_id'].astype(object)\n",
    "Twitter_archive_df['retweeted_status_id'] = Twitter_archive_df['retweeted_status_id'].astype(object)\n",
    "Twitter_archive_df['retweeted_status_user_id'] = Twitter_archive_df['retweeted_status_user_id'].astype(object)\n",
    "Twitter_archive_df['in_reply_to_status_id'] = Twitter_archive_df['in_reply_to_status_id'].astype(object)\n",
    "Twitter_archive_df['in_reply_to_user_id'] = Twitter_archive_df['in_reply_to_user_id'].astype(object)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0e3ebfed",
   "metadata": {},
   "source": [
    "Test"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "id": "33882773",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 2356 entries, 0 to 2355\n",
      "Data columns (total 17 columns):\n",
      " #   Column                      Non-Null Count  Dtype              \n",
      "---  ------                      --------------  -----              \n",
      " 0   tweet_id                    2356 non-null   object             \n",
      " 1   in_reply_to_status_id       78 non-null     object             \n",
      " 2   in_reply_to_user_id         78 non-null     object             \n",
      " 3   timestamp                   2356 non-null   datetime64[ns, UTC]\n",
      " 4   source                      2356 non-null   object             \n",
      " 5   text                        2356 non-null   object             \n",
      " 6   retweeted_status_id         181 non-null    object             \n",
      " 7   retweeted_status_user_id    181 non-null    object             \n",
      " 8   retweeted_status_timestamp  181 non-null    datetime64[ns, UTC]\n",
      " 9   expanded_urls               2297 non-null   object             \n",
      " 10  rating_numerator            2356 non-null   int64              \n",
      " 11  rating_denominator          2356 non-null   int64              \n",
      " 12  name                        2356 non-null   object             \n",
      " 13  doggo                       2356 non-null   object             \n",
      " 14  floofer                     2356 non-null   object             \n",
      " 15  pupper                      2356 non-null   object             \n",
      " 16  puppo                       2356 non-null   object             \n",
      "dtypes: datetime64[ns, UTC](2), int64(2), object(13)\n",
      "memory usage: 313.0+ KB\n"
     ]
    }
   ],
   "source": [
    "Twitter_archive_df.info()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b9b8e1c7",
   "metadata": {},
   "source": [
    "**Quality issue 4 --Name has irrelevant names like \"a\",\"not\",\"all\",\"by\",\"the\",\"my\" etc**"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b6ab0161",
   "metadata": {},
   "source": [
    "**Define:**\n",
    "Notice that all irrelevant names starts with lowercase.\n",
    "\n",
    "All lowercase name will be change to \"None\" then replace with NaN\n",
    "\n",
    "\n",
    "code"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "id": "3dfd6601",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(2356, 17)"
      ]
     },
     "execution_count": 53,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Twitter_archive_df.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "id": "baffa2e9",
   "metadata": {},
   "outputs": [],
   "source": [
    "Twitter_archive_df[[Twitter_archive_df['name'].str.match('[a-z]+')]] = 'None' #changing all lowercase name to None"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "id": "11596333",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "None          854\n",
       "Charlie        12\n",
       "Lucy           11\n",
       "Cooper         11\n",
       "Oliver         11\n",
       "             ... \n",
       "Devón           1\n",
       "Gert            1\n",
       "Dex             1\n",
       "Ace             1\n",
       "Christoper      1\n",
       "Name: name, Length: 932, dtype: int64"
      ]
     },
     "execution_count": 55,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Twitter_archive_df['name'].value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "id": "517f8293",
   "metadata": {},
   "outputs": [],
   "source": [
    "Twitter_archive_df['name'].replace('None', np.NAN, inplace=True) # Replace None with NaN"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "96514ad6",
   "metadata": {},
   "source": [
    "Test"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "id": "678ba502",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "854"
      ]
     },
     "execution_count": 57,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Twitter_archive_df['name'].isnull().sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "id": "5210c964",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>tweet_id</th>\n",
       "      <th>in_reply_to_status_id</th>\n",
       "      <th>in_reply_to_user_id</th>\n",
       "      <th>timestamp</th>\n",
       "      <th>source</th>\n",
       "      <th>text</th>\n",
       "      <th>retweeted_status_id</th>\n",
       "      <th>retweeted_status_user_id</th>\n",
       "      <th>retweeted_status_timestamp</th>\n",
       "      <th>expanded_urls</th>\n",
       "      <th>rating_numerator</th>\n",
       "      <th>rating_denominator</th>\n",
       "      <th>name</th>\n",
       "      <th>doggo</th>\n",
       "      <th>floofer</th>\n",
       "      <th>pupper</th>\n",
       "      <th>puppo</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "Empty DataFrame\n",
       "Columns: [tweet_id, in_reply_to_status_id, in_reply_to_user_id, timestamp, source, text, retweeted_status_id, retweeted_status_user_id, retweeted_status_timestamp, expanded_urls, rating_numerator, rating_denominator, name, doggo, floofer, pupper, puppo]\n",
       "Index: []"
      ]
     },
     "execution_count": 58,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Twitter_archive_df.query('name==\"None\"')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "93688f4e",
   "metadata": {},
   "source": [
    "**Quality issue 5 --there are more than 1 dog stage e.g doggo and pupper(12), doggo and floofer(1), doggo and puppo(1)**"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4c15217c",
   "metadata": {},
   "source": [
    "**Define:**\n",
    "As stated in dogtionary, doggo, pupper, puppo, and floofer are all dog stages.\n",
    "\n",
    "floofer is not completely a stage but it is a terms used to denote dog with excessive furs\n",
    "\n",
    "**Note:** It's not possible for a dog to exhibit two stages at the same time\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "65d60e35",
   "metadata": {},
   "source": [
    "# &"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c4e96d6e",
   "metadata": {},
   "source": [
    "**Quality issue 3 --floofer, pupper,puppo,doggo has alot of missing value, indicated as None instead of NaN**\n",
    "\n",
    "**Define:**\n",
    "Replacing all None value with NaN which is a standard form of null values. This will be done using .replace()\n",
    "\n",
    "code"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "id": "d1c6e219",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>tweet_id</th>\n",
       "      <th>in_reply_to_status_id</th>\n",
       "      <th>in_reply_to_user_id</th>\n",
       "      <th>timestamp</th>\n",
       "      <th>source</th>\n",
       "      <th>text</th>\n",
       "      <th>retweeted_status_id</th>\n",
       "      <th>retweeted_status_user_id</th>\n",
       "      <th>retweeted_status_timestamp</th>\n",
       "      <th>expanded_urls</th>\n",
       "      <th>rating_numerator</th>\n",
       "      <th>rating_denominator</th>\n",
       "      <th>name</th>\n",
       "      <th>doggo</th>\n",
       "      <th>floofer</th>\n",
       "      <th>pupper</th>\n",
       "      <th>puppo</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>200</th>\n",
       "      <td>854010172552949760</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2017-04-17 16:34:26+00:00</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>At first I thought this was a shy doggo, but i...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaT</td>\n",
       "      <td>https://twitter.com/dog_rates/status/854010172...</td>\n",
       "      <td>11</td>\n",
       "      <td>10</td>\n",
       "      <td>NaN</td>\n",
       "      <td>doggo</td>\n",
       "      <td>floofer</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "               tweet_id in_reply_to_status_id in_reply_to_user_id  \\\n",
       "200  854010172552949760                   NaN                 NaN   \n",
       "\n",
       "                     timestamp  \\\n",
       "200  2017-04-17 16:34:26+00:00   \n",
       "\n",
       "                                                source  \\\n",
       "200  <a href=\"http://twitter.com/download/iphone\" r...   \n",
       "\n",
       "                                                  text retweeted_status_id  \\\n",
       "200  At first I thought this was a shy doggo, but i...                 NaN   \n",
       "\n",
       "    retweeted_status_user_id retweeted_status_timestamp  \\\n",
       "200                      NaN                        NaT   \n",
       "\n",
       "                                         expanded_urls rating_numerator  \\\n",
       "200  https://twitter.com/dog_rates/status/854010172...               11   \n",
       "\n",
       "    rating_denominator name  doggo  floofer pupper puppo  \n",
       "200                 10  NaN  doggo  floofer   None  None  "
      ]
     },
     "execution_count": 59,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#it is possible for a dog stage to be doggo and has excessive furs\n",
    "Twitter_archive_df.query('doggo == \"doggo\" & floofer==\"floofer\"') "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "id": "0ff4fcc6",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "\n",
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       "        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>tweet_id</th>\n",
       "      <th>in_reply_to_status_id</th>\n",
       "      <th>in_reply_to_user_id</th>\n",
       "      <th>timestamp</th>\n",
       "      <th>source</th>\n",
       "      <th>text</th>\n",
       "      <th>retweeted_status_id</th>\n",
       "      <th>retweeted_status_user_id</th>\n",
       "      <th>retweeted_status_timestamp</th>\n",
       "      <th>expanded_urls</th>\n",
       "      <th>rating_numerator</th>\n",
       "      <th>rating_denominator</th>\n",
       "      <th>name</th>\n",
       "      <th>doggo</th>\n",
       "      <th>floofer</th>\n",
       "      <th>pupper</th>\n",
       "      <th>puppo</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>460</th>\n",
       "      <td>817777686764523521</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2017-01-07 16:59:28+00:00</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>This is Dido. She's playing the lead role in \"...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaT</td>\n",
       "      <td>https://twitter.com/dog_rates/status/817777686...</td>\n",
       "      <td>13</td>\n",
       "      <td>10</td>\n",
       "      <td>Dido</td>\n",
       "      <td>doggo</td>\n",
       "      <td>None</td>\n",
       "      <td>pupper</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>531</th>\n",
       "      <td>808106460588765185</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2016-12-12 00:29:28+00:00</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>Here we have Burke (pupper) and Dexter (doggo)...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaT</td>\n",
       "      <td>https://twitter.com/dog_rates/status/808106460...</td>\n",
       "      <td>12</td>\n",
       "      <td>10</td>\n",
       "      <td>NaN</td>\n",
       "      <td>doggo</td>\n",
       "      <td>None</td>\n",
       "      <td>pupper</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>565</th>\n",
       "      <td>802265048156610565</td>\n",
       "      <td>733109485275860992.0</td>\n",
       "      <td>4196983835.0</td>\n",
       "      <td>2016-11-25 21:37:47+00:00</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>Like doggo, like pupper version 2. Both 11/10 ...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaT</td>\n",
       "      <td>https://twitter.com/dog_rates/status/802265048...</td>\n",
       "      <td>11</td>\n",
       "      <td>10</td>\n",
       "      <td>NaN</td>\n",
       "      <td>doggo</td>\n",
       "      <td>None</td>\n",
       "      <td>pupper</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>575</th>\n",
       "      <td>801115127852503040</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2016-11-22 17:28:25+00:00</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>This is Bones. He's being haunted by another d...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaT</td>\n",
       "      <td>https://twitter.com/dog_rates/status/801115127...</td>\n",
       "      <td>12</td>\n",
       "      <td>10</td>\n",
       "      <td>Bones</td>\n",
       "      <td>doggo</td>\n",
       "      <td>None</td>\n",
       "      <td>pupper</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>705</th>\n",
       "      <td>785639753186217984</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2016-10-11 00:34:48+00:00</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>This is Pinot. He's a sophisticated doggo. You...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaT</td>\n",
       "      <td>https://twitter.com/dog_rates/status/785639753...</td>\n",
       "      <td>10</td>\n",
       "      <td>10</td>\n",
       "      <td>Pinot</td>\n",
       "      <td>doggo</td>\n",
       "      <td>None</td>\n",
       "      <td>pupper</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>733</th>\n",
       "      <td>781308096455073793</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2016-09-29 01:42:20+00:00</td>\n",
       "      <td>&lt;a href=\"http://vine.co\" rel=\"nofollow\"&gt;Vine -...</td>\n",
       "      <td>Pupper butt 1, Doggo 0. Both 12/10 https://t.c...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaT</td>\n",
       "      <td>https://vine.co/v/5rgu2Law2ut</td>\n",
       "      <td>12</td>\n",
       "      <td>10</td>\n",
       "      <td>NaN</td>\n",
       "      <td>doggo</td>\n",
       "      <td>None</td>\n",
       "      <td>pupper</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>778</th>\n",
       "      <td>775898661951791106</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2016-09-14 03:27:11+00:00</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>RT @dog_rates: Like father (doggo), like son (...</td>\n",
       "      <td>733109485275860992.0</td>\n",
       "      <td>4196983835.0</td>\n",
       "      <td>2016-05-19 01:38:16+00:00</td>\n",
       "      <td>https://twitter.com/dog_rates/status/733109485...</td>\n",
       "      <td>12</td>\n",
       "      <td>10</td>\n",
       "      <td>NaN</td>\n",
       "      <td>doggo</td>\n",
       "      <td>None</td>\n",
       "      <td>pupper</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>889</th>\n",
       "      <td>759793422261743616</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2016-07-31 16:50:42+00:00</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>Meet Maggie &amp;amp; Lila. Maggie is the doggo, L...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaT</td>\n",
       "      <td>https://twitter.com/dog_rates/status/759793422...</td>\n",
       "      <td>12</td>\n",
       "      <td>10</td>\n",
       "      <td>Maggie</td>\n",
       "      <td>doggo</td>\n",
       "      <td>None</td>\n",
       "      <td>pupper</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>956</th>\n",
       "      <td>751583847268179968</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2016-07-09 01:08:47+00:00</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>Please stop sending it pictures that don't eve...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaT</td>\n",
       "      <td>https://twitter.com/dog_rates/status/751583847...</td>\n",
       "      <td>5</td>\n",
       "      <td>10</td>\n",
       "      <td>NaN</td>\n",
       "      <td>doggo</td>\n",
       "      <td>None</td>\n",
       "      <td>pupper</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1113</th>\n",
       "      <td>733109485275860992</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2016-05-19 01:38:16+00:00</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>Like father (doggo), like son (pupper). Both 1...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaT</td>\n",
       "      <td>https://twitter.com/dog_rates/status/733109485...</td>\n",
       "      <td>12</td>\n",
       "      <td>10</td>\n",
       "      <td>NaN</td>\n",
       "      <td>doggo</td>\n",
       "      <td>None</td>\n",
       "      <td>pupper</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                tweet_id in_reply_to_status_id in_reply_to_user_id  \\\n",
       "460   817777686764523521                   NaN                 NaN   \n",
       "531   808106460588765185                   NaN                 NaN   \n",
       "565   802265048156610565  733109485275860992.0        4196983835.0   \n",
       "575   801115127852503040                   NaN                 NaN   \n",
       "705   785639753186217984                   NaN                 NaN   \n",
       "733   781308096455073793                   NaN                 NaN   \n",
       "778   775898661951791106                   NaN                 NaN   \n",
       "889   759793422261743616                   NaN                 NaN   \n",
       "956   751583847268179968                   NaN                 NaN   \n",
       "1113  733109485275860992                   NaN                 NaN   \n",
       "\n",
       "                      timestamp  \\\n",
       "460   2017-01-07 16:59:28+00:00   \n",
       "531   2016-12-12 00:29:28+00:00   \n",
       "565   2016-11-25 21:37:47+00:00   \n",
       "575   2016-11-22 17:28:25+00:00   \n",
       "705   2016-10-11 00:34:48+00:00   \n",
       "733   2016-09-29 01:42:20+00:00   \n",
       "778   2016-09-14 03:27:11+00:00   \n",
       "889   2016-07-31 16:50:42+00:00   \n",
       "956   2016-07-09 01:08:47+00:00   \n",
       "1113  2016-05-19 01:38:16+00:00   \n",
       "\n",
       "                                                 source  \\\n",
       "460   <a href=\"http://twitter.com/download/iphone\" r...   \n",
       "531   <a href=\"http://twitter.com/download/iphone\" r...   \n",
       "565   <a href=\"http://twitter.com/download/iphone\" r...   \n",
       "575   <a href=\"http://twitter.com/download/iphone\" r...   \n",
       "705   <a href=\"http://twitter.com/download/iphone\" r...   \n",
       "733   <a href=\"http://vine.co\" rel=\"nofollow\">Vine -...   \n",
       "778   <a href=\"http://twitter.com/download/iphone\" r...   \n",
       "889   <a href=\"http://twitter.com/download/iphone\" r...   \n",
       "956   <a href=\"http://twitter.com/download/iphone\" r...   \n",
       "1113  <a href=\"http://twitter.com/download/iphone\" r...   \n",
       "\n",
       "                                                   text   retweeted_status_id  \\\n",
       "460   This is Dido. She's playing the lead role in \"...                   NaN   \n",
       "531   Here we have Burke (pupper) and Dexter (doggo)...                   NaN   \n",
       "565   Like doggo, like pupper version 2. Both 11/10 ...                   NaN   \n",
       "575   This is Bones. He's being haunted by another d...                   NaN   \n",
       "705   This is Pinot. He's a sophisticated doggo. You...                   NaN   \n",
       "733   Pupper butt 1, Doggo 0. Both 12/10 https://t.c...                   NaN   \n",
       "778   RT @dog_rates: Like father (doggo), like son (...  733109485275860992.0   \n",
       "889   Meet Maggie &amp; Lila. Maggie is the doggo, L...                   NaN   \n",
