sentiment-analysis-on-the-dataset.ipynb

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   "source": [
    "# Step0: Load all the imports"
   ]
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    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/opt/conda/lib/python3.10/site-packages/scipy/__init__.py:146: UserWarning: A NumPy version >=1.16.5 and <1.23.0 is required for this version of SciPy (detected version 1.23.5\n",
      "  warnings.warn(f\"A NumPy version >={np_minversion} and <{np_maxversion}\"\n",
      "/opt/conda/lib/python3.10/site-packages/nltk/twitter/__init__.py:20: UserWarning: The twython library has not been installed. Some functionality from the twitter package will not be available.\n",
      "  warnings.warn(\"The twython library has not been installed. \"\n"
     ]
    }
   ],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import nltk\n",
    "from nltk.sentiment import SentimentIntensityAnalyzer\n",
    "from tqdm.auto import tqdm\n",
    "import seaborn as sns\n",
    "\n",
    "plt.style.use('ggplot')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "927265e9",
   "metadata": {
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     "status": "completed"
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    "tags": []
   },
   "outputs": [],
   "source": [
    "df = pd.read_csv(\"/kaggle/input/37000-reviews-of-thread-app-dataset/37000_reviews_of_thread_app.csv\",usecols=['source','review_id','user_name','review_description','rating','review_date','laguage_code','country_code','thumbs_up'])"
   ]
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  {
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   "execution_count": 3,
   "id": "61555bbc",
   "metadata": {
    "execution": {
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     "status": "completed"
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   "outputs": [],
   "source": [
    "df.reset_index(inplace = True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "8bc93fca",
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    {
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       "\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>index</th>\n",
       "      <th>source</th>\n",
       "      <th>review_id</th>\n",
       "      <th>user_name</th>\n",
       "      <th>review_description</th>\n",
       "      <th>rating</th>\n",
       "      <th>thumbs_up</th>\n",
       "      <th>review_date</th>\n",
       "      <th>laguage_code</th>\n",
       "      <th>country_code</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0</td>\n",
       "      <td>Google Play</td>\n",
       "      <td>7cd90e5b-4829-43b9-9fb4-c8c6d1e339c1</td>\n",
       "      <td>Eddie Clark Jr.</td>\n",
       "      <td>Good</td>\n",
       "      <td>5</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2023-08-07 19:14:36</td>\n",
       "      <td>en</td>\n",
       "      <td>us</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>Google Play</td>\n",
       "      <td>6deb8265-2bac-4524-bcb6-f90829fa4e69</td>\n",
       "      <td>Rasa RT</td>\n",
       "      <td>Weak copy of Twitter</td>\n",
       "      <td>1</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2023-08-07 19:07:04</td>\n",
       "      <td>en</td>\n",
       "      <td>us</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2</td>\n",
       "      <td>Google Play</td>\n",
       "      <td>91ef61ce-0f05-4f3b-b3d3-5d19cd408ab8</td>\n",
