Project Part 4.0 Open .json file & Conver to .csv.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 4999 entries, 0 to 4998\n",
      "Data columns (total 28 columns):\n",
      "contributors                 0 non-null object\n",
      "coordinates                  27 non-null object\n",
      "created_at                   4999 non-null object\n",
      "entities                     4999 non-null object\n",
      "favorite_count               4999 non-null int64\n",
      "favorited                    4999 non-null bool\n",
      "geo                          27 non-null object\n",
      "id                           4999 non-null int64\n",
      "id_str                       4999 non-null object\n",
      "in_reply_to_screen_name      2956 non-null object\n",
      "in_reply_to_status_id        2452 non-null float64\n",
      "in_reply_to_status_id_str    2452 non-null object\n",
      "in_reply_to_user_id          2956 non-null float64\n",
      "in_reply_to_user_id_str      2956 non-null object\n",
      "is_quote_status              4999 non-null bool\n",
      "lang                         4999 non-null object\n",
      "metadata                     4999 non-null object\n",
      "place                        261 non-null object\n",
      "possibly_sensitive           1107 non-null object\n",
      "quoted_status                189 non-null object\n",
      "quoted_status_id             189 non-null float64\n",
      "quoted_status_id_str         189 non-null object\n",
      "retweet_count                4999 non-null int64\n",
      "retweeted                    4999 non-null bool\n",
      "source                       4999 non-null object\n",
      "text                         4999 non-null object\n",
      "truncated                    4999 non-null bool\n",
      "user                         4999 non-null object\n",
      "dtypes: bool(4), float64(3), int64(3), object(18)\n",
      "memory usage: 956.9+ KB\n"
     ]
    }
   ],
   "source": [
    "import json\n",
    "import os\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "os.chdir('C:\\\\Users\\\\wmj51\\\\Desktop\\\\python')\n",
    "\n",
    "data = []\n",
    "\n",
    "with open(\"positive_tweets.json\") as f:\n",
    "    # use 'marid_post_week3 as a test sample'\n",
    "    for line in f:\n",
    "        try:\n",
    "            tweet = json.loads(line)\n",
    "            if tweet['text'].find('RT @')!=-1:\n",
    "            # drop Retweeted tweet\n",
    "                continue\n",
    "            data.append(tweet)\n",
    "        except:\n",
    "            continue\n",
    "\n",
    "with open('npositive_tweets.json','w') as fp:\n",
    "    json.dump(data,fp)\n",
    "\n",
    "tweets_data_path=('npositive_tweets.json')\n",
    "tweets_data = []\n",
    "tweets_file = open(tweets_data_path,'r')\n",
    "tweets_data = json.load(tweets_file)\n",
    "type(tweets_data)\n",
    "\n",
    "# convert the json file to dataframe\n",
    "df = pd.DataFrame(tweets_data)\n",
    "df.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "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>text</th>\n",
       "      <th>target</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>#FollowFriday @France_Inte @PKuchly57 @Milipol...</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>@Lamb2ja Hey James! How odd :/ Please call our...</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>@DespiteOfficial we had a listen last night :)...</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>@97sides CONGRATS :)</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>yeaaaah yippppy!!!  my accnt verified rqst has...</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                                text  target\n",
       "0  #FollowFriday @France_Inte @PKuchly57 @Milipol...       1\n",
       "1  @Lamb2ja Hey James! How odd :/ Please call our...       1\n",
       "2  @DespiteOfficial we had a listen last night :)...       1\n",
       "3                               @97sides CONGRATS :)       1\n",
       "4  yeaaaah yippppy!!!  my accnt verified rqst has...       1"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "col_to_keep = ['text']\n",
    "df = df[col_to_keep]\n",
    "df['target'] = 1\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 4998 entries, 0 to 4997\n",
      "Data columns (total 28 columns):\n",
      "contributors                 0 non-null object\n",
      "coordinates                  36 non-null object\n",
      "created_at                   4998 non-null object\n",
      "entities                     4998 non-null object\n",
      "favorite_count               4998 non-null int64\n",
      "favorited                    4998 non-null bool\n",
      "geo                          36 non-null object\n",
      "id                           4998 non-null int64\n",
      "id_str                       4998 non-null object\n",
      "in_reply_to_screen_name      2374 non-null object\n",
      "in_reply_to_status_id        2056 non-null float64\n",
      "in_reply_to_status_id_str    2056 non-null object\n",
      "in_reply_to_user_id          2374 non-null float64\n",
      "in_reply_to_user_id_str      2374 non-null object\n",
      "is_quote_status              4998 non-null bool\n",
      "lang                         4998 non-null object\n",
      "metadata                     4998 non-null object\n",
      "place                        234 non-null object\n",
      "possibly_sensitive           554 non-null object\n",
      "quoted_status                135 non-null object\n",
      "quoted_status_id             136 non-null float64\n",
      "quoted_status_id_str         136 non-null object\n",
      "retweet_count                4998 non-null int64\n",
      "retweeted                    4998 non-null bool\n",
      "source                       4998 non-null object\n",
      "text                         4998 non-null object\n",
      "truncated                    4998 non-null bool\n",
      "user                         4998 non-null object\n",
      "dtypes: bool(4), float64(3), int64(3), object(18)\n",
      "memory usage: 956.7+ KB\n"
     ]
    }
   ],
   "source": [
    "data = []\n",
    "\n",
    "with open(\"negative_tweets.json\") as f:\n",
    "    # use 'marid_post_week3 as a test sample'\n",
    "    for line in f:\n",
    "        try:\n",
    "            tweet = json.loads(line)\n",
    "            if tweet['text'].find('RT @')!=-1:\n",
    "            # drop Retweeted tweet\n",
    "                continue\n",
    "            data.append(tweet)\n",
    "        except:\n",
    "            continue\n",
    "\n",
    "with open('nnegative_tweets.json','w') as fp:\n",
    "    json.dump(data,fp)\n",
    "\n",
    "tweets_data_path=('nnegative_tweets.json')\n",
    "tweets_data = []\n",
    "tweets_file = open(tweets_data_path,'r')\n",
    "tweets_data = json.load(tweets_file)\n",
    "type(tweets_data)\n",
    "\n",
    "# convert the json file to dataframe\n",
    "df2 = pd.DataFrame(tweets_data)\n",
    "df2.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "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>text</th>\n",
       "      <th>target</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>hopeless for tmr :(</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Everything in the kids section of IKEA is so c...</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>@Hegelbon That heart sliding into the waste ba...</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>“@ketchBurning: I hate Japanese call him \"bani...</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Dang starting next week I have \"work\" :(</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                                text  target\n",
       "0                                hopeless for tmr :(       0\n",
       "1  Everything in the kids section of IKEA is so c...       0\n",
       "2  @Hegelbon That heart sliding into the waste ba...       0\n",
       "3  “@ketchBurning: I hate Japanese call him \"bani...       0\n",
       "4           Dang starting next week I have \"work\" :(       0"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "col_to_keep = ['text']\n",
    "df2 = df2[col_to_keep]\n",
    "df2['target'] = 0\n",
    "df2.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_tweets = pd.concat([df, df2])\n",
    "df_tweets.head()\n",
    "df_tweets.to_csv('train_NLTKCorpus_Twitter.csv', encoding='utf-8')"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 2",
   "language": "python",
   "name": "python2"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 2
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython2",
   "version": "2.7.14"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}