       "956   Please stop sending it pictures that don't eve...                   NaN   \n",
       "1113  Like father (doggo), like son (pupper). Both 1...                   NaN   \n",
       "\n",
       "     retweeted_status_user_id retweeted_status_timestamp  \\\n",
       "460                       NaN                        NaT   \n",
       "531                       NaN                        NaT   \n",
       "565                       NaN                        NaT   \n",
       "575                       NaN                        NaT   \n",
       "705                       NaN                        NaT   \n",
       "733                       NaN                        NaT   \n",
       "778              4196983835.0  2016-05-19 01:38:16+00:00   \n",
       "889                       NaN                        NaT   \n",
       "956                       NaN                        NaT   \n",
       "1113                      NaN                        NaT   \n",
       "\n",
       "                                          expanded_urls rating_numerator  \\\n",
       "460   https://twitter.com/dog_rates/status/817777686...               13   \n",
       "531   https://twitter.com/dog_rates/status/808106460...               12   \n",
       "565   https://twitter.com/dog_rates/status/802265048...               11   \n",
       "575   https://twitter.com/dog_rates/status/801115127...               12   \n",
       "705   https://twitter.com/dog_rates/status/785639753...               10   \n",
       "733                       https://vine.co/v/5rgu2Law2ut               12   \n",
       "778   https://twitter.com/dog_rates/status/733109485...               12   \n",
       "889   https://twitter.com/dog_rates/status/759793422...               12   \n",
       "956   https://twitter.com/dog_rates/status/751583847...                5   \n",
       "1113  https://twitter.com/dog_rates/status/733109485...               12   \n",
       "\n",
       "     rating_denominator    name  doggo floofer  pupper puppo  \n",
       "460                  10    Dido  doggo    None  pupper  None  \n",
       "531                  10     NaN  doggo    None  pupper  None  \n",
       "565                  10     NaN  doggo    None  pupper  None  \n",
       "575                  10   Bones  doggo    None  pupper  None  \n",
       "705                  10   Pinot  doggo    None  pupper  None  \n",
       "733                  10     NaN  doggo    None  pupper  None  \n",
       "778                  10     NaN  doggo    None  pupper  None  \n",
       "889                  10  Maggie  doggo    None  pupper  None  \n",
       "956                  10     NaN  doggo    None  pupper  None  \n",
       "1113                 10     NaN  doggo    None  pupper  None  "
      ]
     },
     "execution_count": 60,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Twitter_archive_df.query('doggo == \"doggo\" & pupper.notna()')\n",
    "Twitter_archive_df.query('doggo == \"doggo\" & pupper==\"pupper\"')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "id": "5cb099bb",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>tweet_id</th>\n",
       "      <th>in_reply_to_status_id</th>\n",
       "      <th>in_reply_to_user_id</th>\n",
       "      <th>timestamp</th>\n",
       "      <th>source</th>\n",
       "      <th>text</th>\n",
       "      <th>retweeted_status_id</th>\n",
       "      <th>retweeted_status_user_id</th>\n",
       "      <th>retweeted_status_timestamp</th>\n",
       "      <th>expanded_urls</th>\n",
       "      <th>rating_numerator</th>\n",
       "      <th>rating_denominator</th>\n",
       "      <th>name</th>\n",
       "      <th>doggo</th>\n",
       "      <th>floofer</th>\n",
       "      <th>pupper</th>\n",
       "      <th>puppo</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>191</th>\n",
       "      <td>855851453814013952</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2017-04-22 18:31:02+00:00</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>Here's a puppo participating in the #ScienceMa...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaT</td>\n",
       "      <td>https://twitter.com/dog_rates/status/855851453...</td>\n",
       "      <td>13</td>\n",
       "      <td>10</td>\n",
       "      <td>NaN</td>\n",
       "      <td>doggo</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>puppo</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "               tweet_id in_reply_to_status_id in_reply_to_user_id  \\\n",
       "191  855851453814013952                   NaN                 NaN   \n",
       "\n",
       "                     timestamp  \\\n",
       "191  2017-04-22 18:31:02+00:00   \n",
       "\n",
       "                                                source  \\\n",
       "191  <a href=\"http://twitter.com/download/iphone\" r...   \n",
       "\n",
       "                                                  text retweeted_status_id  \\\n",
       "191  Here's a puppo participating in the #ScienceMa...                 NaN   \n",
       "\n",
       "    retweeted_status_user_id retweeted_status_timestamp  \\\n",
       "191                      NaN                        NaT   \n",
       "\n",
       "                                         expanded_urls rating_numerator  \\\n",
       "191  https://twitter.com/dog_rates/status/855851453...               13   \n",
       "\n",
       "    rating_denominator name  doggo floofer pupper  puppo  \n",
       "191                 10  NaN  doggo    None   None  puppo  "
      ]
     },
     "execution_count": 61,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Twitter_archive_df.query('doggo == \"doggo\" & puppo==\"puppo\"')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "00b11311",
   "metadata": {},
   "source": [
    "A big pupper is doggo while a small doggo is a pupper. Both terms are mostly used interchangeably\n",
    "\n",
    "Therefore setting None for pupper column with record  doggo and pupper [pupper coulmn]\n",
    "\n",
    "For the record with both puppo and doggo, the text[Here's a puppo participating in the #ScienceMa...] clearly stated puppo. Therefor setting doggo to None"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "id": "3ec894f7",
   "metadata": {},
   "outputs": [],
   "source": [
    "# set pupper column as None for records which have both doggo and pupper\n",
    "Twitter_archive_df['pupper'][(Twitter_archive_df.doggo == 'doggo') & (Twitter_archive_df.pupper == 'pupper')] = 'None'    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "id": "d87f91b1",
   "metadata": {},
   "outputs": [],
   "source": [
    "#Setting doggo to None\n",
    "Twitter_archive_df['doggo'][(Twitter_archive_df.doggo == 'doggo') & (Twitter_archive_df.puppo == 'puppo')] = 'None'  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "id": "fc29c29d",
   "metadata": {},
   "outputs": [],
   "source": [
    "#Setting floofer to NaN\n",
    "Twitter_archive_df['floofer'][(Twitter_archive_df.doggo == 'doggo') & (Twitter_archive_df.floofer == 'floofer')] = 'None'   "
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d8b0bbe5",
   "metadata": {},
   "source": [
    "Test"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "id": "28625e8a",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "\n",
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       "    }\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>tweet_id</th>\n",
       "      <th>in_reply_to_status_id</th>\n",
       "      <th>in_reply_to_user_id</th>\n",
       "      <th>timestamp</th>\n",
       "      <th>source</th>\n",
       "      <th>text</th>\n",
       "      <th>retweeted_status_id</th>\n",
       "      <th>retweeted_status_user_id</th>\n",
       "      <th>retweeted_status_timestamp</th>\n",
       "      <th>expanded_urls</th>\n",
       "      <th>rating_numerator</th>\n",
       "      <th>rating_denominator</th>\n",
       "      <th>name</th>\n",
       "      <th>doggo</th>\n",
       "      <th>floofer</th>\n",
       "      <th>pupper</th>\n",
       "      <th>puppo</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "Empty DataFrame\n",
       "Columns: [tweet_id, in_reply_to_status_id, in_reply_to_user_id, timestamp, source, text, retweeted_status_id, retweeted_status_user_id, retweeted_status_timestamp, expanded_urls, rating_numerator, rating_denominator, name, doggo, floofer, pupper, puppo]\n",
       "Index: []"
      ]
     },
     "execution_count": 65,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Twitter_archive_df.query('doggo == \"doggo\" & pupper==\"pupper\"')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 66,
   "id": "9eafb323",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\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>tweet_id</th>\n",
       "      <th>in_reply_to_status_id</th>\n",
       "      <th>in_reply_to_user_id</th>\n",
       "      <th>timestamp</th>\n",
       "      <th>source</th>\n",
       "      <th>text</th>\n",
       "      <th>retweeted_status_id</th>\n",
       "      <th>retweeted_status_user_id</th>\n",
       "      <th>retweeted_status_timestamp</th>\n",
       "      <th>expanded_urls</th>\n",
       "      <th>rating_numerator</th>\n",
       "      <th>rating_denominator</th>\n",
       "      <th>name</th>\n",
       "      <th>doggo</th>\n",
       "      <th>floofer</th>\n",
       "      <th>pupper</th>\n",
       "      <th>puppo</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "Empty DataFrame\n",
       "Columns: [tweet_id, in_reply_to_status_id, in_reply_to_user_id, timestamp, source, text, retweeted_status_id, retweeted_status_user_id, retweeted_status_timestamp, expanded_urls, rating_numerator, rating_denominator, name, doggo, floofer, pupper, puppo]\n",
       "Index: []"
      ]
     },
     "execution_count": 66,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Twitter_archive_df.query('doggo == \"doggo\" & floofer==\"floofer\"')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 67,
   "id": "8cb528a4",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
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       "\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>tweet_id</th>\n",
       "      <th>in_reply_to_status_id</th>\n",
       "      <th>in_reply_to_user_id</th>\n",
       "      <th>timestamp</th>\n",
       "      <th>source</th>\n",
       "      <th>text</th>\n",
       "      <th>retweeted_status_id</th>\n",
       "      <th>retweeted_status_user_id</th>\n",
       "      <th>retweeted_status_timestamp</th>\n",
       "      <th>expanded_urls</th>\n",
       "      <th>rating_numerator</th>\n",
       "      <th>rating_denominator</th>\n",
       "      <th>name</th>\n",
       "      <th>doggo</th>\n",
       "      <th>floofer</th>\n",
       "      <th>pupper</th>\n",
       "      <th>puppo</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "Empty DataFrame\n",
       "Columns: [tweet_id, in_reply_to_status_id, in_reply_to_user_id, timestamp, source, text, retweeted_status_id, retweeted_status_user_id, retweeted_status_timestamp, expanded_urls, rating_numerator, rating_denominator, name, doggo, floofer, pupper, puppo]\n",
       "Index: []"
      ]
     },
     "execution_count": 67,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Twitter_archive_df.query('doggo == \"doggo\" & puppo==\"puppo\"')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7a281143",
   "metadata": {},
   "source": [
    "Quality issue 3\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 68,
   "id": "0a5465cf",
   "metadata": {},
   "outputs": [],
   "source": [
    "Twitter_archive_df['floofer'].replace('None', np.NAN, inplace=True)\n",
    "Twitter_archive_df['pupper'].replace('None', np.NAN, inplace=True)\n",
    "Twitter_archive_df['puppo'].replace('None', np.NAN, inplace=True)\n",
    "Twitter_archive_df['doggo'].replace('None', np.NAN, inplace=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d34fedd9",
   "metadata": {},
   "source": [
    "Test"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 69,
   "id": "cf5d86d3",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "floofer    9\n",
      "Name: floofer, dtype: int64\n",
      "pupper    233\n",
      "Name: pupper, dtype: int64\n",
      "puppo    30\n",
      "Name: puppo, dtype: int64\n",
      "doggo    92\n",
      "Name: doggo, dtype: int64\n"
     ]
    }
   ],
   "source": [
    "print(Twitter_archive_df['floofer'].value_counts())\n",
    "print(Twitter_archive_df['pupper'].value_counts())\n",
    "print(Twitter_archive_df['puppo'].value_counts())\n",
    "print(Twitter_archive_df['doggo'].value_counts())"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2192641f",
   "metadata": {},
   "source": [
    "**Quality issue 6 --Duplicated values in expanded_urls**"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e77ab66b",
   "metadata": {},
   "source": [
    "**Define:** dropping duplicated values using .drop_duplicates()\n",
    "\n",
    "code"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 70,
   "id": "4a213fc3",
   "metadata": {},
   "outputs": [],
   "source": [
    "Twitter_archive_df.drop_duplicates('expanded_urls', inplace=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "66da69b8",
   "metadata": {},
   "source": [
    "**Test**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 71,
   "id": "f5c21aac",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0"
      ]
     },
     "execution_count": 71,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sum(Twitter_archive_df['expanded_urls'].duplicated())"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c93c53da",
   "metadata": {},
   "source": [
    "**Quality issue 7 --tweet_id, create_date has incorrect datatype**  [Tweet_data_df]"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "68d588a9",
   "metadata": {},
   "source": [
    "**Define:**\n",
    "changing the datatype using .astype\n",
    "\n",
    "code"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 72,
   "id": "e790ab3e",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 2354 entries, 0 to 2353\n",
      "Data columns (total 4 columns):\n",
      " #   Column          Non-Null Count  Dtype \n",
      "---  ------          --------------  ----- \n",
      " 0   tweet_id        2354 non-null   int64 \n",
      " 1   retweet_count   2354 non-null   int64 \n",
      " 2   favorite_count  2354 non-null   int64 \n",
      " 3   create_date     2354 non-null   object\n",
      "dtypes: int64(3), object(1)\n",
      "memory usage: 73.7+ KB\n"
     ]
    }
   ],
   "source": [
    "Tweet_data_df.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 73,
   "id": "ab14838a",
   "metadata": {},
   "outputs": [],
   "source": [
    "Tweet_data_df['tweet_id'] = Tweet_data_df['tweet_id'].astype(object)\n",
    "Tweet_data_df['create_date'] = pd.to_datetime(Tweet_data_df['create_date'])"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0b823d18",
   "metadata": {},
   "source": [
    "Test"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 74,
   "id": "d992671c",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 2354 entries, 0 to 2353\n",
      "Data columns (total 4 columns):\n",
      " #   Column          Non-Null Count  Dtype              \n",
      "---  ------          --------------  -----              \n",
      " 0   tweet_id        2354 non-null   object             \n",
      " 1   retweet_count   2354 non-null   int64              \n",
      " 2   favorite_count  2354 non-null   int64              \n",
      " 3   create_date     2354 non-null   datetime64[ns, UTC]\n",
      "dtypes: datetime64[ns, UTC](1), int64(2), object(1)\n",
      "memory usage: 73.7+ KB\n"
     ]
    }
   ],
   "source": [
    "Tweet_data_df.info()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3a761966",
   "metadata": {},
   "source": [
    "**Quality issue 8 --Duplicated values in jpg_url**  [dog_pred]"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "873db68d",
   "metadata": {},
   "source": [
    "**Define:**\n",
    "dropping duplicated values using .drop_duplicates()\n",
    "\n",
    "code"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 75,
   "id": "7b8d24c6",
   "metadata": {},
   "outputs": [],
   "source": [
    "dog_pred.drop_duplicates('jpg_url', inplace=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e1163c80",
   "metadata": {},
   "source": [
    "Test"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 76,
   "id": "d8c34437",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0"
      ]
     },
     "execution_count": 76,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sum(dog_pred['jpg_url'].duplicated())"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9c9cec50",
   "metadata": {},
   "source": [
    "**Tidiness issue 1 --[Doggo, puppo, pupper,floofer] should be in one column as \"stages\"**"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "373cb9ac",
   "metadata": {},
   "source": [
    "**Define:**\n",
    "Using .melt() function to solve the tidiness issue\n",
    "\n",
    "code"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 77,
   "id": "3a307484",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['tweet_id', 'in_reply_to_status_id', 'in_reply_to_user_id', 'timestamp',\n",
       "       'source', 'text', 'retweeted_status_id', 'retweeted_status_user_id',\n",
       "       'retweeted_status_timestamp', 'expanded_urls', 'rating_numerator',\n",
       "       'rating_denominator', 'name', 'doggo', 'floofer', 'pupper', 'puppo'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 77,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Twitter_archive_df.columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 78,
   "id": "60663ae0",
   "metadata": {},
   "outputs": [],
   "source": [
    "#using .melt() function\n",
    "Twitter_archive_df = pd.melt(Twitter_archive_df, id_vars=['tweet_id','in_reply_to_status_id',\n",
    "                                                         'in_reply_to_user_id','timestamp','source','text','retweeted_status_id',\n",
    "                                                        'retweeted_status_user_id','retweeted_status_timestamp',\n",
    "                                                        'expanded_urls','rating_numerator','rating_denominator','name'],\n",
    "                            value_vars=['doggo','floofer','pupper','puppo'], \n",
    "                            var_name='count_stages', value_name='dog_stages')\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 79,
   "id": "cd455b60",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>tweet_id</th>\n",
       "      <th>in_reply_to_status_id</th>\n",
       "      <th>in_reply_to_user_id</th>\n",
       "      <th>timestamp</th>\n",
       "      <th>source</th>\n",
       "      <th>text</th>\n",
       "      <th>retweeted_status_id</th>\n",
       "      <th>retweeted_status_user_id</th>\n",
       "      <th>retweeted_status_timestamp</th>\n",
       "      <th>expanded_urls</th>\n",
       "      <th>rating_numerator</th>\n",
       "      <th>rating_denominator</th>\n",
       "      <th>name</th>\n",
       "      <th>count_stages</th>\n",
       "      <th>dog_stages</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>892420643555336193</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2017-08-01 16:23:56+00:00</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>This is Phineas. He's a mystical boy. Only eve...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaT</td>\n",
       "      <td>https://twitter.com/dog_rates/status/892420643...</td>\n",
       "      <td>13</td>\n",
       "      <td>10</td>\n",
       "      <td>Phineas</td>\n",
       "      <td>doggo</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>892177421306343426</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2017-08-01 00:17:27+00:00</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>This is Tilly. She's just checking pup on you....</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaT</td>\n",