       "      <td>SITI NUR HAFIZA BINTI AZIZ</td>\n",
       "      <td>i wish threads have a save button for images a...</td>\n",
       "      <td>3</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2023-08-07 18:57:07</td>\n",
       "      <td>en</td>\n",
       "      <td>us</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>3</td>\n",
       "      <td>Google Play</td>\n",
       "      <td>b7721b78-6b77-4f8c-a1d3-a854af4c1f0f</td>\n",
       "      <td>Asap Khalifah</td>\n",
       "      <td>Love it</td>\n",
       "      <td>5</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2023-08-07 18:37:16</td>\n",
       "      <td>en</td>\n",
       "      <td>us</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>4</td>\n",
       "      <td>Google Play</td>\n",
       "      <td>c89ef522-c94c-4171-878f-1d672dce7f11</td>\n",
       "      <td>Syed Hussein</td>\n",
       "      <td>Very god</td>\n",
       "      <td>5</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2023-08-07 18:14:15</td>\n",
       "      <td>en</td>\n",
       "      <td>us</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   index       source                             review_id  \\\n",
       "0      0  Google Play  7cd90e5b-4829-43b9-9fb4-c8c6d1e339c1   \n",
       "1      1  Google Play  6deb8265-2bac-4524-bcb6-f90829fa4e69   \n",
       "2      2  Google Play  91ef61ce-0f05-4f3b-b3d3-5d19cd408ab8   \n",
       "3      3  Google Play  b7721b78-6b77-4f8c-a1d3-a854af4c1f0f   \n",
       "4      4  Google Play  c89ef522-c94c-4171-878f-1d672dce7f11   \n",
       "\n",
       "                    user_name  \\\n",
       "0             Eddie Clark Jr.   \n",
       "1                     Rasa RT   \n",
       "2  SITI NUR HAFIZA BINTI AZIZ   \n",
       "3               Asap Khalifah   \n",
       "4                Syed Hussein   \n",
       "\n",
       "                                  review_description  rating  thumbs_up  \\\n",
       "0                                               Good       5        0.0   \n",
       "1                               Weak copy of Twitter       1        0.0   \n",
       "2  i wish threads have a save button for images a...       3        0.0   \n",
       "3                                            Love it       5        0.0   \n",
       "4                                           Very god       5        0.0   \n",
       "\n",
       "           review_date laguage_code country_code  \n",
       "0  2023-08-07 19:14:36           en           us  \n",
       "1  2023-08-07 19:07:04           en           us  \n",
       "2  2023-08-07 18:57:07           en           us  \n",
       "3  2023-08-07 18:37:16           en           us  \n",
       "4  2023-08-07 18:14:15           en           us  "
      ]
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     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head()"
   ]
  },
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   "cell_type": "code",
   "execution_count": 5,
   "id": "fb69322d",
   "metadata": {
    "execution": {
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     "start_time": "2023-08-10T07:34:37.857585",
     "status": "completed"
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    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(36943, 10)"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.shape"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f1f15f95",
   "metadata": {