       "      <td>https://twitter.com/dog_rates/status/892177421...</td>\n",
       "      <td>13</td>\n",
       "      <td>10</td>\n",
       "      <td>Tilly</td>\n",
       "      <td>doggo</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "             tweet_id in_reply_to_status_id in_reply_to_user_id  \\\n",
       "0  892420643555336193                   NaN                 NaN   \n",
       "1  892177421306343426                   NaN                 NaN   \n",
       "\n",
       "                   timestamp  \\\n",
       "0  2017-08-01 16:23:56+00:00   \n",
       "1  2017-08-01 00:17:27+00:00   \n",
       "\n",
       "                                              source  \\\n",
       "0  <a href=\"http://twitter.com/download/iphone\" r...   \n",
       "1  <a href=\"http://twitter.com/download/iphone\" r...   \n",
       "\n",
       "                                                text retweeted_status_id  \\\n",
       "0  This is Phineas. He's a mystical boy. Only eve...                 NaN   \n",
       "1  This is Tilly. She's just checking pup on you....                 NaN   \n",
       "\n",
       "  retweeted_status_user_id retweeted_status_timestamp  \\\n",
       "0                      NaN                        NaT   \n",
       "1                      NaN                        NaT   \n",
       "\n",
       "                                       expanded_urls rating_numerator  \\\n",
       "0  https://twitter.com/dog_rates/status/892420643...               13   \n",
       "1  https://twitter.com/dog_rates/status/892177421...               13   \n",
       "\n",
       "  rating_denominator     name count_stages dog_stages  \n",
       "0                 10  Phineas        doggo        NaN  \n",
       "1                 10    Tilly        doggo        NaN  "
      ]
     },
     "execution_count": 79,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Twitter_archive_df.head(2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 80,
   "id": "2710e453",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(8456, 15)"
      ]
     },
     "execution_count": 80,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# checking the shape after performing melting\n",
    "Twitter_archive_df.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 81,
   "id": "911347dd",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([nan, 'doggo', 'floofer', 'pupper', 'puppo'], dtype=object)"
      ]
     },
     "execution_count": 81,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Twitter_archive_df['dog_stages'].unique()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "cf8c093a",
   "metadata": {},
   "source": [
    "Note: after performing melt function, each tweet_id has been duplicated 3ce the original"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 82,
   "id": "fbf1477f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "6342"
      ]
     },
     "execution_count": 82,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sum(Twitter_archive_df['tweet_id'].duplicated())"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "44a6511f",
   "metadata": {},
   "source": [
    "Sorting dog_stages to remove relative duplicate tweet_ids"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 83,
   "id": "ef539a24",
   "metadata": {},
   "outputs": [],
   "source": [
    "Twitter_archive_df = Twitter_archive_df.sort_values('dog_stages').drop_duplicates('tweet_id', keep='first')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ec737cf0",
   "metadata": {},
   "source": [
    "Test"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 84,
   "id": "6e62775b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0"
      ]
     },
     "execution_count": 84,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sum(Twitter_archive_df['tweet_id'].duplicated())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 85,
   "id": "30d9e61a",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "pupper     220\n",
       "doggo       85\n",
       "puppo       26\n",
       "floofer      9\n",
       "Name: dog_stages, dtype: int64"
      ]
     },
     "execution_count": 85,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Twitter_archive_df['dog_stages'].value_counts()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "34d3a90a",
   "metadata": {},
   "source": [
    "dropping count_stages column"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 86,
   "id": "f4c12c12",
   "metadata": {},
   "outputs": [],
   "source": [
    "Twitter_archive_df.drop('count_stages', axis=1, inplace=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5d73c84e",
   "metadata": {},
   "source": [
    "**Tidiness issue 2 --source having unnecessary html tags '<a href=\"http://twitter.com/download/iphone\" rel=\"nofollow\">Twitter for iPhone</a>'**"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b4b07649",
   "metadata": {},
   "source": [
    "**Define:**\n",
    "extracting source in-between html tags"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3d6f77be",
   "metadata": {},
   "source": [
    "Randomly displaying source content\n",
    "\n",
    "code"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 87,
   "id": "9b65fba2",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "2342    <a href=\"http://twitter.com/download/iphone\" r...\n",
       "735     <a href=\"http://twitter.com/download/iphone\" r...\n",
       "1863    <a href=\"http://twitter.com/download/iphone\" r...\n",
       "1272    <a href=\"http://twitter.com/download/iphone\" r...\n",
       "Name: source, dtype: object"
      ]
     },
     "execution_count": 87,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Twitter_archive['source'].sample(4)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 88,
   "id": "1023396f",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\USER\\AppData\\Local\\Temp\\ipykernel_15200\\1119520696.py:1: FutureWarning: The default value of regex will change from True to False in a future version.\n",
      "  Twitter_archive_df['source'] = Twitter_archive_df['source'].str.replace(r'<(?:a\\b[^>]*>|/a>)', '')\n"
     ]
    }
   ],
   "source": [
    "Twitter_archive_df['source'] = Twitter_archive_df['source'].str.replace(r'<(?:a\\b[^>]*>|/a>)', '')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a5be2187",
   "metadata": {},
   "source": [
    "Test"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 89,
   "id": "8df9f4fa",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Twitter for iPhone     1989\n",
       "Vine - Make a Scene      87\n",
       "Twitter Web Client       28\n",
       "TweetDeck                 9\n",
       "None                      1\n",
       "Name: source, dtype: int64"
      ]
     },
     "execution_count": 89,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Twitter_archive_df['source'].value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 90,
   "id": "5f6a63af",
   "metadata": {},
   "outputs": [],
   "source": [
    "Twitter_archive_df['source'].replace('None', np.NAN, inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 91,
   "id": "a64c437d",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Changing the dtype to categorical\n",
    "\n",
    "Twitter_archive_df['source'] = Twitter_archive_df['source'].astype('category')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "40a5118d",
   "metadata": {},
   "source": [
    "Test"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 92,
   "id": "4040c5a3",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Twitter for iPhone     1989\n",
       "Vine - Make a Scene      87\n",
       "Twitter Web Client       28\n",
       "TweetDeck                 9\n",
       "Name: source, dtype: int64"
      ]
     },
     "execution_count": 92,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Twitter_archive_df['source'].value_counts()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b6538e57",
   "metadata": {},
   "source": [
    "**Tidiness issue 3 --in_reply_to_status_id and in_reply_to_user_id are not original data** "
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c0f6129e",
   "metadata": {},
   "source": [
    "**Define:**\n",
    "Drop all rows that has in_reply_to_status_id and in_reply_to_user_id value and drop the columns as well. They are not original data.\n",
    "\n",
    "code"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 93,
   "id": "6dc70568",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>tweet_id</th>\n",
       "      <th>in_reply_to_status_id</th>\n",
       "      <th>in_reply_to_user_id</th>\n",
       "      <th>timestamp</th>\n",
       "      <th>source</th>\n",
       "      <th>text</th>\n",
       "      <th>retweeted_status_id</th>\n",
       "      <th>retweeted_status_user_id</th>\n",
       "      <th>retweeted_status_timestamp</th>\n",
       "      <th>expanded_urls</th>\n",
       "      <th>rating_numerator</th>\n",
       "      <th>rating_denominator</th>\n",
       "      <th>name</th>\n",
       "      <th>dog_stages</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>504</th>\n",
       "      <td>802265048156610565</td>\n",
       "      <td>733109485275860992.0</td>\n",
       "      <td>4196983835.0</td>\n",
       "      <td>2016-11-25 21:37:47+00:00</td>\n",
       "      <td>Twitter for iPhone</td>\n",
       "      <td>Like doggo, like pupper version 2. Both 11/10 ...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaT</td>\n",
       "      <td>https://twitter.com/dog_rates/status/802265048...</td>\n",
       "      <td>11</td>\n",
       "      <td>10</td>\n",
       "      <td>NaN</td>\n",
       "      <td>doggo</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5547</th>\n",
       "      <td>694356675654983680</td>\n",
       "      <td>670668383499735040.0</td>\n",
       "      <td>4196983835.0</td>\n",
       "      <td>2016-02-02 03:08:26+00:00</td>\n",
       "      <td>Twitter for iPhone</td>\n",
       "      <td>This pupper only appears through the hole of a...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaT</td>\n",
       "      <td>https://twitter.com/dog_rates/status/694356675...</td>\n",
       "      <td>10</td>\n",
       "      <td>10</td>\n",
       "      <td>NaN</td>\n",
       "      <td>pupper</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5429</th>\n",
       "      <td>705786532653883392</td>\n",
       "      <td>703255935813287936.0</td>\n",
       "      <td>4196983835.0</td>\n",
       "      <td>2016-03-04 16:06:36+00:00</td>\n",
       "      <td>Twitter for iPhone</td>\n",
       "      <td>Seriously, add us 🐶 11/10 for sad wet pupper h...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaT</td>\n",
       "      <td>https://twitter.com/dog_rates/status/705786532...</td>\n",
       "      <td>11</td>\n",
       "      <td>10</td>\n",
       "      <td>NaN</td>\n",
       "      <td>pupper</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>NaN</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30</th>\n",
       "      <td>886267009285017600</td>\n",
       "      <td>886266357075128320.0</td>\n",
       "      <td>2281181600.0</td>\n",
       "      <td>2017-07-15 16:51:35+00:00</td>\n",
       "      <td>Twitter for iPhone</td>\n",
       "      <td>@NonWhiteHat @MayhewMayhem omg hello tanner yo...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaT</td>\n",
       "      <td>NaN</td>\n",
       "      <td>12</td>\n",
       "      <td>10</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>137</th>\n",
       "      <td>863079547188785154</td>\n",
       "      <td>667152164079423488.0</td>\n",
       "      <td>4196983835.0</td>\n",
       "      <td>2017-05-12 17:12:53+00:00</td>\n",
       "      <td>Twitter for iPhone</td>\n",
       "      <td>Ladies and gentlemen... I found Pipsy. He may ...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaT</td>\n",
       "      <td>https://twitter.com/dog_rates/status/863079547...</td>\n",
       "      <td>14</td>\n",
       "      <td>10</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>168</th>\n",
       "      <td>856526610513747968</td>\n",
       "      <td>855818117272018944.0</td>\n",
       "      <td>4196983835.0</td>\n",
       "      <td>2017-04-24 15:13:52+00:00</td>\n",
       "      <td>Twitter for iPhone</td>\n",
       "      <td>THIS IS CHARLIE, MARK. HE DID JUST WANT TO SAY...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaT</td>\n",
       "      <td>https://twitter.com/dog_rates/status/856526610...</td>\n",
       "      <td>14</td>\n",
       "      <td>10</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>227</th>\n",
       "      <td>844979544864018432</td>\n",
       "      <td>759099523532779520.0</td>\n",
       "      <td>4196983835.0</td>\n",
       "      <td>2017-03-23 18:29:57+00:00</td>\n",
       "      <td>Twitter for iPhone</td>\n",
       "      <td>PUPDATE: I'm proud to announce that Toby is 23...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaT</td>\n",
       "      <td>https://twitter.com/dog_rates/status/844979544...</td>\n",
       "      <td>13</td>\n",
       "      <td>10</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>910</th>\n",
       "      <td>746906459439529985</td>\n",
       "      <td>746885919387574272.0</td>\n",
       "      <td>4196983835.0</td>\n",
       "      <td>2016-06-26 03:22:31+00:00</td>\n",
       "      <td>Twitter for iPhone</td>\n",
       "      <td>PUPDATE: can't see any. Even if I could, I cou...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaT</td>\n",
       "      <td>https://twitter.com/dog_rates/status/746906459...</td>\n",
       "      <td>0</td>\n",
       "      <td>10</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>911</th>\n",
       "      <td>746818907684614144</td>\n",
       "      <td>691416866452082688.0</td>\n",
       "      <td>4196983835.0</td>\n",
       "      <td>2016-06-25 21:34:37+00:00</td>\n",
       "      <td>Twitter for iPhone</td>\n",
       "      <td>Guys... Dog Jesus 2.0\\n13/10 buoyant af https:...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaT</td>\n",
       "      <td>https://twitter.com/dog_rates/status/746818907...</td>\n",
       "      <td>13</td>\n",
       "      <td>10</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1005</th>\n",
       "      <td>729838605770891264</td>\n",
       "      <td>729113531270991872.0</td>\n",
       "      <td>4196983835.0</td>\n",
       "      <td>2016-05-10 01:00:58+00:00</td>\n",
       "      <td>Twitter for iPhone</td>\n",
       "      <td>\"Challenge completed\" \\n(pupgraded to 12/10) h...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaT</td>\n",
       "      <td>https://twitter.com/dog_rates/status/729838605...</td>\n",
       "      <td>12</td>\n",
       "      <td>10</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1210</th>\n",
       "      <td>704871453724954624</td>\n",
       "      <td>667152164079423488.0</td>\n",
       "      <td>4196983835.0</td>\n",
       "      <td>2016-03-02 03:30:25+00:00</td>\n",
       "      <td>Twitter for iPhone</td>\n",
       "      <td>I found a forest Pipsy. 12/10 https://t.co/mIQ...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaT</td>\n",
       "      <td>https://twitter.com/dog_rates/status/704871453...</td>\n",
       "      <td>12</td>\n",
       "      <td>10</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1223</th>\n",
       "      <td>703425003149250560</td>\n",
       "      <td>703041949650034688.0</td>\n",
       "      <td>4196983835.0</td>\n",
       "      <td>2016-02-27 03:42:44+00:00</td>\n",
       "      <td>Twitter for iPhone</td>\n",
       "      <td>Really guys? Again? I know this is a rare Alba...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaT</td>\n",
       "      <td>https://twitter.com/dog_rates/status/703425003...</td>\n",
       "      <td>9</td>\n",
       "      <td>10</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1309</th>\n",
       "      <td>695767669421768709</td>\n",
       "      <td>675349384339542016.0</td>\n",
       "      <td>4196983835.0</td>\n",
       "      <td>2016-02-06 00:35:13+00:00</td>\n",
       "      <td>Twitter for iPhone</td>\n",
       "      <td>If you are aware of who is making these please...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaT</td>\n",
       "      <td>https://twitter.com/dog_rates/status/695767669...</td>\n",
       "      <td>13</td>\n",
       "      <td>10</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1351</th>\n",
       "      <td>692142790915014657</td>\n",
       "      <td>692041934689402880.0</td>\n",
       "      <td>4196983835.0</td>\n",
       "      <td>2016-01-27 00:31:15+00:00</td>\n",
       "      <td>Twitter for iPhone</td>\n",
       "      <td>These are some pictures of Teddy that further ...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaT</td>\n",
       "      <td>https://twitter.com/dog_rates/status/692142790...</td>\n",
       "      <td>13</td>\n",
       "      <td>10</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1473</th>\n",
       "      <td>684538444857667585</td>\n",
       "      <td>684481074559381504.0</td>\n",
       "      <td>4196983835.0</td>\n",
       "      <td>2016-01-06 00:54:18+00:00</td>\n",
       "      <td>Twitter for iPhone</td>\n",
       "      <td>After watching this video, we've determined th...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaT</td>\n",
       "      <td>https://twitter.com/dog_rates/status/684538444...</td>\n",
       "      <td>12</td>\n",
       "      <td>10</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1477</th>\n",
       "      <td>684225744407494656</td>\n",
       "      <td>684222868335505408.0</td>\n",
       "      <td>4196983835.0</td>\n",
       "      <td>2016-01-05 04:11:44+00:00</td>\n",
       "      <td>Twitter for iPhone</td>\n",
       "      <td>Two sneaky puppers were not initially seen, mo...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaT</td>\n",
       "      <td>https://twitter.com/dog_rates/status/684225744...</td>\n",
       "      <td>143</td>\n",
       "      <td>130</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1668</th>\n",
       "      <td>675870721063669760</td>\n",
       "      <td>675707330206547968.0</td>\n",
       "      <td>4196983835.0</td>\n",
       "      <td>2015-12-13 02:51:51+00:00</td>\n",
       "      <td>Twitter for iPhone</td>\n",
       "      <td>&amp;amp; this is Yoshi. Another world record cont...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaT</td>\n",
       "      <td>https://twitter.com/dog_rates/status/675870721...</td>\n",
       "      <td>11</td>\n",
       "      <td>10</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1677</th>\n",
       "      <td>675707330206547968</td>\n",
       "      <td>675497103322386432.0</td>\n",
       "      <td>4196983835.0</td>\n",
       "      <td>2015-12-12 16:02:36+00:00</td>\n",
       "      <td>Twitter for iPhone</td>\n",
       "      <td>We've got ourselves a battle here. Watch out R...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaT</td>\n",
       "      <td>https://twitter.com/dog_rates/status/675707330...</td>\n",
       "      <td>11</td>\n",
       "      <td>10</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1689</th>\n",
       "      <td>675349384339542016</td>\n",
       "      <td>674999807681908736.0</td>\n",
       "      <td>4196983835.0</td>\n",
       "      <td>2015-12-11 16:20:15+00:00</td>\n",
       "      <td>Twitter for iPhone</td>\n",
       "      <td>Yea I lied. Here's more. All 13/10 https://t.c...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaT</td>\n",
       "      <td>https://twitter.com/dog_rates/status/675349384...</td>\n",
       "      <td>13</td>\n",
       "      <td>10</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1703</th>\n",
       "      <td>674999807681908736</td>\n",
       "      <td>674793399141146624.0</td>\n",