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     "duration": 0.009712,
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     "start_time": "2023-08-10T07:34:37.889377",
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    "tags": []
   },
   "source": [
    "# step1: Some eda [univariate eda,numerical data]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "12edb020",
   "metadata": {
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    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "5    17000\n",
       "1    11282\n",
       "4     3588\n",
       "3     2956\n",
       "2     2117\n",
       "Name: rating, dtype: int64"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['rating'].value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "948bd817",
   "metadata": {
    "execution": {
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     "duration": 0.02864,
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     "exception": false,
     "start_time": "2023-08-10T07:34:37.946469",
     "status": "completed"
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    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.0      30611\n",
       "1.0       2889\n",
       "2.0        520\n",
       "3.0        193\n",
       "4.0        124\n",
       "         ...  \n",
       "164.0        1\n",
       "91.0         1\n",
       "547.0        1\n",
       "268.0        1\n",
       "114.0        1\n",
       "Name: thumbs_up, Length: 149, dtype: int64"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['thumbs_up'].value_counts()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e01fe110",
   "metadata": {
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     "duration": 0.009954,
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     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "## 1. Some plots"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "827aaa99",
   "metadata": {
    "execution": {
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    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Axes: title={'center': 'count for ratings'}>"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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lBx54QFdccYVfm9LSUv3qV7/S4cOHZRiG4uLi9L3vfU/9+/eXJPl8PuXk5GjXrl2qr69XUlKSZs6cqX79+pl9eDwerV+/Xnv37pUkjR49Wunp6erdu7fZprKyUmvXrtWhQ4cUHByssWPHKi0tTXZ7m08LAABYUJtndOrq6jR48GClp6e3uL+8vFyPPvqoBg0apEWLFumnP/2pbrnlFjkcDrPNhg0btGfPHmVmZio7O1u1tbVavny5mpqazDarVq1ScXGxsrKylJWVpeLiYq1evdrc39TUpGXLlqmurk7Z2dnKzMzUBx98oBdeeKGtpwQAACyqzUFnxIgRmjZtmsaMGdPi/pdfflkjRozQ9OnTFR8fr6997WsaOXKkwsLCJEler1c7duxQWlqakpOTFR8fr3nz5qmkpER5eXmSTs0IHThwQHPmzJHb7Zbb7dbs2bO1f/9+HTt2TJL04YcfqrS0VPPmzVN8fLySk5OVlpam7du3y+v1ftnrAQAALKRd7/E0NTVp//79mjJlipYuXaqioiINHDhQN998s3l7q7CwUI2NjUpOTjaPi4yMlMvlUkFBgVJSUlRQUCCn06nExESzjdvtltPpVH5+vmJiYlRQUCCXy6XIyEizzfDhw+Xz+VRYWKikpKRm4/P5fPL5fOZrm82mXr16mT93VafH3pXPwSqoReCgFoGDWnQ/gVTrdg06NTU1qq2t1ebNm3X77bfrzjvv1IEDB/Szn/1MCxcu1LBhw1RdXS273a7Q0FC/Y8PCwlRdXS1Jqq6uNmeA2tImNDRUdrvdbHO23Nxcbdq0yXwdHx+vFStWaMCAAV/+pANIVFRUZw8B/0ItAge1CBzUonU+6uwBtIPo6OjOHoKp3Wd0pFMLhydPnixJGjx4sPLz8/Xuu+9q2LBh5zzWMIzz9m8Yhl9KbCkxnt3mTKmpqea4zjy+oqJCDQ0N533/QGWz2RQVFaXy8vJWXUd0HGoROKhF4KAW3U9ZWVmH9m+321s9SdGuQadv374KCgpSbGys3/ZBgwYpPz9fkhQeHq6GhgZ5PB6/WZ2amhoNHTrUbHPixIlm/dfU1JizOOHh4Tp69Kjffo/Ho8bGxhZngyTJ4XD4LYo+kxX+8hmGYYnzsAJqETioReCgFt1HINW5XZ+jY7fbdfHFF5sLhk8rKyszv1qekJCgoKAgc+GxJFVVVamkpERut1vSqfU4Xq/XL8gcOXJEXq/XDENut1slJSWqqqoy2+Tl5cnhcCghIaE9TwsAAHRRbQ46tbW1Ki4uVnFxsSTp+PHjKi4uVmVlpSRpypQp2r17t9577z2Vl5fr7bff1r59+3T99ddLkpxOpyZOnKicnBz97W9/U1FRkVavXi2Xy2UuUI6NjVVKSorWrFmjgoICFRQUaM2aNRo5cqRiYmIknVp4HBsbq6eeekpFRUX629/+ppycHF177bVyOp3tcW0AAEAXZzPaOL906NAhLV68uNn28ePHa+7cuZKkHTt26I033tCnn36qmJgY3XbbbfqP//gPs219fb02btyonTt3+j0w8PSsj3TqNtS6deu0b98+SdKoUaOUkZHR4gMDDx48qODgYI0bN0533XXXOW9PnUtFRYXft7G6GpvNpujoaJWVlQXUdGF3RC0CB7UIHNSibRpnTensIXxlQc9u6dD+HQ5Hq9fotDnoWBFBB+2FWgQOahE4qEXbEHTOry1Bh991BQAALIugAwAALIugAwAALIugAwAALIugAwAALIugAwAALIugAwAALIugAwAALIugAwAALIugAwAALIugAwAALIugAwAALIugAwAALIugAwAALIugAwAALIugAwAALIugAwAALIugAwAALIugAwAALIugAwAALIugAwAALIugAwAALIugAwAALIugAwAALIugAwAALIugAwAALIugAwAALIugAwAALIugAwAALIugAwAALIugAwAALMve1gMOHz6sLVu2qKioSFVVVXrggQd0xRVXtNj2mWee0XvvvacZM2bopptuMrf7fD7l5ORo165dqq+vV1JSkmbOnKl+/fqZbTwej9avX6+9e/dKkkaPHq309HT17t3bbFNZWam1a9fq0KFDCg4O1tixY5WWlia7vc2nBQAALKjNMzp1dXUaPHiw0tPTv7Ddnj17dOTIEUVERDTbt2HDBu3Zs0eZmZnKzs5WbW2tli9frqamJrPNqlWrVFxcrKysLGVlZam4uFirV6829zc1NWnZsmWqq6tTdna2MjMz9cEHH+iFF15o6ykBAACLanPQGTFihKZNm6YxY8acs81nn32mdevWaf78+c1mV7xer3bs2KG0tDQlJycrPj5e8+bNU0lJifLy8iRJpaWlOnDggObMmSO32y23263Zs2dr//79OnbsmCTpww8/VGlpqebNm6f4+HglJycrLS1N27dvl9frbetpAQAAC2r3ezxNTU1avXq1pkyZori4uGb7CwsL1djYqOTkZHNbZGSkXC6XCgoKlJKSooKCAjmdTiUmJppt3G63nE6n8vPzFRMTo4KCArlcLkVGRppthg8fLp/Pp8LCQiUlJTV7b5/PJ5/PZ7622Wzq1auX+XNXdXrsXfkcrIJaBA5qETioRfcTSLVu96CzefNmBQUF6YYbbmhxf3V1tex2u0JDQ/22h4WFqbq62mwTFhbW7NjztQkNDZXdbjfbnC03N1ebNm0yX8fHx2vFihUaMGBAK88usEVFRXX2EPAv1CJwUIvAQS1a56POHkA7iI6O7uwhmNo16BQWFmrr1q1asWJFm9OcYRitanNmvy29x9ltzpSamqrJkyc3O76iokINDQ1tGm8gsdlsioqKUnl5eauuIzoOtQgc1CJwUIvup6ysrEP7t9vtrZ6kaNeg8/e//101NTW67777zG1NTU164YUXtHXrVv3iF79QeHi4Ghoa5PF4/GZ1ampqNHToUElSeHi4Tpw40az/mpoacxYnPDxcR48e9dvv8XjU2NjY4myQJDkcDjkcjhb3WeEvn2EYljgPK6AWgYNaBA5q0X0EUp3bNehcffXVuvzyy/22LV26VFdffbWuueYaSVJCQoKCgoKUl5enq666SpJUVVWlkpIS3XnnnZJOrcfxer06evSohgwZIkk6cuSIvF6vGYbcbrdef/11VVVVmd/sysvLk8PhUEJCQnueFgAA6KLaHHRqa2tVXl5uvj5+/LiKi4sVGhqq/v37q0+fPv5vYLcrPDxcMTExkiSn06mJEycqJydHffr0UWhoqHJycuRyucwFyrGxsUpJSdGaNWs0a9YsSaeeyTNy5Eizn+HDhys2NlZPPfWUpk+fLo/Ho5ycHF177bVyOp1f7moAAABLaXPQ+cc//qHFixebr08/t2b8+PGaO3duq/qYMWOGgoKCtHLlSvOBgQsWLFCPHv/+tvv8+fO1bt06LV26VJI0atQoZWRkmPt79Oihhx56SGvXrtUjjzyi4OBgjRs3TnfddVdbTwkAAFiUzQikG2mdpKKiwu9r512NzWZTdHS0ysrKAuq+aHdELQIHtQgc1KJtGmdN6ewhfGVBz27p0P4dDkerFyPzu64AAIBlEXQAAIBlEXQAAIBlEXQAAIBlEXQAAIBlEXQAAIBlEXQAAIBlEXQAAIBlEXQAAIBlEXQAAIBlEXQAAIBlEXQAAIBlEXQAAIBlEXQAAIBlEXQAAIBlEXQAAIBlEXQAAIBlEXQAAIBlEXQAAIBlEXQAAIBlEXQAAIBlEXQAAIBlEXQAAIBlEXQAAIBlEXQAAIBlEXQAAIBlEXQAAIBlEXQAAIBlEXQAAIBlEXQAAIBl2dt6wOHDh7VlyxYVFRWpqqpKDzzwgK644gpJUkNDg15++WX99a9/1fHjx+V0OnX55ZfrjjvuUGRkpNmHz+dTTk6Odu3apfr6eiUlJWnmzJnq16+f2cbj8Wj9+vXau3evJGn06NFKT09X7969zTaVlZVau3atDh06pODgYI0dO1ZpaWmy29t8WgAAwILaPKNTV1enwYMHKz09vdm++vp6FRUV6ZZbbtGKFSv0//7f/1NZWZkee+wxv3YbNmzQnj17lJmZqezsbNXW1mr58uVqamoy26xatUrFxcXKyspSVlaWiouLtXr1anN/U1OTli1bprq6OmVnZyszM1MffPCBXnjhhbaeEgAAsKg2B50RI0Zo2rRpGjNmTLN9TqdTjzzyiK666irFxMTI7XbrnnvuUWFhoSorKyVJXq9XO3bsUFpampKTkxUfH6958+appKREeXl5kqTS0lIdOHBAc+bMkdvtltvt1uzZs7V//34dO3ZMkvThhx+qtLRU8+bNU3x8vJKTk5WWlqbt27fL6/V+lWsCAAAsosPv8Xi9XtlsNjmdTklSYWGhGhsblZycbLaJjIyUy+VSQUGBUlJSVFBQIKfTqcTERLON2+2W0+lUfn6+YmJiVFBQIJfL5XdLbPjw4fL5fCosLFRSUlKzsfh8Pvl8PvO1zWZTr169zJ+7qtNj78rnYBXUInBQi8BBLbqfQKp1hwad+vp6vfjiixo7dqwZdKqrq2W32xUaGurXNiwsTNXV1WabsLCwZv2dr01oaKjsdrvZ5my5ubnatGmT+To+Pl4rVqzQgAEDvuQZBpaoqKjOHgL+hVoEDmoROKhF63zU2QNoB9HR0Z09BFOHBZ2GhgY9+eSTMgxDM2fOPG97wzBa1ebMlNhSYjy7zZlSU1M1efLkZsdXVFSooaHhvO8fqGw2m6KiolReXt6q64iOQy0CB7UIHNSi+ykrK+vQ/u12e6snKTok6DQ0NGjlypWqqKjQo48+as7mSFJ4eLgaGhrk8Xj8ZnVqamo0dOhQs82JEyea9VtTU2PO4oSHh+vo0aN++z0ejxobG1ucDZIkh8Mhh8PR4j4r/OUzDMMS52EF1CJwUIvAQS26j0Cqc7s/R+d0yCkvL9cjjzyiPn36+O1PSEhQUFCQufBYkqqqqlRSUiK32y3p1Hocr9frF2SOHDkir9drhiG3262SkhJVVVWZbfLy8uRwOJSQkNDepwUAALqgNs/o1NbWqry83Hx9/PhxFRcXKzQ0VBEREXriiSdUVFSkBQsWqKmpyVwvc3r9jNPp1MSJE5WTk6M+ffooNDRUOTk5crlc5gLl2NhYpaSkaM2aNZo1a5Yk6ZlnntHIkSMVExMj6dTC49jYWD311FOaPn26PB6PcnJydO211/rNIAEAgO7LZrRxfunQoUNavHhxs+3jx4/Xf/3Xf+n+++9v8biFCxfqsssuk3RqkfLGjRu1c+dOvwcG9u/f32zv8Xi0bt067du3T5I0atQoZWRktPjAwIMHDyo4OFjjxo3TXXfddc7bU+dSUVHh922srsZmsyk6OlplZWUBNV3YHVGLwEEtAge1aJvGWVM6ewhfWdCzWzq0f4fD0eo1Om0OOlZE0EF7oRaBg1oEDmrRNgSd82tL0OF3XQEAAMsi6AAAAMsi6AAAAMsi6AAAAMsi6AAAAMsi6AAAAMsi6AAAAMsi6AAAAMvqsN9ejn+7EA9/+qiD++/ohz8BANARmNEBAACWRdABAACWRdABAACWRdABAACWRdABAACWRdABAACWRdABAACWRdABAACWRdABAACWRdABAACWRdABAACWRdABAACWRdABAACWRdABAACWRdABAACWRdABAACWRdABAACWRdABAACWRdABAACWRdABAACWRdABAACWZW/rAYcPH9aWLVtUVFSkqqoqPfDAA7riiivM/YZh6LXXXtP27dvl8XiUmJiojIwMxcXFmW18Pp9ycnK0a9cu1dfXKykpSTNnzlS/fv3MNh6PR+vXr9fevXslSaNHj1Z6erp69+5ttqmsrNTatWt16NAhBQcHa+zYsUpLS5Pd3ubTAgAAFtTmGZ26ujoNHjxY6enpLe7fvHmz3nrrLaWnp2vZsmUKDw/XkiVLdPLkSbPNhg0btGfPHmVmZio7O1u1tbVavny5mpqazDarVq1ScXGxsrKylJWVpeLiYq1evdrc39TUpGXLlqmurk7Z2dnKzMzUBx98oBdeeKGtpwQAACyqzUFnxIgRmjZtmsaMGdNsn2EY2rp1q1JTUzVmzBi5XC7NnTtXdXV12rlzpyTJ6/Vqx44dSktLU3JysuLj4zVv3jyVlJQoLy9PklRaWqoDBw5ozpw5crvdcrvdmj17tvbv369jx45Jkj788EOVlpZq3rx5io+PV3JystLS0rR9+3Z5vd6vck0AAIBFtOs9nuPHj6u6ulrDhw83tzkcDg0bNkz5+fmaNGmSCgsL1djYqOTkZLNNZGSkXC6XCgoKlJKSooKCAjmdTiUmJppt3G63nE6n8vPzFRMTo4KCArlcLkVGRppthg8fLp/Pp8LCQiUlJTUbn8/nk8/nM1/bbDb16tXL/BnnxvVpndPXievV+ahF4KAW3U8g1bpdg051dbUkKSwszG97WFiYKisrzTZ2u12hoaHN2pw+vrq6ulkfrWkTGhoqu91utjlbbm6uNm3aZL6Oj4/XihUrNGDAgNae4pfyUYf2fmFER0d39hC6lKioqM4eAv6FWgQOatE6fGa0rw5ZtXt2kjMM47zHtLbNmX23lBjPbnOm1NRUTZ48udnxFRUVamhoOO/7d2dlZWWdPYQuwWazKSoqSuXl5a36M42OQy0CB7Xofjr6M8Nut7d6kqJdg054eLikU7MtERER5vaamhpz9iU8PFwNDQ3yeDx+szo1NTUaOnSo2ebEiRPN+j+7n6NHj/rt93g8amxsbHE2SDp1G83hcLS4j798X4zr0zaGYXDNAgS1CBzUovsIpDq363N0Bg4cqPDwcHNRsSQ1NDTo8OHDZohJSEhQUFCQX5uqqiqVlJTI7XZLOrUex+v1+gWZI0eOyOv1mv243W6VlJSoqqrKbJOXlyeHw6GEhIT2PC0AANBFtXlGp7a2VuXl5ebr48ePq7i4WKGhoerfv79uvPFG5ebmKjo6WlFRUcrNzVVISIjGjRsnSXI6nZo4caJycnLUp08fhYaGKicnRy6Xy1ygHBsbq5SUFK1Zs0azZs2SJD3zzDMaOXKkYmJiJJ1aeBwbG6unnnpK06dPl8fjUU5Ojq699lo5nc6vfGEAAEDXZzPaOL906NAhLV68uNn28ePHa+7cueYDA9977z19/vnnGjJkiDIyMuRyucy29fX12rhxo3bu3On3wMD+/fubbTwej9atW6d9+/ZJkkaNGqWMjIwWHxh48OBBBQcHa9y4cbrrrrvOeXvqXCoqKvy+jdXeGmdN6bC+L5SgZ7d09hC6BJvNpujoaJWVlQXU1G13RC0CB7VoGz4zzs/hcLR6jU6bg44VEXTOj6DTOvyDHjioReCgFm3DZ8b5tSXo8LuuAACAZRF0AACAZRF0AACAZRF0AACAZRF0AACAZRF0AACAZRF0AACAZRF0AACAZRF0AACAZRF0AACAZRF0AACAZRF0AACAZRF0AACAZRF0AACAZRF0AACAZRF0AACAZRF0AACAZRF0AACAZRF0AACAZRF0AACAZRF0AACAZRF0AACAZRF0AACAZRF0AACAZRF0AACAZRF0AACAZRF0AACAZRF0AACAZRF0AACAZRF0AACAZRF0AACAZdnbu8PGxka99tpr+uMf/6jq6mpFRERowoQJ+va3v60ePU7lKsMw9Nprr2n79u3yeDxKTExURkaG4uLizH58Pp9ycnK0a9cu1dfXKykpSTNnzlS/fv3MNh6PR+vXr9fevXslSaNHj1Z6erp69+7d3qcFAAC6oHaf0dm8ebO2bdumjIwMrVy5UtOnT9eWLVv09ttv+7V56623lJ6ermXLlik8PFxLlizRyZMnzTYbNmzQnj17lJmZqezsbNXW1mr58uVqamoy26xatUrFxcXKyspSVlaWiouLtXr16vY+JQAA0EW1e9ApKCjQ6NGjNXLkSA0cOFBXXnmlkpOT9Y9//EPSqdmcrVu3KjU1VWPGjJHL5dLcuXNVV1ennTt3SpK8Xq927NihtLQ0JScnKz4+XvPmzVNJSYny8vIkSaWlpTpw4IDmzJkjt9stt9ut2bNna//+/Tp27Fh7nxYAAOiC2v3W1SWXXKJt27bp2LFjiomJUXFxsfLz8zVjxgxJ0vHjx1VdXa3hw4ebxzgcDg0bNkz5+fmaNGmSCgsL1djYqOTkZLNNZGSkXC6XCgoKlJKSooKCAjmdTiUmJppt3G63nE6n8vPzFRMT02xsPp9PPp/PfG2z2dSrVy/