       "      <td>4196983835.0</td>\n",
       "      <td>2015-12-10 17:11:09+00:00</td>\n",
       "      <td>Twitter for iPhone</td>\n",
       "      <td>Ok last one of these. I may try to make some m...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaT</td>\n",
       "      <td>https://twitter.com/dog_rates/status/674999807...</td>\n",
       "      <td>13</td>\n",
       "      <td>10</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1706</th>\n",
       "      <td>674793399141146624</td>\n",
       "      <td>671729906628341760.0</td>\n",
       "      <td>4196983835.0</td>\n",
       "      <td>2015-12-10 03:30:58+00:00</td>\n",
       "      <td>Twitter for iPhone</td>\n",
       "      <td>I have found another. 13/10 https://t.co/HwroP...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaT</td>\n",
       "      <td>https://twitter.com/dog_rates/status/674793399...</td>\n",
       "      <td>13</td>\n",
       "      <td>10</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1713</th>\n",
       "      <td>674754018082705410</td>\n",
       "      <td>674752233200820224.0</td>\n",
       "      <td>4196983835.0</td>\n",
       "      <td>2015-12-10 00:54:28+00:00</td>\n",
       "      <td>Twitter for iPhone</td>\n",
       "      <td>Just received another perfect photo of dogs an...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaT</td>\n",
       "      <td>https://twitter.com/dog_rates/status/674754018...</td>\n",
       "      <td>12</td>\n",
       "      <td>10</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1842</th>\n",
       "      <td>671729906628341761</td>\n",
       "      <td>671561002136281088.0</td>\n",
       "      <td>4196983835.0</td>\n",
       "      <td>2015-12-01 16:37:44+00:00</td>\n",
       "      <td>Twitter for iPhone</td>\n",
       "      <td>I'm just going to leave this one here as well....</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaT</td>\n",
       "      <td>https://twitter.com/dog_rates/status/671729906...</td>\n",
       "      <td>13</td>\n",
       "      <td>10</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1965</th>\n",
       "      <td>669353438988365824</td>\n",
       "      <td>667806454573760512.0</td>\n",
       "      <td>4196983835.0</td>\n",
       "      <td>2015-11-25 03:14:30+00:00</td>\n",
       "      <td>Twitter for iPhone</td>\n",
       "      <td>This is Tessa. She is also very pleased after ...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaT</td>\n",
       "      <td>https://twitter.com/dog_rates/status/669353438...</td>\n",
       "      <td>10</td>\n",
       "      <td>10</td>\n",
       "      <td>Tessa</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                tweet_id in_reply_to_status_id in_reply_to_user_id  \\\n",
       "504   802265048156610565  733109485275860992.0        4196983835.0   \n",
       "5547  694356675654983680  670668383499735040.0        4196983835.0   \n",
       "5429  705786532653883392  703255935813287936.0        4196983835.0   \n",
       "22                  None                  None                None   \n",
       "30    886267009285017600  886266357075128320.0        2281181600.0   \n",
       "137   863079547188785154  667152164079423488.0        4196983835.0   \n",
       "168   856526610513747968  855818117272018944.0        4196983835.0   \n",
       "227   844979544864018432  759099523532779520.0        4196983835.0   \n",
       "910   746906459439529985  746885919387574272.0        4196983835.0   \n",
       "911   746818907684614144  691416866452082688.0        4196983835.0   \n",
       "1005  729838605770891264  729113531270991872.0        4196983835.0   \n",
       "1210  704871453724954624  667152164079423488.0        4196983835.0   \n",
       "1223  703425003149250560  703041949650034688.0        4196983835.0   \n",
       "1309  695767669421768709  675349384339542016.0        4196983835.0   \n",
       "1351  692142790915014657  692041934689402880.0        4196983835.0   \n",
       "1473  684538444857667585  684481074559381504.0        4196983835.0   \n",
       "1477  684225744407494656  684222868335505408.0        4196983835.0   \n",
       "1668  675870721063669760  675707330206547968.0        4196983835.0   \n",
       "1677  675707330206547968  675497103322386432.0        4196983835.0   \n",
       "1689  675349384339542016  674999807681908736.0        4196983835.0   \n",
       "1703  674999807681908736  674793399141146624.0        4196983835.0   \n",
       "1706  674793399141146624  671729906628341760.0        4196983835.0   \n",
       "1713  674754018082705410  674752233200820224.0        4196983835.0   \n",
       "1842  671729906628341761  671561002136281088.0        4196983835.0   \n",
       "1965  669353438988365824  667806454573760512.0        4196983835.0   \n",
       "\n",
       "                      timestamp              source  \\\n",
       "504   2016-11-25 21:37:47+00:00  Twitter for iPhone   \n",
       "5547  2016-02-02 03:08:26+00:00  Twitter for iPhone   \n",
       "5429  2016-03-04 16:06:36+00:00  Twitter for iPhone   \n",
       "22                         None                 NaN   \n",
       "30    2017-07-15 16:51:35+00:00  Twitter for iPhone   \n",
       "137   2017-05-12 17:12:53+00:00  Twitter for iPhone   \n",
       "168   2017-04-24 15:13:52+00:00  Twitter for iPhone   \n",
       "227   2017-03-23 18:29:57+00:00  Twitter for iPhone   \n",
       "910   2016-06-26 03:22:31+00:00  Twitter for iPhone   \n",
       "911   2016-06-25 21:34:37+00:00  Twitter for iPhone   \n",
       "1005  2016-05-10 01:00:58+00:00  Twitter for iPhone   \n",
       "1210  2016-03-02 03:30:25+00:00  Twitter for iPhone   \n",
       "1223  2016-02-27 03:42:44+00:00  Twitter for iPhone   \n",
       "1309  2016-02-06 00:35:13+00:00  Twitter for iPhone   \n",
       "1351  2016-01-27 00:31:15+00:00  Twitter for iPhone   \n",
       "1473  2016-01-06 00:54:18+00:00  Twitter for iPhone   \n",
       "1477  2016-01-05 04:11:44+00:00  Twitter for iPhone   \n",
       "1668  2015-12-13 02:51:51+00:00  Twitter for iPhone   \n",
       "1677  2015-12-12 16:02:36+00:00  Twitter for iPhone   \n",
       "1689  2015-12-11 16:20:15+00:00  Twitter for iPhone   \n",
       "1703  2015-12-10 17:11:09+00:00  Twitter for iPhone   \n",
       "1706  2015-12-10 03:30:58+00:00  Twitter for iPhone   \n",
       "1713  2015-12-10 00:54:28+00:00  Twitter for iPhone   \n",
       "1842  2015-12-01 16:37:44+00:00  Twitter for iPhone   \n",
       "1965  2015-11-25 03:14:30+00:00  Twitter for iPhone   \n",
       "\n",
       "                                                   text retweeted_status_id  \\\n",
       "504   Like doggo, like pupper version 2. Both 11/10 ...                 NaN   \n",
       "5547  This pupper only appears through the hole of a...                 NaN   \n",
       "5429  Seriously, add us 🐶 11/10 for sad wet pupper h...                 NaN   \n",
       "22                                                 None                None   \n",
       "30    @NonWhiteHat @MayhewMayhem omg hello tanner yo...                 NaN   \n",
       "137   Ladies and gentlemen... I found Pipsy. He may ...                 NaN   \n",
       "168   THIS IS CHARLIE, MARK. HE DID JUST WANT TO SAY...                 NaN   \n",
       "227   PUPDATE: I'm proud to announce that Toby is 23...                 NaN   \n",
       "910   PUPDATE: can't see any. Even if I could, I cou...                 NaN   \n",
       "911   Guys... Dog Jesus 2.0\\n13/10 buoyant af https:...                 NaN   \n",
       "1005  \"Challenge completed\" \\n(pupgraded to 12/10) h...                 NaN   \n",
       "1210  I found a forest Pipsy. 12/10 https://t.co/mIQ...                 NaN   \n",
       "1223  Really guys? Again? I know this is a rare Alba...                 NaN   \n",
       "1309  If you are aware of who is making these please...                 NaN   \n",
       "1351  These are some pictures of Teddy that further ...                 NaN   \n",
       "1473  After watching this video, we've determined th...                 NaN   \n",
       "1477  Two sneaky puppers were not initially seen, mo...                 NaN   \n",
       "1668  &amp; this is Yoshi. Another world record cont...                 NaN   \n",
       "1677  We've got ourselves a battle here. Watch out R...                 NaN   \n",
       "1689  Yea I lied. Here's more. All 13/10 https://t.c...                 NaN   \n",
       "1703  Ok last one of these. I may try to make some m...                 NaN   \n",
       "1706  I have found another. 13/10 https://t.co/HwroP...                 NaN   \n",
       "1713  Just received another perfect photo of dogs an...                 NaN   \n",
       "1842  I'm just going to leave this one here as well....                 NaN   \n",
       "1965  This is Tessa. She is also very pleased after ...                 NaN   \n",
       "\n",
       "     retweeted_status_user_id retweeted_status_timestamp  \\\n",
       "504                       NaN                        NaT   \n",
       "5547                      NaN                        NaT   \n",
       "5429                      NaN                        NaT   \n",
       "22                       None                       None   \n",
       "30                        NaN                        NaT   \n",
       "137                       NaN                        NaT   \n",
       "168                       NaN                        NaT   \n",
       "227                       NaN                        NaT   \n",
       "910                       NaN                        NaT   \n",
       "911                       NaN                        NaT   \n",
       "1005                      NaN                        NaT   \n",
       "1210                      NaN                        NaT   \n",
       "1223                      NaN                        NaT   \n",
       "1309                      NaN                        NaT   \n",
       "1351                      NaN                        NaT   \n",
       "1473                      NaN                        NaT   \n",
       "1477                      NaN                        NaT   \n",
       "1668                      NaN                        NaT   \n",
       "1677                      NaN                        NaT   \n",
       "1689                      NaN                        NaT   \n",
       "1703                      NaN                        NaT   \n",
       "1706                      NaN                        NaT   \n",
       "1713                      NaN                        NaT   \n",
       "1842                      NaN                        NaT   \n",
       "1965                      NaN                        NaT   \n",
       "\n",
       "                                          expanded_urls rating_numerator  \\\n",
       "504   https://twitter.com/dog_rates/status/802265048...               11   \n",
       "5547  https://twitter.com/dog_rates/status/694356675...               10   \n",
       "5429  https://twitter.com/dog_rates/status/705786532...               11   \n",
       "22                                                 None             None   \n",
       "30                                                  NaN               12   \n",
       "137   https://twitter.com/dog_rates/status/863079547...               14   \n",
       "168   https://twitter.com/dog_rates/status/856526610...               14   \n",
       "227   https://twitter.com/dog_rates/status/844979544...               13   \n",
       "910   https://twitter.com/dog_rates/status/746906459...                0   \n",
       "911   https://twitter.com/dog_rates/status/746818907...               13   \n",
       "1005  https://twitter.com/dog_rates/status/729838605...               12   \n",
       "1210  https://twitter.com/dog_rates/status/704871453...               12   \n",
       "1223  https://twitter.com/dog_rates/status/703425003...                9   \n",
       "1309  https://twitter.com/dog_rates/status/695767669...               13   \n",
       "1351  https://twitter.com/dog_rates/status/692142790...               13   \n",
       "1473  https://twitter.com/dog_rates/status/684538444...               12   \n",
       "1477  https://twitter.com/dog_rates/status/684225744...              143   \n",
       "1668  https://twitter.com/dog_rates/status/675870721...               11   \n",
       "1677  https://twitter.com/dog_rates/status/675707330...               11   \n",
       "1689  https://twitter.com/dog_rates/status/675349384...               13   \n",
       "1703  https://twitter.com/dog_rates/status/674999807...               13   \n",
       "1706  https://twitter.com/dog_rates/status/674793399...               13   \n",
       "1713  https://twitter.com/dog_rates/status/674754018...               12   \n",
       "1842  https://twitter.com/dog_rates/status/671729906...               13   \n",
       "1965  https://twitter.com/dog_rates/status/669353438...               10   \n",
       "\n",
       "     rating_denominator   name dog_stages  \n",
       "504                  10    NaN      doggo  \n",
       "5547                 10    NaN     pupper  \n",
       "5429                 10    NaN     pupper  \n",
       "22                 None    NaN        NaN  \n",
       "30                   10    NaN        NaN  \n",
       "137                  10    NaN        NaN  \n",
       "168                  10    NaN        NaN  \n",
       "227                  10    NaN        NaN  \n",
       "910                  10    NaN        NaN  \n",
       "911                  10    NaN        NaN  \n",
       "1005                 10    NaN        NaN  \n",
       "1210                 10    NaN        NaN  \n",
       "1223                 10    NaN        NaN  \n",
       "1309                 10    NaN        NaN  \n",
       "1351                 10    NaN        NaN  \n",
       "1473                 10    NaN        NaN  \n",
       "1477                130    NaN        NaN  \n",
       "1668                 10    NaN        NaN  \n",
       "1677                 10    NaN        NaN  \n",
       "1689                 10    NaN        NaN  \n",
       "1703                 10    NaN        NaN  \n",
       "1706                 10    NaN        NaN  \n",
       "1713                 10    NaN        NaN  \n",
       "1842                 10    NaN        NaN  \n",
       "1965                 10  Tessa        NaN  "
      ]
     },
     "execution_count": 93,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#checking affected rows\n",
    "Twitter_archive_df.query('in_reply_to_status_id.notna()')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 94,
   "id": "33a269c0",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>tweet_id</th>\n",
       "      <th>in_reply_to_status_id</th>\n",
       "      <th>in_reply_to_user_id</th>\n",
       "      <th>timestamp</th>\n",
       "      <th>source</th>\n",
       "      <th>text</th>\n",
       "      <th>retweeted_status_id</th>\n",
       "      <th>retweeted_status_user_id</th>\n",
       "      <th>retweeted_status_timestamp</th>\n",
       "      <th>expanded_urls</th>\n",
       "      <th>rating_numerator</th>\n",
       "      <th>rating_denominator</th>\n",
       "      <th>name</th>\n",
       "      <th>dog_stages</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>504</th>\n",
       "      <td>802265048156610565</td>\n",
       "      <td>733109485275860992.0</td>\n",
       "      <td>4196983835.0</td>\n",
       "      <td>2016-11-25 21:37:47+00:00</td>\n",
       "      <td>Twitter for iPhone</td>\n",
       "      <td>Like doggo, like pupper version 2. Both 11/10 ...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaT</td>\n",
       "      <td>https://twitter.com/dog_rates/status/802265048...</td>\n",
       "      <td>11</td>\n",
       "      <td>10</td>\n",
       "      <td>NaN</td>\n",
       "      <td>doggo</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5547</th>\n",
       "      <td>694356675654983680</td>\n",
       "      <td>670668383499735040.0</td>\n",
       "      <td>4196983835.0</td>\n",
       "      <td>2016-02-02 03:08:26+00:00</td>\n",
       "      <td>Twitter for iPhone</td>\n",
       "      <td>This pupper only appears through the hole of a...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaT</td>\n",
       "      <td>https://twitter.com/dog_rates/status/694356675...</td>\n",
       "      <td>10</td>\n",
       "      <td>10</td>\n",
       "      <td>NaN</td>\n",
       "      <td>pupper</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5429</th>\n",
       "      <td>705786532653883392</td>\n",
       "      <td>703255935813287936.0</td>\n",
       "      <td>4196983835.0</td>\n",
       "      <td>2016-03-04 16:06:36+00:00</td>\n",
       "      <td>Twitter for iPhone</td>\n",
       "      <td>Seriously, add us 🐶 11/10 for sad wet pupper h...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaT</td>\n",
       "      <td>https://twitter.com/dog_rates/status/705786532...</td>\n",
       "      <td>11</td>\n",
       "      <td>10</td>\n",
       "      <td>NaN</td>\n",
       "      <td>pupper</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>NaN</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30</th>\n",
       "      <td>886267009285017600</td>\n",
       "      <td>886266357075128320.0</td>\n",
       "      <td>2281181600.0</td>\n",
       "      <td>2017-07-15 16:51:35+00:00</td>\n",
       "      <td>Twitter for iPhone</td>\n",
       "      <td>@NonWhiteHat @MayhewMayhem omg hello tanner yo...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaT</td>\n",
       "      <td>NaN</td>\n",
       "      <td>12</td>\n",
       "      <td>10</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>137</th>\n",
       "      <td>863079547188785154</td>\n",
       "      <td>667152164079423488.0</td>\n",
       "      <td>4196983835.0</td>\n",
       "      <td>2017-05-12 17:12:53+00:00</td>\n",
       "      <td>Twitter for iPhone</td>\n",
       "      <td>Ladies and gentlemen... I found Pipsy. He may ...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaT</td>\n",
       "      <td>https://twitter.com/dog_rates/status/863079547...</td>\n",
       "      <td>14</td>\n",
       "      <td>10</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>168</th>\n",
       "      <td>856526610513747968</td>\n",
       "      <td>855818117272018944.0</td>\n",
       "      <td>4196983835.0</td>\n",
       "      <td>2017-04-24 15:13:52+00:00</td>\n",
       "      <td>Twitter for iPhone</td>\n",
       "      <td>THIS IS CHARLIE, MARK. HE DID JUST WANT TO SAY...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaT</td>\n",
       "      <td>https://twitter.com/dog_rates/status/856526610...</td>\n",
       "      <td>14</td>\n",
       "      <td>10</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>227</th>\n",
       "      <td>844979544864018432</td>\n",
       "      <td>759099523532779520.0</td>\n",
       "      <td>4196983835.0</td>\n",
       "      <td>2017-03-23 18:29:57+00:00</td>\n",
       "      <td>Twitter for iPhone</td>\n",
       "      <td>PUPDATE: I'm proud to announce that Toby is 23...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaT</td>\n",
       "      <td>https://twitter.com/dog_rates/status/844979544...</td>\n",
       "      <td>13</td>\n",
       "      <td>10</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>910</th>\n",
       "      <td>746906459439529985</td>\n",
       "      <td>746885919387574272.0</td>\n",
       "      <td>4196983835.0</td>\n",
       "      <td>2016-06-26 03:22:31+00:00</td>\n",
       "      <td>Twitter for iPhone</td>\n",
       "      <td>PUPDATE: can't see any. Even if I could, I cou...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaT</td>\n",
       "      <td>https://twitter.com/dog_rates/status/746906459...</td>\n",
       "      <td>0</td>\n",
       "      <td>10</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>911</th>\n",
       "      <td>746818907684614144</td>\n",
       "      <td>691416866452082688.0</td>\n",
       "      <td>4196983835.0</td>\n",
       "      <td>2016-06-25 21:34:37+00:00</td>\n",
       "      <td>Twitter for iPhone</td>\n",
       "      <td>Guys... Dog Jesus 2.0\\n13/10 buoyant af https:...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaT</td>\n",
       "      <td>https://twitter.com/dog_rates/status/746818907...</td>\n",
       "      <td>13</td>\n",
       "      <td>10</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1005</th>\n",
       "      <td>729838605770891264</td>\n",
       "      <td>729113531270991872.0</td>\n",
       "      <td>4196983835.0</td>\n",
       "      <td>2016-05-10 01:00:58+00:00</td>\n",
       "      <td>Twitter for iPhone</td>\n",
       "      <td>\"Challenge completed\" \\n(pupgraded to 12/10) h...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaT</td>\n",
       "      <td>https://twitter.com/dog_rates/status/729838605...</td>\n",
       "      <td>12</td>\n",
       "      <td>10</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1210</th>\n",
       "      <td>704871453724954624</td>\n",
       "      <td>667152164079423488.0</td>\n",
       "      <td>4196983835.0</td>\n",
       "      <td>2016-03-02 03:30:25+00:00</td>\n",
       "      <td>Twitter for iPhone</td>\n",
       "      <td>I found a forest Pipsy. 12/10 https://t.co/mIQ...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaT</td>\n",
       "      <td>https://twitter.com/dog_rates/status/704871453...</td>\n",
       "      <td>12</td>\n",
       "      <td>10</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1223</th>\n",
       "      <td>703425003149250560</td>\n",
       "      <td>703041949650034688.0</td>\n",
       "      <td>4196983835.0</td>\n",
       "      <td>2016-02-27 03:42:44+00:00</td>\n",
       "      <td>Twitter for iPhone</td>\n",
       "      <td>Really guys? Again? I know this is a rare Alba...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaT</td>\n",
       "      <td>https://twitter.com/dog_rates/status/703425003...</td>\n",
       "      <td>9</td>\n",
       "      <td>10</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1309</th>\n",
       "      <td>695767669421768709</td>\n",
       "      <td>675349384339542016.0</td>\n",
       "      <td>4196983835.0</td>\n",
       "      <td>2016-02-06 00:35:13+00:00</td>\n",
       "      <td>Twitter for iPhone</td>\n",
       "      <td>If you are aware of who is making these please...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaT</td>\n",
       "      <td>https://twitter.com/dog_rates/status/695767669...</td>\n",
       "      <td>13</td>\n",
       "      <td>10</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1351</th>\n",
       "      <td>692142790915014657</td>\n",
       "      <td>692041934689402880.0</td>\n",
       "      <td>4196983835.0</td>\n",
       "      <td>2016-01-27 00:31:15+00:00</td>\n",
       "      <td>Twitter for iPhone</td>\n",
       "      <td>These are some pictures of Teddy that further ...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaT</td>\n",
       "      <td>https://twitter.com/dog_rates/status/692142790...</td>\n",
       "      <td>13</td>\n",
       "      <td>10</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1473</th>\n",
       "      <td>684538444857667585</td>\n",
       "      <td>684481074559381504.0</td>\n",
       "      <td>4196983835.0</td>\n",
       "      <td>2016-01-06 00:54:18+00:00</td>\n",
       "      <td>Twitter for iPhone</td>\n",
       "      <td>After watching this video, we've determined th...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaT</td>\n",
       "      <td>https://twitter.com/dog_rates/status/684538444...</td>\n",
       "      <td>12</td>\n",
       "      <td>10</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1477</th>\n",
       "      <td>684225744407494656</td>\n",
       "      <td>684222868335505408.0</td>\n",
       "      <td>4196983835.0</td>\n",
       "      <td>2016-01-05 04:11:44+00:00</td>\n",
       "      <td>Twitter for iPhone</td>\n",
       "      <td>Two sneaky puppers were not initially seen, mo...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaT</td>\n",
       "      <td>https://twitter.com/dog_rates/status/684225744...</td>\n",
       "      <td>143</td>\n",
       "      <td>130</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1668</th>\n",
       "      <td>675870721063669760</td>\n",
       "      <td>675707330206547968.0</td>\n",
       "      <td>4196983835.0</td>\n",
       "      <td>2015-12-13 02:51:51+00:00</td>\n",
       "      <td>Twitter for iPhone</td>\n",
       "      <td>&amp;amp; this is Yoshi. Another world record cont...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaT</td>\n",
       "      <td>https://twitter.com/dog_rates/status/675870721...</td>\n",
       "      <td>11</td>\n",
       "      <td>10</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1677</th>\n",
       "      <td>675707330206547968</td>\n",
       "      <td>675497103322386432.0</td>\n",
       "      <td>4196983835.0</td>\n",
       "      <td>2015-12-12 16:02:36+00:00</td>\n",
       "      <td>Twitter for iPhone</td>\n",
       "      <td>We've got ourselves a battle here. Watch out R...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaT</td>\n",
       "      <td>https://twitter.com/dog_rates/status/675707330...</td>\n",
       "      <td>11</td>\n",
       "      <td>10</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1689</th>\n",
       "      <td>675349384339542016</td>\n",
       "      <td>674999807681908736.0</td>\n",
       "      <td>4196983835.0</td>\n",
       "      <td>2015-12-11 16:20:15+00:00</td>\n",
       "      <td>Twitter for iPhone</td>\n",
       "      <td>Yea I lied. Here's more. All 13/10 https://t.c...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaT</td>\n",
       "      <td>https://twitter.com/dog_rates/status/675349384...</td>\n",
       "      <td>13</td>\n",
       "      <td>10</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1703</th>\n",
       "      <td>674999807681908736</td>\n",
       "      <td>674793399141146624.0</td>\n",
       "      <td>4196983835.0</td>\n",
       "      <td>2015-12-10 17:11:09+00:00</td>\n",
       "      <td>Twitter for iPhone</td>\n",
       "      <td>Ok last one of these. I may try to make some m...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaT</td>\n",
       "      <td>https://twitter.com/dog_rates/status/674999807...</td>\n",
       "      <td>13</td>\n",
       "      <td>10</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1706</th>\n",
       "      <td>674793399141146624</td>\n",
       "      <td>671729906628341760.0</td>\n",
       "      <td>4196983835.0</td>\n",
       "      <td>2015-12-10 03:30:58+00:00</td>\n",
       "      <td>Twitter for iPhone</td>\n",
       "      <td>I have found another. 13/10 https://t.co/HwroP...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaT</td>\n",
       "      <td>https://twitter.com/dog_rates/status/674793399...</td>\n",
       "      <td>13</td>\n",
       "      <td>10</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1713</th>\n",
       "      <td>674754018082705410</td>\n",
       "      <td>674752233200820224.0</td>\n",
       "      <td>4196983835.0</td>\n",
       "      <td>2015-12-10 00:54:28+00:00</td>\n",
       "      <td>Twitter for iPhone</td>\n",
       "      <td>Just received another perfect photo of dogs an...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaT</td>\n",
       "      <td>https://twitter.com/dog_rates/status/674754018...</td>\n",
       "      <td>12</td>\n",
       "      <td>10</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1842</th>\n",
       "      <td>671729906628341761</td>\n",
       "      <td>671561002136281088.0</td>\n",
       "      <td>4196983835.0</td>\n",
       "      <td>2015-12-01 16:37:44+00:00</td>\n",
       "      <td>Twitter for iPhone</td>\n",
       "      <td>I'm just going to leave this one here as well....</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaT</td>\n",
       "      <td>https://twitter.com/dog_rates/status/671729906...</td>\n",
       "      <td>13</td>\n",
       "      <td>10</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1965</th>\n",
       "      <td>669353438988365824</td>\n",
       "      <td>667806454573760512.0</td>\n",
       "      <td>4196983835.0</td>\n",
       "      <td>2015-11-25 03:14:30+00:00</td>\n",
       "      <td>Twitter for iPhone</td>\n",
       "      <td>This is Tessa. She is also very pleased after ...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaT</td>\n",
       "      <td>https://twitter.com/dog_rates/status/669353438...</td>\n",
       "      <td>10</td>\n",
       "      <td>10</td>\n",
       "      <td>Tessa</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                tweet_id in_reply_to_status_id in_reply_to_user_id  \\\n",
       "504   802265048156610565  733109485275860992.0        4196983835.0   \n",
       "5547  694356675654983680  670668383499735040.0        4196983835.0   \n",
       "5429  705786532653883392  703255935813287936.0        4196983835.0   \n",
       "22                  None                  None                None   \n",
       "30    886267009285017600  886266357075128320.0        2281181600.0   \n",
       "137   863079547188785154  667152164079423488.0        4196983835.0   \n",
       "168   856526610513747968  855818117272018944.0        4196983835.0   \n",
       "227   844979544864018432  759099523532779520.0        4196983835.0   \n",
       "910   746906459439529985  746885919387574272.0        4196983835.0   \n",
       "911   746818907684614144  691416866452082688.0        4196983835.0   \n",
       "1005  729838605770891264  729113531270991872.0        4196983835.0   \n",
       "1210  704871453724954624  667152164079423488.0        4196983835.0   \n",
       "1223  703425003149250560  703041949650034688.0        4196983835.0   \n",
       "1309  695767669421768709  675349384339542016.0        4196983835.0   \n",
       "1351  692142790915014657  692041934689402880.0        4196983835.0   \n",
       "1473  684538444857667585  684481074559381504.0        4196983835.0   \n",
       "1477  684225744407494656  684222868335505408.0        4196983835.0   \n",
       "1668  675870721063669760  675707330206547968.0        4196983835.0   \n",
       "1677  675707330206547968  675497103322386432.0        4196983835.0   \n",
       "1689  675349384339542016  674999807681908736.0        4196983835.0   \n",
       "1703  674999807681908736  674793399141146624.0        4196983835.0   \n",
       "1706  674793399141146624  671729906628341760.0        4196983835.0   \n",
       "1713  674754018082705410  674752233200820224.0        4196983835.0   \n",
       "1842  671729906628341761  671561002136281088.0        4196983835.0   \n",
       "1965  669353438988365824  667806454573760512.0        4196983835.0   \n",
       "\n",
       "                      timestamp              source  \\\n",
       "504   2016-11-25 21:37:47+00:00  Twitter for iPhone   \n",
       "5547  2016-02-02 03:08:26+00:00  Twitter for iPhone   \n",
       "5429  2016-03-04 16:06:36+00:00  Twitter for iPhone   \n",
       "22                         None                 NaN   \n",
       "30    2017-07-15 16:51:35+00:00  Twitter for iPhone   \n",
       "137   2017-05-12 17:12:53+00:00  Twitter for iPhone   \n",
       "168   2017-04-24 15:13:52+00:00  Twitter for iPhone   \n",
       "227   2017-03-23 18:29:57+00:00  Twitter for iPhone   \n",
       "910   2016-06-26 03:22:31+00:00  Twitter for iPhone   \n",
       "911   2016-06-25 21:34:37+00:00  Twitter for iPhone   \n",
       "1005  2016-05-10 01:00:58+00:00  Twitter for iPhone   \n",
       "1210  2016-03-02 03:30:25+00:00  Twitter for iPhone   \n",
       "1223  2016-02-27 03:42:44+00:00  Twitter for iPhone   \n",
       "1309  2016-02-06 00:35:13+00:00  Twitter for iPhone   \n",
       "1351  2016-01-27 00:31:15+00:00  Twitter for iPhone   \n",
       "1473  2016-01-06 00:54:18+00:00  Twitter for iPhone   \n",
       "1477  2016-01-05 04:11:44+00:00  Twitter for iPhone   \n",
       "1668  2015-12-13 02:51:51+00:00  Twitter for iPhone   \n",
       "1677  2015-12-12 16:02:36+00:00  Twitter for iPhone   \n",
       "1689  2015-12-11 16:20:15+00:00  Twitter for iPhone   \n",
       "1703  2015-12-10 17:11:09+00:00  Twitter for iPhone   \n",
       "1706  2015-12-10 03:30:58+00:00  Twitter for iPhone   \n",
       "1713  2015-12-10 00:54:28+00:00  Twitter for iPhone   \n",
       "1842  2015-12-01 16:37:44+00:00  Twitter for iPhone   \n",
       "1965  2015-11-25 03:14:30+00:00  Twitter for iPhone   \n",
       "\n",
       "                                                   text retweeted_status_id  \\\n",
       "504   Like doggo, like pupper version 2. Both 11/10 ...                 NaN   \n",
       "5547  This pupper only appears through the hole of a...                 NaN   \n",
       "5429  Seriously, add us 🐶 11/10 for sad wet pupper h...                 NaN   \n",
       "22                                                 None                None   \n",
       "30    @NonWhiteHat @MayhewMayhem omg hello tanner yo...                 NaN   \n",
       "137   Ladies and gentlemen... I found Pipsy. He may ...                 NaN   \n",
       "168   THIS IS CHARLIE, MARK. HE DID JUST WANT TO SAY...                 NaN   \n",
       "227   PUPDATE: I'm proud to announce that Toby is 23...                 NaN   \n",
       "910   PUPDATE: can't see any. Even if I could, I cou...                 NaN   \n",
       "911   Guys... Dog Jesus 2.0\\n13/10 buoyant af https:...                 NaN   \n",
       "1005  \"Challenge completed\" \\n(pupgraded to 12/10) h...                 NaN   \n",
       "1210  I found a forest Pipsy. 12/10 https://t.co/mIQ...                 NaN   \n",
       "1223  Really guys? Again? I know this is a rare Alba...                 NaN   \n",
       "1309  If you are aware of who is making these please...                 NaN   \n",
       "1351  These are some pictures of Teddy that further ...                 NaN   \n",
       "1473  After watching this video, we've determined th...                 NaN   \n",
       "1477  Two sneaky puppers were not initially seen, mo...                 NaN   \n",
       "1668  &amp; this is Yoshi. Another world record cont...                 NaN   \n",
       "1677  We've got ourselves a battle here. Watch out R...                 NaN   \n",
       "1689  Yea I lied. Here's more. All 13/10 https://t.c...                 NaN   \n",
       "1703  Ok last one of these. I may try to make some m...                 NaN   \n",
       "1706  I have found another. 13/10 https://t.co/HwroP...                 NaN   \n",
       "1713  Just received another perfect photo of dogs an...                 NaN   \n",
       "1842  I'm just going to leave this one here as well....                 NaN   \n",
       "1965  This is Tessa. She is also very pleased after ...                 NaN   \n",
       "\n",
       "     retweeted_status_user_id retweeted_status_timestamp  \\\n",
       "504                       NaN                        NaT   \n",
       "5547                      NaN                        NaT   \n",
       "5429                      NaN                        NaT   \n",
       "22                       None                       None   \n",
       "30                        NaN                        NaT   \n",
       "137                       NaN                        NaT   \n",
       "168                       NaN                        NaT   \n",
       "227                       NaN                        NaT   \n",
       "910                       NaN                        NaT   \n",
       "911                       NaN                        NaT   \n",
       "1005                      NaN                        NaT   \n",
       "1210                      NaN                        NaT   \n",
       "1223                      NaN                        NaT   \n",
       "1309                      NaN                        NaT   \n",
       "1351                      NaN                        NaT   \n",
       "1473                      NaN                        NaT   \n",
       "1477                      NaN                        NaT   \n",
       "1668                      NaN                        NaT   \n",
       "1677                      NaN                        NaT   \n",
       "1689                      NaN                        NaT   \n",
       "1703                      NaN                        NaT   \n",
       "1706                      NaN                        NaT   \n",
       "1713                      NaN                        NaT   \n",
       "1842                      NaN                        NaT   \n",
       "1965                      NaN                        NaT   \n",
       "\n",
       "                                          expanded_urls rating_numerator  \\\n",
       "504   https://twitter.com/dog_rates/status/802265048...               11   \n",
       "5547  https://twitter.com/dog_rates/status/694356675...               10   \n",
       "5429  https://twitter.com/dog_rates/status/705786532...               11   \n",
       "22                                                 None             None   \n",
       "30                                                  NaN               12   \n",
       "137   https://twitter.com/dog_rates/status/863079547...               14   \n",
       "168   https://twitter.com/dog_rates/status/856526610...               14   \n",
       "227   https://twitter.com/dog_rates/status/844979544...               13   \n",
       "910   https://twitter.com/dog_rates/status/746906459...                0   \n",
       "911   https://twitter.com/dog_rates/status/746818907...               13   \n",
       "1005  https://twitter.com/dog_rates/status/729838605...               12   \n",
       "1210  https://twitter.com/dog_rates/status/704871453...               12   \n",
       "1223  https://twitter.com/dog_rates/status/703425003...                9   \n",
       "1309  https://twitter.com/dog_rates/status/695767669...               13   \n",
       "1351  https://twitter.com/dog_rates/status/692142790...               13   \n",
       "1473  https://twitter.com/dog_rates/status/684538444...               12   \n",
       "1477  https://twitter.com/dog_rates/status/684225744...              143   \n",
       "1668  https://twitter.com/dog_rates/status/675870721...               11   \n",
       "1677  https://twitter.com/dog_rates/status/675707330...               11   \n",
       "1689  https://twitter.com/dog_rates/status/675349384...               13   \n",
       "1703  https://twitter.com/dog_rates/status/674999807...               13   \n",
       "1706  https://twitter.com/dog_rates/status/674793399...               13   \n",
       "1713  https://twitter.com/dog_rates/status/674754018...               12   \n",
       "1842  https://twitter.com/dog_rates/status/671729906...               13   \n",
       "1965  https://twitter.com/dog_rates/status/669353438...               10   \n",
       "\n",
       "     rating_denominator   name dog_stages  \n",
       "504                  10    NaN      doggo  \n",
       "5547                 10    NaN     pupper  \n",
       "5429                 10    NaN     pupper  \n",
       "22                 None    NaN        NaN  \n",
       "30                   10    NaN        NaN  \n",
       "137                  10    NaN        NaN  \n",
       "168                  10    NaN        NaN  \n",
       "227                  10    NaN        NaN  \n",
       "910                  10    NaN        NaN  \n",
       "911                  10    NaN        NaN  \n",