zZ5wb16d1Tl8nrlfnoxaBg1p0P4FU63YPOlOnTpXX69X3vvc99ejRQ01NTZo2bZrGjRsnSaqurpYkhYWF+R0XFhamyspKs43dbldoaGizNqePr66ubtbH2W3Olpubq02bNpmv4+PjtWLFCg0YMODLnGqrfdShvV8Y0dHRnT2ELiUqKqqzh4B/oRaBg1q0Dp8Z7avdg87u3bv1xz/+UfPnz1dcXJyKi4u1YcMGc1HyaWenPcMwztt3a9ucK0mmpqZq8uTJzcZQUVGhhoaG8/bdnZWVlXX2ELoEm82mqKgolZeXt+rPKzoOtQgc1KL76ejPDLvd3upJinYPOhs3btTUqVM1duxYSZLL5VJFRYXeeOMNTZgwQeHh4ZJkfiPrtJqaGnOGJjw8XA0NDfJ4PH6zOjU1NRo6dKjZ5sSJE83e/8x+zuZwOORwOFrcx1++L8b1aRvDMLhmAYJaBA5q0X0EUp3bfTFyXV2d+TVy80169DBPeuDAgQoPDzcXFUtSQ0ODDh8+bIaYhIQEBQUF+bWpqqpSSUmJ3G63pFPrcbxer44ePWq2OXLkiLxer9kPAADo3tp9RmfUqFF6/fXX1b9/f8XGxqq4uFhvvvmmrrnmGkmnpjBvvPFG5ebmKjo6WlFRUcrNzVVISIi5jsfpdGrixInKyclRnz59FBoaqpycHLlcLnOBcmxsrFJSUrRmzRrNmjVLkvTMM89o5MiRLS5EBgAA3U+7B5309HS98sorWrt2rU6cOKHIyEhNmjRJt956q9lm6tSpqq+v19q1a/X5559ryJAhysrKMr8BJUkzZsxQUFCQVq5caT4wcMGCBX6zRfPnz9e6deu0dOlSSadCVkZGRnufEgAA6KJsRiDdSOskFRUVfl87b2+Ns6Z0WN8XStCzWzp7CF2CzWZTdHS0ysrKAuoedXdELQIHtWgbPjPOz+FwtHoxMr/rCgAAWBZBBwAAWBZBBwAAWBZBBwAAWBZBBwAAWBZBBwAAWBZBBwAAWBZBBwAAWBZBBwAAWBZBBwAAWBZBBwAAWBZBBwAAWBZBBwAAWBZBBwAAWBZBBwAAWBZBBwAAWBZBBwAAWBZBBwAAWBZBBwAAWBZBBwAAWBZBBwAAWBZBBwAAWBZBBwAAWBZBBwAAWBZBBwAAWBZBBwAAWBZBBwAAWBZBBwAAWBZBBwAAWBZBBwAAWJa9Izr97LPPtHHjRh04cED19fWKjo7Wvffeq4SEBEmSYRh67bXXtH37dnk8HiUmJiojI0NxcXFmHz6fTzk5Odq1a5fq6+uVlJSkmTNnql+/fmYbj8ej9evXa+/evZKk0aNHKz09Xb179+6I0wIAAF1Mu8/oeDwePfLII7Lb7frRj36kJ554QmlpaXI6nWabzZs366233lJ6erqWLVum8PBwLVmyRCdPnjTbbNiwQXv27FFmZqays7NVW1ur5cuXq6mpyWyzatUqFRcXKysrS1lZWSouLtbq1avb+5QAAEAX1e5BZ/PmzerXr5/uu+8+DRkyRAMHDtTll1+uqKgoSadmc7Zu3arU1FSNGTNGLpdLc+fOVV1dnXbu3ClJ8nq92rFjh9LS0pScnKz4+HjNmzdPJSUlysvLkySVlpbqwIEDmjNnjtxut9xut2bPnq39+/fr2LFj7X1aAACgC2r3W1d79+7V8OHD9cQTT+jw4cOKjIzUddddp29+85uSpOPHj6u6ulrDhw83j3E4HBo2bJjy8/M1adIkFRYWqrGxUcnJyWabyMhIuVwuFRQUKCUlRQUFBXI6nUpMTDTbuN1uOZ1O5efnKyYmptnYfD6ffD6f+dpms6lXr17mzzg3rk/rnL5OXK/ORy0CB7XofgKp1u0edI4fP65t27bppptuUmpqqo4ePar169fL4XBo/Pjxqq6uliSFhYX5HRcWFqbKykpJUnV1tex2u0JDQ5u1OX18dXV1sz7ObnO23Nxcbdq0yXwdHx+vFStWaMCAAV/ybFvnow7t/cKIjo7u7CF0KadnMNH5qEXgoBatw2dG+2r3oNPU1KSLL75Yd9xxh6RTYeKjjz7Su+++q/Hjx5vtzk57hmGct+/WtjlXkkxNTdXkyZObjaGiokINDQ3n7bs7Kysr6+whdAk2m01RUVEqLy9v1Z9XdBxqETioRffT0Z8Zdru91ZMU7R50IiIiFBsb67ctNjZWH3zwgSQpPDxc0qkZmYiICLNNTU2NOUMTHh6uhoYGeTwev1mdmpoaDR061Gxz4sSJZu9/Zj9nczgccjgcLe7jL98X4/q0jWEYXLMAQS0CB7XoPgKpzu2+GHno0KHNFgMfO3bMTF4DBw5UeHi4uahYkhoaGnT48GEzxCQkJCgoKMivTVVVlUpKSuR2uyWdWo/j9Xp19OhRs82RI0fk9XrNfgAAQPfW7kHnpptu0pEjR/T666+rvLxcO3fu1Pbt23X99ddLOjWFeeONNyo3N1d79uxRSUmJfvGLXygkJETjxo2TJDmdTk2cOFE5OTn629/+pqKiIq1evVoul8tcoBwbG6uUlBStWbNGBQUFKigo0Jo1azRy5MgWFyIDAIDup91vXQ0ZMkQPPPCAXnzxRf3617/WwIEDNWPGDH3jG98w20ydOlX19fVau3atPv/8cw0ZMkRZWVnmN6AkacaMGQoKCtLKlSvNBwYuWLBAPXr8O5vNnz9f69at09KlSyVJo0aNUkZGRnufEgAA6KJsRiDdSOskFRUVfl87b2+Ns6Z0WN8XStCzWzp7CF2CzWZTdHS0ysrKAuoedXdELQIHtWgbPjPOz+FwtHoxMr/rCgAAWBZBBwAAWBZBBwAAWBZBBwAAWBZBBwAAWBZBBwAAWBZBBwAAWBZBBwAAWBZBBwAAWBZBBwAAWBZBBwAAWBZBBwAAWBZBBwAAWBZBBwAAWBZBBwAAWBZBBwAAWBZBBwAAWBZBBwAAWBZBBwAAWBZBBwAAWBZBBwAAWBZBBwAAWBZBBwAAWBZBBwAAWBZBBwAAWBZBBwAAWBZBBwAAWBZBBwAAWBZBBwAAWBZBBwAAWBZBBwAAWJa9o98gNzdXL730km688UbdfffdkiTDMPTaa69p+/bt8ng8SkxMVEZGhuLi4szjfD6fcnJytGvXLtXX1yspKUkzZ85Uv379zDYej0fr16/X3r17JUmjR49Wenq6evfu3dGnBQAAuoAOndE5evSo3nvvPV100UV+2zdv3qy33npL6enpWrZsmcLDw7VkyRKdPHnSbLNhwwbt2bNHmZmZys7OVm1trZYvX66mpiazzapVq1RcXKysrCxlZWWpuLhYq1ev7shTAgAAXUiHBZ3a2lqtXr1as2fP9pthMQxDW7duVWpqqsaMGSOXy6W5c+eqrq5OO3fulCR5vV7t2LFDaWlpSk5OVnx8vObNm6eSkhLl5eVJkkpLS3XgwAHNmTNHbrdbbrdbs2fP1v79+3Xs2LGOOi0AANCFdNitq7Vr12rEiBFKTk7W66+/bm4/fvy4qqurNXz4cHObw+HQsGHDlJ+fr0mTJqmwsFCNjY1KTk4220RGRsrlcqmgoEApKSkqKCiQ0+lUYmKi2cbtdsvpdCo/P18xMTHNxuTz+eTz+czXNptNvXr1Mn/GuXF9Wuf0deJ6dT5qETioRfcTSLXukKCza9cuFRUVadmyZc32VVdXS5LCwsL8toeFhamystJsY7fbFRoa2qzN6eOrq6ub9XF2m7Pl5uZq06ZN5uv4+HitWLFCAwYMaO2pfSkfdWjvF0Z0dHRnD6FLiYqK6uwh4F+oReCgFq3DZ0b7avegU1lZqQ0bNigrK0vBwcHnbHd22jMM47x9t7bNuZJkamqqJk+e3GwMFRUVamhoOG/f3VlZWVlnD6FLsNlsioqKUnl5eav+vKLjUIvAQS26n47+zLDb7a2epGj3oFNYWKgTJ07ohz/8obmtqalJf//73/X222/rySeflHRqRiYiIsJsU1NTY87QhIeHq6GhQR6Px29Wp6amRkOHDjXbnDhxotn7n9nP2RwOhxwOR4v7+Mv3xbg+bWMYBtcsQFCLwEEtuo9AqnO7B53LL79cjz/+uN+2X/7yl4qJidHUqVP1ta99TeHh4crLy1N8fLwkqaGhQYcPH9add94pSUpISFBQUJDy8vJ01VVXSZKqqqpUUlJitnG73fJ6vTp69KiGDBkiSTpy5Ii8Xq8ZhgAAQPfW7kGnV69ecrlcfttCQkLUp08fc/uNN96o3NxcRUdHKyoqSrm5uQoJCdG4ceMkSU6nUxMnTlROTo769Omj0NBQ5eTkyOVymQuUY2NjlZKSojVr1mjWrFmSpGeeeUYjR45scSEyAADofjr8gYEtmTp1qurr67V27Vp9/vnnGjJkiLKyssxvQEnSjBkzFBQUpJUrV5oPDFywYIF69Pj3N+Lnz5+vdevWaenSpZKkUaNGKSMj44KfDwAACEw2I5BupHWSiooKv6+dt7fGWVM6rO8LJejZLZ09hC7BZrMpOjpaZWVlAXWPujuiFoGDWrQNnxnn53A4Wr0Ymd91BQAALKtTbl0BAALHhZhBuBDPhmHmGS1hRgcAAFgWQQcAAFgWQQcAAFgWQQcAAFgWQQcAAFgWQQcAAFgWQQcAAFgWQQcAAFgWQQcAAFgWQQcAAFgWQQcAAFgWQQcAAFgWv9QTQKfgF0kCuBCY0QEAAJZF0AEAAJZF0AEAAJZF0AEAAJZF0AEAAJZF0AEAAJZF0AEAAJZF0AEAAJZF0AEAAJZF0AEAAJZF0AEAAJZF0AEAAJZF0AEAAJZF0AEAAJZF0AEAAJZlb+8Oc3NztWfPHn388ccKDg6W2+3W9OnTFRMTY7YxDEOvvfaatm/fLo/Ho8TERGVkZCguLs5s4/P5lJOTo127dqm+vl5JSUmaOXOm+vXrZ7bxeDxav3699u7dK0kaPXq00tPT1bt37/Y+LQAA0AW1+4zO4cOHdf3112vp0qV6+OGH1dTUpCVLlqi2ttZss3nzZr311ltKT0/XsmXLFB4eriVLlujkyZNmmw0bNmjPnj3KzMxUdna2amtrtXz5cjU1NZltVq1apeLiYmVlZSkrK0vFxcVavXp1e58SAADootp9RicrK8vv9X333aeZM2eqsLBQw4YNk2EY2rp1q1JTUzVmzBhJ0ty5czVr1izt3LlTkyZNktfr1Y4dOzRv3jwlJydLkubNm6d7771XeXl5SklJUWlpqQ4cOKClS5cqMTFRkjR79mw9/PDDOnbsmN8MEnBa46wpHf4eH3X4O0hBz265AO8CAF1fuweds3m9XklSaGioJOn48eOqrq7W8OHDzTYOh0PDhg1Tfn6+Jk2apMLCQjU2NpohR5IiIyPlcrlUUFCglJQUFRQUyOl0miFHktxut5xOp/Lz81sMOj6fTz6fz3xts9nUq1cv82ecG9cnsFCPwEEtAge1CByBVIsODTqGYej555/XJZdcIpfLJUmqrq6WJIWFhfm1DQsLU2VlpdnGbreb4ejMNqePr66ubtbH2W3Olpubq02bNpmv4+PjtWLFCg0YMODLnF6rXYj/w+9o0dHRnT2EdmGFWkjWqAe1CBzUIrBYoR6BVIsODTrPPfecSkpKlJ2d3Wzf2WnPMIzz9tfaNudKkqmpqZo8eXKzMVRUVKihoeG8fXdnZWVlnT0EnIF6BA5qETioReDo6FrY7fZWT1J0WNBZt26d9u3bp8WLF/t9Uyo8PFzSqRmZiIgIc3tNTY05QxMeHq6GhgZ5PB6/WZ2amhoNHTrUbHPixIlm73tmP2dzOBxyOBwt7mtNiOrOuD6BhXoEDmoROKhF4AikWrT7t64Mw9Bzzz2nDz74QI8++qgGDhzot3/gwIEKDw9XXl6eua2hoUGHDx82Q0xCQoKCgoL82lRVVamkpERut1vSqfU4Xq9XR48eNdscOXJEXq/X7AcAAHRv7T6j89xzz2nnzp36wQ9+oF69epnrZZxOp4KDg2Wz2XTjjTcqNzdX0dHRioqKUm5urkJCQjRu3Diz7cSJE5WTk6M+ffooNDRUOTk5crlc5gLl2NhYpaSkaM2aNZo1a5Yk6ZlnntHIkSP5xhUAAJDUAUHn3XfflSQtWrTIb/t9992nCRMmSJKmTp2q+vp6rV27Vp9//rmGDBmirKws8xtQkjRjxgwFBQVp5cqV5gMDFyxYoB49/j0JNX/+fK1bt05Lly6VJI0aNUoZGRntfUoAAKCLaveg8+qrr563jc1m02233abbbrvtnG2Cg4OVnp6u9PT0c7YJDQ3V/Pnzv9Q4AQCA9fG7rgAAgGURdAAAgGURdAAAgGURdAAAgGURdAAAgGURdAAAgGURdAAAgGURdAAAgGURdAAAgGURdAAAgGURdAAAgGURdAAAgGURdAAAgGURdAAAgGURdAAAgGURdAAAgGURdAAAgGURdAAAgGURdAAAgGURdAAAgGURdAAAgGURdAAAgGURdAAAgGURdAAAgGURdAAAgGURdAAAgGURdAAAgGURdAAAgGURdAAAgGURdAAAgGXZO3sAX9U777yjLVu2qLq6WrGxsbr77rt16aWXdvawAABAAOjSMzq7d+/Whg0b9O1vf1srVqzQpZdeqp/85CeqrKzs7KEBAIAA0KWDzptvvqmJEyfq2muvNWdz+vfvr3fffbezhwYAAAJAl7111dDQoMLCQt18881+25OTk5Wfn9/iMT6fTz6fz3xts9nUq1cv2e0dexl6XDy0Q/u/EIIcjs4eQruwQi0ka9SDWgQOahFYrFCPjq5FWz63u2zQqampUVNTk8LCwvy2h4WFqbq6usVjcnNztWnTJvP12LFjlZmZqYiIiI4cqrTqVx3bP1qPWgQOahE4qEVgoR7tqkvfupJOzcq0ZpskpaamasOGDeZ/s2bN8pvh6apOnjypBQsW6OTJk509lG6PWgQOahE4qEXg6I616LIzOn379lWPHj2azd6cOHGi2SzPaQ6HQw6LTG2eyTAMFRUVyTCMzh5Kt0ctAge1CBzUInB