       "1005                 10    NaN        NaN  \n",
       "1210                 10    NaN        NaN  \n",
       "1223                 10    NaN        NaN  \n",
       "1309                 10    NaN        NaN  \n",
       "1351                 10    NaN        NaN  \n",
       "1473                 10    NaN        NaN  \n",
       "1477                130    NaN        NaN  \n",
       "1668                 10    NaN        NaN  \n",
       "1677                 10    NaN        NaN  \n",
       "1689                 10    NaN        NaN  \n",
       "1703                 10    NaN        NaN  \n",
       "1706                 10    NaN        NaN  \n",
       "1713                 10    NaN        NaN  \n",
       "1842                 10    NaN        NaN  \n",
       "1965                 10  Tessa        NaN  "
      ]
     },
     "execution_count": 94,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# checking affected rows\n",
    "Twitter_archive_df.query('in_reply_to_user_id.notna()')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d3fda61f",
   "metadata": {},
   "source": [
    "same tweet_id were affected for in_reply_to_status_id and in_reply_to_user_id value, so dropping the rows and the columns itself"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 95,
   "id": "c407d3b7",
   "metadata": {},
   "outputs": [],
   "source": [
    "Twitter_archive_df = Twitter_archive_df[Twitter_archive_df.in_reply_to_status_id.isnull()]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 96,
   "id": "2ff611ba",
   "metadata": {},
   "outputs": [],
   "source": [
    "# dropping the columns\n",
    "Twitter_archive_df.drop(['in_reply_to_status_id', 'in_reply_to_user_id'], axis=1, inplace=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f6503235",
   "metadata": {},
   "source": [
    "Test"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 98,
   "id": "91bea021",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Int64Index: 2089 entries, 9 to 2113\n",
      "Data columns (total 12 columns):\n",
      " #   Column                      Non-Null Count  Dtype   \n",
      "---  ------                      --------------  -----   \n",
      " 0   tweet_id                    2089 non-null   object  \n",
      " 1   timestamp                   2089 non-null   object  \n",
      " 2   source                      2089 non-null   category\n",
      " 3   text                        2089 non-null   object  \n",
      " 4   retweeted_status_id         175 non-null    object  \n",
      " 5   retweeted_status_user_id    175 non-null    object  \n",
      " 6   retweeted_status_timestamp  175 non-null    object  \n",
      " 7   expanded_urls               2089 non-null   object  \n",
      " 8   rating_numerator            2089 non-null   object  \n",
      " 9   rating_denominator          2089 non-null   object  \n",
      " 10  name                        1443 non-null   object  \n",
      " 11  dog_stages                  337 non-null    object  \n",
      "dtypes: category(1), object(11)\n",
      "memory usage: 198.1+ KB\n"
     ]
    }
   ],
   "source": [
    "Twitter_archive_df.info()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "aa5a084d",
   "metadata": {},
   "source": [
    "**Tidiness issue 4 --Only the original tweet is needed, drop all retweet columnsi.e retweeted_status_id, retweeted_status_user_id, retweeted_status_timestamp**"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f8262176",
   "metadata": {},
   "source": [
    "**Define:**\n",
    "Delete rows with retweeted_status_id, retweeted_status_user_id, and retweeted_status_timestamp by filtering the dataframe using .isnull(). Since same tweet_ids are affected, filtering using any of the column will cater for all\n",
    "\n",
    "code"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 99,
   "id": "6bf567ef",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Filtering the dataframe\n",
    "\n",
    "Twitter_archive_df = Twitter_archive_df[Twitter_archive_df.retweeted_status_id.isnull()]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 100,
   "id": "4834c218",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\USER\\AppData\\Local\\Temp\\ipykernel_15200\\1673881077.py:2: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  Twitter_archive_df.drop(['retweeted_status_id', 'retweeted_status_user_id', 'retweeted_status_timestamp'], axis=1, inplace=True)\n"
     ]
    }
   ],
   "source": [
    "# dropping the columns\n",
    "Twitter_archive_df.drop(['retweeted_status_id', 'retweeted_status_user_id', 'retweeted_status_timestamp'], axis=1, inplace=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "78baf096",
   "metadata": {},
   "source": [
    "Test"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 102,
   "id": "721ffe8b",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Int64Index: 1914 entries, 9 to 2113\n",
      "Data columns (total 9 columns):\n",
      " #   Column              Non-Null Count  Dtype   \n",
      "---  ------              --------------  -----   \n",
      " 0   tweet_id            1914 non-null   object  \n",
      " 1   timestamp           1914 non-null   object  \n",
      " 2   source              1914 non-null   category\n",
      " 3   text                1914 non-null   object  \n",
      " 4   expanded_urls       1914 non-null   object  \n",
      " 5   rating_numerator    1914 non-null   object  \n",
      " 6   rating_denominator  1914 non-null   object  \n",
      " 7   name                1332 non-null   object  \n",
      " 8   dog_stages          303 non-null    object  \n",
      "dtypes: category(1), object(8)\n",
      "memory usage: 136.6+ KB\n"
     ]
    }
   ],
   "source": [
    "Twitter_archive_df.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 103,
   "id": "b7b29f0c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['tweet_id', 'timestamp', 'source', 'text', 'expanded_urls',\n",
       "       'rating_numerator', 'rating_denominator', 'name', 'dog_stages'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 103,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Twitter_archive_df.columns"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "99ff55bf",
   "metadata": {},
   "source": [
    "**Tidiness issue 5 --create_date exist in Twitter_archive as timestamp. therefore, create date should be drop**"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "cf82714e",
   "metadata": {},
   "source": [
    "**Define:**\n",
    "Dropping of create_date in Tweet_data using .drop()\n",
    "\n",
    "code"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 105,
   "id": "781eba15",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['tweet_id', 'retweet_count', 'favorite_count', 'create_date'], dtype='object')"
      ]
     },
     "execution_count": 105,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Tweet_data_df.columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 106,
   "id": "1f1da5e2",
   "metadata": {},
   "outputs": [],
   "source": [
    "Tweet_data_df.drop('create_date', axis=1, inplace=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "979f3292",
   "metadata": {},
   "source": [
    "Test"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 107,
   "id": "53df425c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['tweet_id', 'retweet_count', 'favorite_count'], dtype='object')"
      ]
     },
     "execution_count": 107,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Tweet_data_df.columns"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "922859a8",
   "metadata": {},
   "source": [
    "**Tidiness issue 6 --Ensure that all rows contain at least one true prediction**"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "694a14aa",
   "metadata": {},
   "source": [
    "**Define:**\n",
    "Using .query() method to filter rows with all false-prediction\n",
    "\n",
    "code"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 108,
   "id": "aa6aaa89",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>tweet_id</th>\n",
       "      <th>jpg_url</th>\n",
       "      <th>img_num</th>\n",
       "      <th>p1</th>\n",
       "      <th>p1_conf</th>\n",
       "      <th>p1_dog</th>\n",
       "      <th>p2</th>\n",
       "      <th>p2_conf</th>\n",
       "      <th>p2_dog</th>\n",
       "      <th>p3</th>\n",
       "      <th>p3_conf</th>\n",
       "      <th>p3_dog</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>666020888022790149</td>\n",
       "      <td>https://pbs.twimg.com/media/CT4udn0WwAA0aMy.jpg</td>\n",
       "      <td>1</td>\n",
       "      <td>Welsh_springer_spaniel</td>\n",
       "      <td>0.465074</td>\n",
       "      <td>True</td>\n",
       "      <td>collie</td>\n",
       "      <td>0.156665</td>\n",
       "      <td>True</td>\n",
       "      <td>Shetland_sheepdog</td>\n",
       "      <td>0.061428</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>666029285002620928</td>\n",
       "      <td>https://pbs.twimg.com/media/CT42GRgUYAA5iDo.jpg</td>\n",
       "      <td>1</td>\n",
       "      <td>redbone</td>\n",
       "      <td>0.506826</td>\n",
       "      <td>True</td>\n",
       "      <td>miniature_pinscher</td>\n",
       "      <td>0.074192</td>\n",
       "      <td>True</td>\n",
       "      <td>Rhodesian_ridgeback</td>\n",
       "      <td>0.072010</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>666033412701032449</td>\n",
       "      <td>https://pbs.twimg.com/media/CT4521TWwAEvMyu.jpg</td>\n",
       "      <td>1</td>\n",
       "      <td>German_shepherd</td>\n",
       "      <td>0.596461</td>\n",
       "      <td>True</td>\n",
       "      <td>malinois</td>\n",
       "      <td>0.138584</td>\n",
       "      <td>True</td>\n",
       "      <td>bloodhound</td>\n",
       "      <td>0.116197</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "             tweet_id                                          jpg_url  \\\n",
       "0  666020888022790149  https://pbs.twimg.com/media/CT4udn0WwAA0aMy.jpg   \n",
       "1  666029285002620928  https://pbs.twimg.com/media/CT42GRgUYAA5iDo.jpg   \n",
       "2  666033412701032449  https://pbs.twimg.com/media/CT4521TWwAEvMyu.jpg   \n",
       "\n",
       "   img_num                      p1   p1_conf  p1_dog                  p2  \\\n",
       "0        1  Welsh_springer_spaniel  0.465074    True              collie   \n",
       "1        1                 redbone  0.506826    True  miniature_pinscher   \n",
       "2        1         German_shepherd  0.596461    True            malinois   \n",
       "\n",
       "    p2_conf  p2_dog                   p3   p3_conf  p3_dog  \n",
       "0  0.156665    True    Shetland_sheepdog  0.061428    True  \n",
       "1  0.074192    True  Rhodesian_ridgeback  0.072010    True  \n",
       "2  0.138584    True           bloodhound  0.116197    True  "
      ]
     },
     "execution_count": 108,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dog_pred_df.head(3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 109,
   "id": "4240ede7",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "True     1532\n",
       "False     543\n",
       "Name: p1_dog, dtype: int64"
      ]
     },
     "execution_count": 109,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#dog_pred['p1'].unique()\n",
    "dog_pred_df['p1_dog'].value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 110,
   "id": "1f1c6f98",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "True     1553\n",
       "False     522\n",
       "Name: p2_dog, dtype: int64"
      ]
     },
     "execution_count": 110,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dog_pred_df['p2_dog'].value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 111,
   "id": "1dc6c51a",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "True     1499\n",
       "False     576\n",
       "Name: p3_dog, dtype: int64"
      ]
     },
     "execution_count": 111,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dog_pred_df['p3_dog'].value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 112,
   "id": "eb309a1d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
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       "    .dataframe tbody tr th {\n",
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>tweet_id</th>\n",
       "      <th>jpg_url</th>\n",
       "      <th>img_num</th>\n",
       "      <th>p1</th>\n",
       "      <th>p1_conf</th>\n",
       "      <th>p1_dog</th>\n",
       "      <th>p2</th>\n",
       "      <th>p2_conf</th>\n",
       "      <th>p2_dog</th>\n",
       "      <th>p3</th>\n",
       "      <th>p3_conf</th>\n",
       "      <th>p3_dog</th>\n",
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       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>666020888022790149</td>\n",
       "      <td>https://pbs.twimg.com/media/CT4udn0WwAA0aMy.jpg</td>\n",
       "      <td>1</td>\n",
       "      <td>Welsh_springer_spaniel</td>\n",
       "      <td>0.465074</td>\n",
       "      <td>True</td>\n",
       "      <td>collie</td>\n",
       "      <td>0.156665</td>\n",
       "      <td>True</td>\n",
       "      <td>Shetland_sheepdog</td>\n",
       "      <td>0.061428</td>\n",
       "      <td>True</td>\n",
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       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>666029285002620928</td>\n",
       "      <td>https://pbs.twimg.com/media/CT42GRgUYAA5iDo.jpg</td>\n",
       "      <td>1</td>\n",
       "      <td>redbone</td>\n",
       "      <td>0.506826</td>\n",
       "      <td>True</td>\n",
       "      <td>miniature_pinscher</td>\n",
       "      <td>0.074192</td>\n",
       "      <td>True</td>\n",
       "      <td>Rhodesian_ridgeback</td>\n",
       "      <td>0.072010</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>666033412701032449</td>\n",
       "      <td>https://pbs.twimg.com/media/CT4521TWwAEvMyu.jpg</td>\n",
       "      <td>1</td>\n",
       "      <td>German_shepherd</td>\n",
       "      <td>0.596461</td>\n",
       "      <td>True</td>\n",
       "      <td>malinois</td>\n",
       "      <td>0.138584</td>\n",
       "      <td>True</td>\n",
       "      <td>bloodhound</td>\n",
       "      <td>0.116197</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>666044226329800704</td>\n",
       "      <td>https://pbs.twimg.com/media/CT5Dr8HUEAA-lEu.jpg</td>\n",
       "      <td>1</td>\n",
       "      <td>Rhodesian_ridgeback</td>\n",
       "      <td>0.408143</td>\n",
       "      <td>True</td>\n",
       "      <td>redbone</td>\n",
       "      <td>0.360687</td>\n",
       "      <td>True</td>\n",
       "      <td>miniature_pinscher</td>\n",
       "      <td>0.222752</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>666049248165822465</td>\n",
       "      <td>https://pbs.twimg.com/media/CT5IQmsXIAAKY4A.jpg</td>\n",
       "      <td>1</td>\n",
       "      <td>miniature_pinscher</td>\n",
       "      <td>0.560311</td>\n",
       "      <td>True</td>\n",
       "      <td>Rottweiler</td>\n",
       "      <td>0.243682</td>\n",
       "      <td>True</td>\n",
       "      <td>Doberman</td>\n",
       "      <td>0.154629</td>\n",
       "      <td>True</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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2069</th>\n",
       "      <td>891087950875897856</td>\n",
       "      <td>https://pbs.twimg.com/media/DF3HwyEWsAABqE6.jpg</td>\n",
       "      <td>1</td>\n",
       "      <td>Chesapeake_Bay_retriever</td>\n",
       "      <td>0.425595</td>\n",
       "      <td>True</td>\n",
       "      <td>Irish_terrier</td>\n",
       "      <td>0.116317</td>\n",
       "      <td>True</td>\n",
       "      <td>Indian_elephant</td>\n",
       "      <td>0.076902</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2070</th>\n",
       "      <td>891327558926688256</td>\n",
       "      <td>https://pbs.twimg.com/media/DF6hr6BUMAAzZgT.jpg</td>\n",
       "      <td>2</td>\n",
       "      <td>basset</td>\n",
       "      <td>0.555712</td>\n",
       "      <td>True</td>\n",
       "      <td>English_springer</td>\n",
       "      <td>0.225770</td>\n",
       "      <td>True</td>\n",
       "      <td>German_short-haired_pointer</td>\n",
       "      <td>0.175219</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2071</th>\n",
       "      <td>891689557279858688</td>\n",
       "      <td>https://pbs.twimg.com/media/DF_q7IAWsAEuuN8.jpg</td>\n",
       "      <td>1</td>\n",
       "      <td>paper_towel</td>\n",
       "      <td>0.170278</td>\n",
       "      <td>False</td>\n",
       "      <td>Labrador_retriever</td>\n",
       "      <td>0.168086</td>\n",
       "      <td>True</td>\n",
       "      <td>spatula</td>\n",
       "      <td>0.040836</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2072</th>\n",
       "      <td>891815181378084864</td>\n",
       "      <td>https://pbs.twimg.com/media/DGBdLU1WsAANxJ9.jpg</td>\n",
       "      <td>1</td>\n",
       "      <td>Chihuahua</td>\n",
       "      <td>0.716012</td>\n",
       "      <td>True</td>\n",
       "      <td>malamute</td>\n",
       "      <td>0.078253</td>\n",
       "      <td>True</td>\n",
       "      <td>kelpie</td>\n",
       "      <td>0.031379</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2073</th>\n",
       "      <td>892177421306343426</td>\n",
       "      <td>https://pbs.twimg.com/media/DGGmoV4XsAAUL6n.jpg</td>\n",
       "      <td>1</td>\n",
       "      <td>Chihuahua</td>\n",
       "      <td>0.323581</td>\n",
       "      <td>True</td>\n",
       "      <td>Pekinese</td>\n",
       "      <td>0.090647</td>\n",
       "      <td>True</td>\n",
       "      <td>papillon</td>\n",
       "      <td>0.068957</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>1751 rows × 12 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                tweet_id                                          jpg_url  \\\n",
       "0     666020888022790149  https://pbs.twimg.com/media/CT4udn0WwAA0aMy.jpg   \n",
       "1     666029285002620928  https://pbs.twimg.com/media/CT42GRgUYAA5iDo.jpg   \n",
       "2     666033412701032449  https://pbs.twimg.com/media/CT4521TWwAEvMyu.jpg   \n",
       "3     666044226329800704  https://pbs.twimg.com/media/CT5Dr8HUEAA-lEu.jpg   \n",
       "4     666049248165822465  https://pbs.twimg.com/media/CT5IQmsXIAAKY4A.jpg   \n",
       "...                  ...                                              ...   \n",
       "2069  891087950875897856  https://pbs.twimg.com/media/DF3HwyEWsAABqE6.jpg   \n",
       "2070  891327558926688256  https://pbs.twimg.com/media/DF6hr6BUMAAzZgT.jpg   \n",
       "2071  891689557279858688  https://pbs.twimg.com/media/DF_q7IAWsAEuuN8.jpg   \n",
       "2072  891815181378084864  https://pbs.twimg.com/media/DGBdLU1WsAANxJ9.jpg   \n",
       "2073  892177421306343426  https://pbs.twimg.com/media/DGGmoV4XsAAUL6n.jpg   \n",
       "\n",
       "      img_num                        p1   p1_conf  p1_dog                  p2  \\\n",
       "0           1    Welsh_springer_spaniel  0.465074    True              collie   \n",
       "1           1                   redbone  0.506826    True  miniature_pinscher   \n",
       "2           1           German_shepherd  0.596461    True            malinois   \n",
       "3           1       Rhodesian_ridgeback  0.408143    True             redbone   \n",
       "4           1        miniature_pinscher  0.560311    True          Rottweiler   \n",
       "...       ...                       ...       ...     ...                 ...   \n",
       "2069        1  Chesapeake_Bay_retriever  0.425595    True       Irish_terrier   \n",
       "2070        2                    basset  0.555712    True    English_springer   \n",
       "2071        1               paper_towel  0.170278   False  Labrador_retriever   \n",
       "2072        1                 Chihuahua  0.716012    True            malamute   \n",
       "2073        1                 Chihuahua  0.323581    True            Pekinese   \n",
       "\n",
       "       p2_conf  p2_dog                           p3   p3_conf  p3_dog  \n",
       "0     0.156665    True            Shetland_sheepdog  0.061428    True  \n",
       "1     0.074192    True          Rhodesian_ridgeback  0.072010    True  \n",
       "2     0.138584    True                   bloodhound  0.116197    True  \n",
       "3     0.360687    True           miniature_pinscher  0.222752    True  \n",
       "4     0.243682    True                     Doberman  0.154629    True  \n",
       "...        ...     ...                          ...       ...     ...  \n",
       "2069  0.116317    True              Indian_elephant  0.076902   False  \n",
       "2070  0.225770    True  German_short-haired_pointer  0.175219    True  \n",
       "2071  0.168086    True                      spatula  0.040836   False  \n",
       "2072  0.078253    True                       kelpie  0.031379    True  \n",
       "2073  0.090647    True                     papillon  0.068957    True  \n",
       "\n",
       "[1751 rows x 12 columns]"
      ]
     },
     "execution_count": 112,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# checking rows with at least one true prediction\n",
    "dog_pred_df.query('(p1_dog == True) or (p2_dog == True) or (p3_dog == True)')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 113,
   "id": "14859817",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>tweet_id</th>\n",
       "      <th>jpg_url</th>\n",
       "      <th>img_num</th>\n",
       "      <th>p1</th>\n",
       "      <th>p1_conf</th>\n",
       "      <th>p1_dog</th>\n",
       "      <th>p2</th>\n",
       "      <th>p2_conf</th>\n",
       "      <th>p2_dog</th>\n",
       "      <th>p3</th>\n",
       "      <th>p3_conf</th>\n",
       "      <th>p3_dog</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>666051853826850816</td>\n",
       "      <td>https://pbs.twimg.com/media/CT5KoJ1WoAAJash.jpg</td>\n",
       "      <td>1</td>\n",
       "      <td>box_turtle</td>\n",
       "      <td>0.933012</td>\n",
       "      <td>False</td>\n",
       "      <td>mud_turtle</td>\n",
       "      <td>0.045885</td>\n",
       "      <td>False</td>\n",
       "      <td>terrapin</td>\n",
       "      <td>0.017885</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>666104133288665088</td>\n",
       "      <td>https://pbs.twimg.com/media/CT56LSZWoAAlJj2.jpg</td>\n",
       "      <td>1</td>\n",
       "      <td>hen</td>\n",
       "      <td>0.965932</td>\n",
       "      <td>False</td>\n",
       "      <td>cock</td>\n",
       "      <td>0.033919</td>\n",
       "      <td>False</td>\n",
       "      <td>partridge</td>\n",
       "      <td>0.000052</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>666268910803644416</td>\n",
       "      <td>https://pbs.twimg.com/media/CT8QCd1WEAADXws.jpg</td>\n",
       "      <td>1</td>\n",
       "      <td>desktop_computer</td>\n",
       "      <td>0.086502</td>\n",
       "      <td>False</td>\n",
       "      <td>desk</td>\n",
       "      <td>0.085547</td>\n",
       "      <td>False</td>\n",
       "      <td>bookcase</td>\n",
       "      <td>0.079480</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>666293911632134144</td>\n",
       "      <td>https://pbs.twimg.com/media/CT8mx7KW4AEQu8N.jpg</td>\n",
       "      <td>1</td>\n",
       "      <td>three-toed_sloth</td>\n",
       "      <td>0.914671</td>\n",
       "      <td>False</td>\n",
       "      <td>otter</td>\n",
       "      <td>0.015250</td>\n",
       "      <td>False</td>\n",
       "      <td>great_grey_owl</td>\n",
       "      <td>0.013207</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>666362758909284353</td>\n",
       "      <td>https://pbs.twimg.com/media/CT9lXGsUcAAyUFt.jpg</td>\n",
       "      <td>1</td>\n",
       "      <td>guinea_pig</td>\n",
       "      <td>0.996496</td>\n",
       "      <td>False</td>\n",
       "      <td>skunk</td>\n",
       "      <td>0.002402</td>\n",
       "      <td>False</td>\n",
       "      <td>hamster</td>\n",
       "      <td>0.000461</td>\n",
       "      <td>False</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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021</th>\n",
       "      <td>880935762899988482</td>\n",
       "      <td>https://pbs.twimg.com/media/DDm2Z5aXUAEDS2u.jpg</td>\n",
       "      <td>1</td>\n",
       "      <td>street_sign</td>\n",
       "      <td>0.251801</td>\n",
       "      <td>False</td>\n",
       "      <td>umbrella</td>\n",
       "      <td>0.115123</td>\n",
       "      <td>False</td>\n",
       "      <td>traffic_light</td>\n",
       "      <td>0.069534</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022</th>\n",
       "      <td>881268444196462592</td>\n",
       "      <td>https://pbs.twimg.com/media/DDrk-f9WAAI-WQv.jpg</td>\n",
       "      <td>1</td>\n",
       "      <td>tusker</td>\n",
       "      <td>0.473303</td>\n",
       "      <td>False</td>\n",
       "      <td>Indian_elephant</td>\n",
       "      <td>0.245646</td>\n",
       "      <td>False</td>\n",
       "      <td>ibex</td>\n",
       "      <td>0.055661</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2046</th>\n",
       "      <td>886680336477933568</td>\n",
       "      <td>https://pbs.twimg.com/media/DE4fEDzWAAAyHMM.jpg</td>\n",
       "      <td>1</td>\n",
       "      <td>convertible</td>\n",
       "      <td>0.738995</td>\n",
       "      <td>False</td>\n",
       "      <td>sports_car</td>\n",
       "      <td>0.139952</td>\n",
       "      <td>False</td>\n",
       "      <td>car_wheel</td>\n",
       "      <td>0.044173</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2052</th>\n",
       "      <td>887517139158093824</td>\n",
       "      <td>https://pbs.twimg.com/ext_tw_video_thumb/88751...</td>\n",
       "      <td>1</td>\n",
       "      <td>limousine</td>\n",
       "      <td>0.130432</td>\n",
       "      <td>False</td>\n",
       "      <td>tow_truck</td>\n",
       "      <td>0.029175</td>\n",
       "      <td>False</td>\n",
       "      <td>shopping_cart</td>\n",
       "      <td>0.026321</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2074</th>\n",
       "      <td>892420643555336193</td>\n",
       "      <td>https://pbs.twimg.com/media/DGKD1-bXoAAIAUK.jpg</td>\n",
       "      <td>1</td>\n",
       "      <td>orange</td>\n",
       "      <td>0.097049</td>\n",
       "      <td>False</td>\n",
       "      <td>bagel</td>\n",
       "      <td>0.085851</td>\n",
       "      <td>False</td>\n",
       "      <td>banana</td>\n",
       "      <td>0.076110</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>324 rows × 12 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                tweet_id                                            jpg_url  \\\n",
       "6     666051853826850816    https://pbs.twimg.com/media/CT5KoJ1WoAAJash.jpg   \n",
       "17    666104133288665088    https://pbs.twimg.com/media/CT56LSZWoAAlJj2.jpg   \n",
       "18    666268910803644416    https://pbs.twimg.com/media/CT8QCd1WEAADXws.jpg   \n",
       "21    666293911632134144    https://pbs.twimg.com/media/CT8mx7KW4AEQu8N.jpg   \n",
       "25    666362758909284353    https://pbs.twimg.com/media/CT9lXGsUcAAyUFt.jpg   \n",
       "...                  ...                                                ...   \n",
       "2021  880935762899988482    https://pbs.twimg.com/media/DDm2Z5aXUAEDS2u.jpg   \n",
       "2022  881268444196462592    https://pbs.twimg.com/media/DDrk-f9WAAI-WQv.jpg   \n",
       "2046  886680336477933568    https://pbs.twimg.com/media/DE4fEDzWAAAyHMM.jpg   \n",
       "2052  887517139158093824  https://pbs.twimg.com/ext_tw_video_thumb/88751...   \n",
       "2074  892420643555336193    https://pbs.twimg.com/media/DGKD1-bXoAAIAUK.jpg   \n",
       "\n",
       "      img_num                p1   p1_conf  p1_dog               p2   p2_conf  \\\n",
       "6           1        box_turtle  0.933012   False       mud_turtle  0.045885   \n",
       "17          1               hen  0.965932   False             cock  0.033919   \n",
       "18          1  desktop_computer  0.086502   False             desk  0.085547   \n",
       "21          1  three-toed_sloth  0.914671   False            otter  0.015250   \n",
       "25          1        guinea_pig  0.996496   False            skunk  0.002402   \n",
       "...       ...               ...       ...     ...              ...       ...   \n",
       "2021        1       street_sign  0.251801   False         umbrella  0.115123   \n",
       "2022        1            tusker  0.473303   False  Indian_elephant  0.245646   \n",
       "2046        1       convertible  0.738995   False       sports_car  0.139952   \n",
       "2052        1         limousine  0.130432   False        tow_truck  0.029175   \n",
       "2074        1            orange  0.097049   False            bagel  0.085851   \n",
       "\n",
       "      p2_dog              p3   p3_conf  p3_dog  \n",
       "6      False        terrapin  0.017885   False  \n",
       "17     False       partridge  0.000052   False  \n",
       "18     False        bookcase  0.079480   False  \n",
       "21     False  great_grey_owl  0.013207   False  \n",
       "25     False         hamster  0.000461   False  \n",
       "...      ...             ...       ...     ...  \n",
       "2021   False   traffic_light  0.069534   False  \n",
       "2022   False            ibex  0.055661   False  \n",
       "2046   False       car_wheel  0.044173   False  \n",
       "2052   False   shopping_cart  0.026321   False  \n",
       "2074   False          banana  0.076110   False  \n",
       "\n",
       "[324 rows x 12 columns]"
      ]
     },
     "execution_count": 113,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dog_pred_df.query('(p1_dog == False) & (p2_dog == False) & (p3_dog == False)')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 114,
   "id": "641e994f",
   "metadata": {},
   "outputs": [],
   "source": [
    "# filtering rows with at least one dog prediction\n",
    "dog_pred_df = dog_pred_df.query('(p1_dog == True) or (p2_dog == True) or (p3_dog == True)')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "798b0400",
   "metadata": {},
   "source": [
    "Test"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 115,
   "id": "57a5ec16",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>tweet_id</th>\n",
       "      <th>jpg_url</th>\n",
       "      <th>img_num</th>\n",
       "      <th>p1</th>\n",
       "      <th>p1_conf</th>\n",
       "      <th>p1_dog</th>\n",
       "      <th>p2</th>\n",
       "      <th>p2_conf</th>\n",
       "      <th>p2_dog</th>\n",
       "      <th>p3</th>\n",
       "      <th>p3_conf</th>\n",
       "      <th>p3_dog</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "Empty DataFrame\n",
       "Columns: [tweet_id, jpg_url, img_num, p1, p1_conf, p1_dog, p2, p2_conf, p2_dog, p3, p3_conf, p3_dog]\n",
       "Index: []"
      ]
     },
     "execution_count": 115,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dog_pred_df.query('(p1_dog == False) & (p2_dog == False) & (p3_dog == False)')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c190c0c1",
   "metadata": {},
   "source": [
    "Confirming the three dataframe are in right order"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 116,
   "id": "677e3cf4",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Int64Index: 1914 entries, 9 to 2113\n",
      "Data columns (total 9 columns):\n",
      " #   Column              Non-Null Count  Dtype              \n",
      "---  ------              --------------  -----              \n",
      " 0   tweet_id            1914 non-null   object             \n",
      " 1   timestamp           1914 non-null   datetime64[ns, UTC]\n",
      " 2   source              1914 non-null   category           \n",
      " 3   text                1914 non-null   object             \n",
      " 4   expanded_urls       1914 non-null   object             \n",
      " 5   rating_numerator    1914 non-null   int32              \n",
      " 6   rating_denominator  1914 non-null   int32              \n",
      " 7   name                1332 non-null   object             \n",
      " 8   dog_stages          303 non-null    object             \n",
      "dtypes: category(1), datetime64[ns, UTC](1), int32(2), object(5)\n",
      "memory usage: 121.7+ KB\n"
     ]
    }
   ],
   "source": [
    "Twitter_archive_df.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 117,
   "id": "1e3c9306",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 2354 entries, 0 to 2353\n",
      "Data columns (total 3 columns):\n",
      " #   Column          Non-Null Count  Dtype \n",
      "---  ------          --------------  ----- \n",
      " 0   tweet_id        2354 non-null   object\n",
      " 1   retweet_count   2354 non-null   int64 \n",
      " 2   favorite_count  2354 non-null   int64 \n",
      "dtypes: int64(2), object(1)\n",
      "memory usage: 55.3+ KB\n"
     ]
    }
   ],
   "source": [
    "Tweet_data_df.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 118,
   "id": "5c69d4f8",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Int64Index: 1751 entries, 0 to 2073\n",
      "Data columns (total 12 columns):\n",
      " #   Column    Non-Null Count  Dtype  \n",
      "---  ------    --------------  -----  \n",
      " 0   tweet_id  1751 non-null   int64  \n",
      " 1   jpg_url   1751 non-null   object \n",
      " 2   img_num   1751 non-null   int64  \n",
      " 3   p1        1751 non-null   object \n",
      " 4   p1_conf   1751 non-null   float64\n",
      " 5   p1_dog    1751 non-null   bool   \n",
      " 6   p2        1751 non-null   object \n",
      " 7   p2_conf   1751 non-null   float64\n",
      " 8   p2_dog    1751 non-null   bool   \n",
      " 9   p3        1751 non-null   object \n",
      " 10  p3_conf   1751 non-null   float64\n",
      " 11  p3_dog    1751 non-null   bool   \n",
      "dtypes: bool(3), float64(3), int64(2), object(4)\n",
      "memory usage: 141.9+ KB\n"
     ]
    }
   ],
   "source": [
    "dog_pred_df.info()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c4f186eb",
   "metadata": {},
   "source": [
    "### **Merging the three dataframe together using .merge() function. Using inner and on tweet_id**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 119,
   "id": "521dc4cd",
   "metadata": {},
   "outputs": [],
   "source": [
    "Clean_df = pd.merge(pd.merge(Twitter_archive_df,Tweet_data_df, on='tweet_id', how='inner'),dog_pred_df, on='tweet_id', how='inner')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 120,
   "id": "b8ae3242",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(1520, 22)"
      ]
     },
     "execution_count": 120,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Clean_df.shape"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b10218f0",
   "metadata": {},
   "source": [
    "saving to csv file"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 121,
   "id": "1258119e",
   "metadata": {},
   "outputs": [],
   "source": [
    "Clean_df.to_csv('twitter_archive_master.csv', index=False)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "50e19788",
   "metadata": {},
   "source": [
    "### **Analysing the twitter_archive_master dataset to get insights and visualization** "
   ]
  },
  {
   "cell_type": "markdown",
   "id": "555b2411",
   "metadata": {},
   "source": [
    "**Questions to be analyze:**\n",
    "\n",
    "--Which device is used to tweet the most?\n",
    "\n",
    "--Top tweet IDs with the most average likes\n",
    "\n",
    "--When and in what month did the most tweets occur?\n",
    "\n",
    "--What are the most common dog names"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 122,
   "id": "67868792",
   "metadata": {},
   "outputs": [],
   "source": [
    "# reading the data using pd.read_csv\n",
    "df = pd.read_csv('twitter_archive_master.csv')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "8598d225",
   "metadata": {},
   "source": [
    "Inspecting the top 3"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 123,
   "id": "2cd34126",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>tweet_id</th>\n",
       "      <th>timestamp</th>\n",
       "      <th>source</th>\n",
       "      <th>text</th>\n",
       "      <th>expanded_urls</th>\n",
       "      <th>rating_numerator</th>\n",
       "      <th>rating_denominator</th>\n",
       "      <th>name</th>\n",
       "      <th>dog_stages</th>\n",
       "      <th>retweet_count</th>\n",
       "      <th>...</th>\n",
       "      <th>img_num</th>\n",
       "      <th>p1</th>\n",
       "      <th>p1_conf</th>\n",
       "      <th>p1_dog</th>\n",
       "      <th>p2</th>\n",
       "      <th>p2_conf</th>\n",
       "      <th>p2_dog</th>\n",
       "      <th>p3</th>\n",
       "      <th>p3_conf</th>\n",
       "      <th>p3_dog</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>890240255349198849</td>\n",
       "      <td>2017-07-26 15:59:51+00:00</td>\n",
       "      <td>Twitter for iPhone</td>\n",
       "      <td>This is Cassie. She is a college pup. Studying...</td>\n",
       "      <td>https://twitter.com/dog_rates/status/890240255...</td>\n",
       "      <td>14</td>\n",
       "      <td>10</td>\n",
       "      <td>Cassie</td>\n",
       "      <td>doggo</td>\n",
       "      <td>7711</td>\n",
       "      <td>...</td>\n",
       "      <td>1</td>\n",
       "      <td>Pembroke</td>\n",
       "      <td>0.511319</td>\n",
       "      <td>True</td>\n",
       "      <td>Cardigan</td>\n",
       "      <td>0.451038</td>\n",
       "      <td>True</td>\n",
       "      <td>Chihuahua</td>\n",
       "      <td>0.029248</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>760893934457552897</td>\n",
       "      <td>2016-08-03 17:43:45+00:00</td>\n",
       "      <td>Twitter for iPhone</td>\n",
       "      <td>This is Wishes. He has the day off. Daily stru...</td>\n",
       "      <td>https://twitter.com/dog_rates/status/760893934...</td>\n",
       "      <td>11</td>\n",
       "      <td>10</td>\n",
       "      <td>Wishes</td>\n",
       "      <td>doggo</td>\n",
       "      <td>1104</td>\n",
       "      <td>...</td>\n",
       "      <td>1</td>\n",
       "      <td>Blenheim_spaniel</td>\n",
       "      <td>0.113992</td>\n",
       "      <td>True</td>\n",
       "      <td>cocker_spaniel</td>\n",
       "      <td>0.105780</td>\n",
       "      <td>True</td>\n",
       "      <td>borzoi</td>\n",
       "      <td>0.073935</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>775364825476165632</td>\n",
       "      <td>2016-09-12 16:05:54+00:00</td>\n",
       "      <td>Twitter for iPhone</td>\n",
       "      <td>This is Finley. He's an independent doggo stil...</td>\n",
       "      <td>https://twitter.com/dog_rates/status/775364825...</td>\n",
       "      <td>11</td>\n",
       "      <td>10</td>\n",
       "      <td>Finley</td>\n",
       "      <td>doggo</td>\n",
       "      <td>3472</td>\n",
       "      <td>...</td>\n",
       "      <td>3</td>\n",
       "      <td>beagle</td>\n",
       "      <td>0.571229</td>\n",
       "      <td>True</td>\n",
       "      <td>Chihuahua</td>\n",
       "      <td>0.175257</td>\n",
       "      <td>True</td>\n",
       "      <td>Pembroke</td>\n",
       "      <td>0.034306</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>3 rows × 22 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "             tweet_id                  timestamp              source  \\\n",
       "0  890240255349198849  2017-07-26 15:59:51+00:00  Twitter for iPhone   \n",
       "1  760893934457552897  2016-08-03 17:43:45+00:00  Twitter for iPhone   \n",
       "2  775364825476165632  2016-09-12 16:05:54+00:00  Twitter for iPhone   \n",
       "\n",
       "                                                text  \\\n",
       "0  This is Cassie. She is a college pup. Studying...   \n",
       "1  This is Wishes. He has the day off. Daily stru...   \n",
       "2  This is Finley. He's an independent doggo stil...   \n",
       "\n",
       "                                       expanded_urls  rating_numerator  \\\n",
       "0  https://twitter.com/dog_rates/status/890240255...                14   \n",
       "1  https://twitter.com/dog_rates/status/760893934...                11   \n",
       "2  https://twitter.com/dog_rates/status/775364825...                11   \n",
       "\n",
       "   rating_denominator    name dog_stages  retweet_count  ...  img_num  \\\n",
       "0                  10  Cassie      doggo           7711  ...        1   \n",
       "1                  10  Wishes      doggo           1104  ...        1   \n",
       "2                  10  Finley      doggo           3472  ...        3   \n",
       "\n",
       "                 p1   p1_conf p1_dog              p2   p2_conf p2_dog  \\\n",
       "0          Pembroke  0.511319   True        Cardigan  0.451038   True   \n",
       "1  Blenheim_spaniel  0.113992   True  cocker_spaniel  0.105780   True   \n",
       "2            beagle  0.571229   True       Chihuahua  0.175257   True   \n",
       "\n",
       "          p3   p3_conf p3_dog  \n",
       "0  Chihuahua  0.029248   True  \n",
       "1     borzoi  0.073935   True  \n",
       "2   Pembroke  0.034306   True  \n",
       "\n",
       "[3 rows x 22 columns]"
      ]
     },
     "execution_count": 123,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head(3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 124,
   "id": "44366e3e",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 1520 entries, 0 to 1519\n",
      "Data columns (total 22 columns):\n",
      " #   Column              Non-Null Count  Dtype  \n",
      "---  ------              --------------  -----  \n",
      " 0   tweet_id            1520 non-null   int64  \n",
      " 1   timestamp           1520 non-null   object \n",
      " 2   source              1520 non-null   object \n",
      " 3   text                1520 non-null   object \n",
      " 4   expanded_urls       1520 non-null   object \n",
      " 5   rating_numerator    1520 non-null   int64  \n",
      " 6   rating_denominator  1520 non-null   int64  \n",
      " 7   name                1135 non-null   object \n",
      " 8   dog_stages          233 non-null    object \n",
      " 9   retweet_count       1520 non-null   int64  \n",
      " 10  favorite_count      1520 non-null   int64  \n",
      " 11  jpg_url             1520 non-null   object \n",
      " 12  img_num             1520 non-null   int64  \n",
      " 13  p1                  1520 non-null   object \n",
      " 14  p1_conf             1520 non-null   float64\n",
      " 15  p1_dog              1520 non-null   bool   \n",
      " 16  p2                  1520 non-null   object \n",
      " 17  p2_conf             1520 non-null   float64\n",
      " 18  p2_dog              1520 non-null   bool   \n",
      " 19  p3                  1520 non-null   object \n",
      " 20  p3_conf             1520 non-null   float64\n",
      " 21  p3_dog              1520 non-null   bool   \n",
      "dtypes: bool(3), float64(3), int64(6), object(10)\n",
      "memory usage: 230.2+ KB\n"
     ]
    }
   ],
   "source": [
    "df.info()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b0ea51b7",
   "metadata": {},
   "source": [
    "Changing the dtypes of tweet_id and img_num"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 125,
   "id": "301924cc",
   "metadata": {},
   "outputs": [],
   "source": [
    "df['tweet_id'] = df['tweet_id'].astype('object')\n",
    "df['img_num'] = df['img_num'].astype('category')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d9966c44",
   "metadata": {},
   "source": [
    "checking missing values"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 126,
   "id": "b5b1c492",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "tweet_id                 0\n",
       "timestamp                0\n",
       "source                   0\n",
       "text                     0\n",
       "expanded_urls            0\n",
       "rating_numerator         0\n",
       "rating_denominator       0\n",
       "name                   385\n",
       "dog_stages            1287\n",
       "retweet_count            0\n",
       "favorite_count           0\n",
       "jpg_url                  0\n",
       "img_num                  0\n",
       "p1                       0\n",
       "p1_conf                  0\n",
       "p1_dog                   0\n",
       "p2                       0\n",
       "p2_conf                  0\n",
       "p2_dog                   0\n",
       "p3                       0\n",
       "p3_conf                  0\n",
       "p3_dog                   0\n",
       "dtype: int64"
      ]
     },
     "execution_count": 126,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.isnull().sum()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "1a77453b",
   "metadata": {},
   "source": [
    "checking for numerical distribution of the data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 127,
   "id": "53fa3c5e",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
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       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>rating_numerator</th>\n",
       "      <th>rating_denominator</th>\n",
       "      <th>retweet_count</th>\n",
       "      <th>favorite_count</th>\n",
       "      <th>p1_conf</th>\n",
       "      <th>p2_conf</th>\n",
       "      <th>p3_conf</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>1520.000000</td>\n",
       "      <td>1520.000000</td>\n",
       "      <td>1520.000000</td>\n",
       "      <td>1520.000000</td>\n",
       "      <td>1520.000000</td>\n",
       "      <td>1520.000000</td>\n",
       "      <td>1520.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>11.385526</td>\n",
       "      <td>10.492105</td>\n",
       "      <td>2674.194737</td>\n",
       "      <td>8949.605263</td>\n",
       "      <td>0.604381</td>\n",
       "      <td>0.136855</td>\n",
       "      <td>0.061874</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>7.538275</td>\n",
       "      <td>6.558689</td>\n",
       "      <td>4569.875289</td>\n",
       "      <td>12186.197498</td>\n",
       "      <td>0.267961</td>\n",
       "      <td>0.100927</td>\n",
       "      <td>0.052490</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>7.000000</td>\n",
       "      <td>16.000000</td>\n",
       "      <td>81.000000</td>\n",
       "      <td>0.044333</td>\n",
       "      <td>0.000010</td>\n",
       "      <td>0.000001</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>10.000000</td>\n",
       "      <td>10.000000</td>\n",
       "      <td>651.500000</td>\n",
       "      <td>2212.000000</td>\n",
       "      <td>0.374963</td>\n",
       "      <td>0.054704</td>\n",
       "      <td>0.016055</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>11.000000</td>\n",
       "      <td>10.000000</td>\n",
       "      <td>1402.500000</td>\n",
       "      <td>4226.000000</td>\n",
       "      <td>0.606253</td>\n",
       "      <td>0.121376</td>\n",
       "      <td>0.049527</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>12.000000</td>\n",
       "      <td>10.000000</td>\n",
       "      <td>3129.250000</td>\n",
       "      <td>11315.500000</td>\n",
       "      <td>0.853978</td>\n",
       "      <td>0.198024</td>\n",
       "      <td>0.095050</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>165.000000</td>\n",
       "      <td>150.000000</td>\n",
       "      <td>79515.000000</td>\n",
       "      <td>132810.000000</td>\n",
       "      <td>0.999984</td>\n",
       "      <td>0.464816</td>\n",
       "      <td>0.273419</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       rating_numerator  rating_denominator  retweet_count  favorite_count  \\\n",
       "count       1520.000000         1520.000000    1520.000000     1520.000000   \n",
       "mean          11.385526           10.492105    2674.194737     8949.605263   \n",
       "std            7.538275            6.558689    4569.875289    12186.197498   \n",
       "min            0.000000            7.000000      16.000000       81.000000   \n",
       "25%           10.000000           10.000000     651.500000     2212.000000   \n",
       "50%           11.000000           10.000000    1402.500000     4226.000000   \n",
       "75%           12.000000           10.000000    3129.250000    11315.500000   \n",
       "max          165.000000          150.000000   79515.000000   132810.000000   \n",
       "\n",
       "           p1_conf      p2_conf      p3_conf  \n",
       "count  1520.000000  1520.000000  1520.000000  \n",
       "mean      0.604381     0.136855     0.061874  \n",
       "std       0.267961     0.100927     0.052490  \n",
       "min       0.044333     0.000010     0.000001  \n",
       "25%       0.374963     0.054704     0.016055  \n",
       "50%       0.606253     0.121376     0.049527  \n",
       "75%       0.853978     0.198024     0.095050  \n",
       "max       0.999984     0.464816     0.273419  "
      ]
     },
     "execution_count": 127,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 128,
   "id": "389e8ca7",
   "metadata": {},
   "outputs": [],
   "source": [
    "# changing timestamp to datetime\n",
    "df['timestamp'] = pd.to_datetime(df['timestamp'])"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "903a33e1",
   "metadata": {},
   "source": [
    "#### **Which device is used to tweet the most?**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 129,
   "id": "0cc25c80",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Twitter for iPhone    1493\n",
       "Twitter Web Client      19\n",
       "TweetDeck                8\n",
       "Name: source, dtype: int64"
      ]
     },
     "execution_count": 129,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['source'].value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 130,
   "id": "568977ac",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "df['source'].value_counts().plot(kind='barh', title='Tweet source', xlabel='source', ylabel='frequency');"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5eea2ac5",
   "metadata": {},
   "source": [
    "Around 98% users tweet by iPhone"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e5e2b4c2",
   "metadata": {},
   "source": [
    "#### **Top tweet IDs with the most average likes**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 131,
   "id": "56c0849b",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\USER\\AppData\\Local\\Temp\\ipykernel_15200\\1086355708.py:1: FutureWarning: Indexing with multiple keys (implicitly converted to a tuple of keys) will be deprecated, use a list instead.\n",
      "  df.groupby('tweet_id')['retweet_count','favorite_count'].mean().nlargest(3, 'favorite_count')\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>retweet_count</th>\n",
       "      <th>favorite_count</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>tweet_id</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>822872901745569793</th>\n",
       "      <td>48265.0</td>\n",
       "      <td>132810.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>744234799360020481</th>\n",
       "      <td>79515.0</td>\n",
       "      <td>131075.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>879415818425184262</th>\n",
       "      <td>45849.0</td>\n",
       "      <td>107956.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                    retweet_count  favorite_count\n",
       "tweet_id                                         \n",
       "822872901745569793        48265.0        132810.0\n",
       "744234799360020481        79515.0        131075.0\n",
       "879415818425184262        45849.0        107956.0"
      ]
     },
     "execution_count": 131,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.groupby('tweet_id')['retweet_count','favorite_count'].mean().nlargest(3, 'favorite_count')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "60aa4b11",
   "metadata": {},
   "source": [
    "Checking for the attributes that makes it favorites"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 132,
   "id": "9dafe2c9",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>tweet_id</th>\n",
       "      <th>timestamp</th>\n",
       "      <th>source</th>\n",
       "      <th>text</th>\n",
       "      <th>expanded_urls</th>\n",
       "      <th>rating_numerator</th>\n",
       "      <th>rating_denominator</th>\n",
       "      <th>name</th>\n",
       "      <th>dog_stages</th>\n",
       "      <th>retweet_count</th>\n",
       "      <th>...</th>\n",
       "      <th>img_num</th>\n",
       "      <th>p1</th>\n",
       "      <th>p1_conf</th>\n",
       "      <th>p1_dog</th>\n",
       "      <th>p2</th>\n",
       "      <th>p2_conf</th>\n",
       "      <th>p2_dog</th>\n",
       "      <th>p3</th>\n",
       "      <th>p3_conf</th>\n",
       "      <th>p3_dog</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>223</th>\n",
       "      <td>822872901745569793</td>\n",
       "      <td>2017-01-21 18:26:02+00:00</td>\n",
       "      <td>Twitter for iPhone</td>\n",
       "      <td>Here's a super supportive puppo participating ...</td>\n",
       "      <td>https://twitter.com/dog_rates/status/822872901...</td>\n",
       "      <td>13</td>\n",
       "      <td>10</td>\n",
       "      <td>NaN</td>\n",
       "      <td>puppo</td>\n",
       "      <td>48265</td>\n",
       "      <td>...</td>\n",
       "      <td>1</td>\n",
       "      <td>Lakeland_terrier</td>\n",
       "      <td>0.196015</td>\n",
       "      <td>True</td>\n",
       "      <td>Labrador_retriever</td>\n",
       "      <td>0.160329</td>\n",
       "      <td>True</td>\n",
       "      <td>Irish_terrier</td>\n",
       "      <td>0.069126</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>1 rows × 22 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "               tweet_id                 timestamp              source  \\\n",
       "223  822872901745569793 2017-01-21 18:26:02+00:00  Twitter for iPhone   \n",
       "\n",
       "                                                  text  \\\n",
       "223  Here's a super supportive puppo participating ...   \n",
       "\n",
       "                                         expanded_urls  rating_numerator  \\\n",
       "223  https://twitter.com/dog_rates/status/822872901...                13   \n",
       "\n",
       "     rating_denominator name dog_stages  retweet_count  ...  img_num  \\\n",
       "223                  10  NaN      puppo          48265  ...        1   \n",
       "\n",
       "                   p1   p1_conf p1_dog                  p2   p2_conf p2_dog  \\\n",
       "223  Lakeland_terrier  0.196015   True  Labrador_retriever  0.160329   True   \n",
       "\n",
       "                p3   p3_conf p3_dog  \n",
       "223  Irish_terrier  0.069126   True  \n",
       "\n",
       "[1 rows x 22 columns]"
      ]
     },
     "execution_count": 132,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.query('tweet_id==822872901745569793')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2c667aa5",
   "metadata": {},
   "source": [
    "#### **When and in what month did the most tweets occur?**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 133,
   "id": "8ed2dab0",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "timestamp  timestamp\n",
       "2015       11           194\n",
       "           12           258\n",
       "2016       1            133\n",
       "           2             84\n",
       "           3            102\n",
       "           4             47\n",
       "           5             45\n",
       "           6             55\n",
       "           7             73\n",
       "           8             42\n",
       "           9             52\n",
       "           10            55\n",
       "           11            44\n",
       "           12            48\n",
       "2017       1             52\n",
       "           2             54\n",
       "           3             37\n",
       "           4             32\n",
       "           5             29\n",
       "           6             38\n",
       "           7             45\n",
       "           8              1\n",
       "Name: tweet_id, dtype: int64"
      ]
     },
     "execution_count": 133,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.tweet_id.groupby([df['timestamp'].dt.year, df['timestamp'].dt.month]).count()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0ae67d0c",
   "metadata": {},
   "source": [
    "December, 2015 have the highest tweets"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 134,
   "id": "c8b33e88",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "df.tweet_id.groupby([df['timestamp'].dt.year, df['timestamp'].dt.month]).count().plot(kind='line', \n",
    "                                                                                      title='Tweets Trend with time',xlabel='trend',\n",
    "                                                                                     ylabel='frequency');"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7057fa88",
   "metadata": {},
   "source": [
    "The above visualization shows that Tweets trend decrease with time with highest(peak) tweets in December, 2015"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "bf509624",
   "metadata": {},
   "source": [
    "#### **What are the most common dog names**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 135,
   "id": "eebfe6d0",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Lucy       10\n",
       "Tucker      9\n",
       "Charlie     9\n",
       "Cooper      9\n",
       "Oliver      8\n",
       "Name: name, dtype: int64"
      ]
     },
     "execution_count": 135,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.name.value_counts().nlargest(5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 136,
   "id": "e1d0e068",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:title={'center':'Common Dog Names'}, xlabel='Dog names', ylabel='Frequency'>"
      ]
     },
     "execution_count": 136,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "df.name.value_counts().nlargest(5).plot(kind='bar', title='Common Dog Names', xlabel='Dog names', ylabel='Frequency') "
   ]
  },
  {
   "cell_type": "markdown",
   "id": "251c442a",
   "metadata": {},
   "source": [
    "Tucker, Charlie, and Copper have the same occurence while Lucy occur most"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "514f63a3",
   "metadata": {},
   "source": [
    "**Visualizing ratings distribution**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 137,
   "id": "e9163500",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "df['rating_numerator'].value_counts().sort_index().plot(kind='bar', title='ratings numerator distribution', xlabel='distribution');"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c9fea1e0",
   "metadata": {},
   "source": [
    "The above plot shows the distribution of dog ratings with minimum to be 0 and mostly concentrated between 10-13. The ratings numerator is not evenly distributed"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 138,
   "id": "7b57734e",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "df['rating_denominator'].value_counts().sort_index().plot(kind='bar', title='ratings denominator distribution');"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b66b6d40",
   "metadata": {},
   "source": [
    "The above plot shows the distribution of dog ratings denominator with minimum to be 7 and mostly concentrated between 9-10. The ratings denominator is not evenly distributed"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "a54c12c9",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "98ecc997",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.8.13"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}