0x1p02Rkdu92uhIQE5eXl+W3Py8vT0KFd//4mAAD46rrsjI4kTZ48WatXr1ZCQoLcbrfee+89VVZWatKkSZ09NAAAEAC6dNC56qqr9H//93/69a9/raqqKsXFxemhhx7SgAEDOntoF5TD4dCtt95qydtyXQ21CBzUInBQi8DRHWthM7rTjToAANCtdNk1OgAAAOdD0AEAAJZF0AEAAJZF0AEAAJZF0AEAAJZF0AEAdDi+4IvOQtABAHS4O+64Q6WlpZ09DHRDXfqBgWiusrJSr776qu67777OHkq3UF9fr8LCQoWGhio2NrbZvj/96U8aP358J42ueyktLdWRI0fkdrs1aNAgffzxx9q6dat8Pp+uvvpqJSUldfYQu4Xnn3++xe1NTU1644031KdPH0nSjBkzLuSw8C8ej0e///3vVVZWpoiICI0fP179+/fv7GF1KIKOxZz+Q0zQ6XjHjh3T0qVLVVlZKUm69NJLlZmZqYiICEmS1+vV008/TdC5AA4cOKDHHntMPXv2VF1dnR588EE99dRTuuiiiyRJS5cuVVZWFmHnAti6dasuuugi9e7du9m+jz/+WD179uyEUXVfs2fP1uOPP64+ffro+PHjevjhhyVJLpdL+/bt029+8xstXbpUgwYN6uSRdhyCThezd+/eL9z/ySefXKCR4Fe/+pXi4uK0bNkyeb1ePf/883rkkUe0aNEiy/8fUqDZtGmTpkyZomnTpmnXrl36+c9/ruuuu07f+c53JEkvvfSS3njjDYLOBTBt2jRt375daWlpftf7O9/5jubOndts5hMdq7q6Wk1NTZKkF198UYMGDdIPf/hDhYSEyOfz6Wc/+5leeeUVff/73+/kkXYcgk4X89Of/rSzh4B/KSgo0COPPKK+ffuqb9++WrBggdauXatHH31UCxcuVEhISGcPsdv46KOPdP/990uSvv71r+upp57SmDFjzP1jx47Vjh07Omt43Upqaqouv/xyrV69WqNGjdIdd9whu52PmkBw9OhRzZkzx/y3yeFw6JZbbtETTzzRySPrWPzp62LCw8OVkZGhK664osX9xcXFWrBgwQUeVfdUX1+vHj381/PPnDlT69at06JFizR//vxOGln31qNHDzkcDr9bJ7169ZLX6+3EUXUvQ4YM0YoVK7R27Vo99NBDmjdvXmcPqVuz2WySJJ/Pp7CwML99YWFhqqmp6YxhXTAEnS4mISFBRUVF5ww6uHBiYmJUWFjYbCo+PT1dhmHoscce66SRdT8DBw5UeXm5oqKiJElLlizxu3346aefmmuncGH07NlT999/v3bt2qUf//jH5u0TXHjZ2dkKCgrSyZMnVVZWpri4OHNfZWWluUDcqgg6XcyUKVNUV1d3zv1RUVFauHDhBRxR93XFFVdo165duvrqq5vty8jIkGEY2rZtWyeMrPuZNGmS3wepy+Xy2//Xv/6V9TmdZOzYsbrkkktUWFjI2rVOcOutt/q9Dg4O9nu9b98+XXLJJRdySBeczeApTgAAwKJ4YCAAALAsgg4AALAsgg4AALAsgg4AALAsgg4AALAsgg4AALAsgg4AALCs/w+YPg2oXHjgrAAAAABJRU5ErkJggg==",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "df['rating'].value_counts().sort_index().plot(kind='bar',title = 'count for ratings')\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "47633164",
   "metadata": {
    "papermill": {
     "duration": 0.010601,
     "end_time": "2023-08-10T07:34:38.450700",
     "exception": false,
     "start_time": "2023-08-10T07:34:38.440099",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "# step2: Basic NLTK"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "12e51ed6",
   "metadata": {
    "papermill": {
     "duration": 0.010522,
     "end_time": "2023-08-10T07:34:38.472708",
     "exception": false,
     "start_time": "2023-08-10T07:34:38.462186",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "## example1:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "ef38d9b4",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-08-10T07:34:38.497592Z",
     "iopub.status.busy": "2023-08-10T07:34:38.496381Z",
     "iopub.status.idle": "2023-08-10T07:34:38.503489Z",
     "shell.execute_reply": "2023-08-10T07:34:38.502511Z"
    },
    "papermill": {
     "duration": 0.022414,
     "end_time": "2023-08-10T07:34:38.505911",
     "exception": false,
     "start_time": "2023-08-10T07:34:38.483497",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'Super intuitive and easily portable from Instagram etc. I enjoy it I just always forget to use the damn thing after the influx when it debuted!'"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "example = df['review_description'][55]\n",
    "example"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "1314e27f",
   "metadata": {
    "papermill": {
     "duration": 0.010816,
     "end_time": "2023-08-10T07:34:38.527833",
     "exception": false,
     "start_time": "2023-08-10T07:34:38.517017",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "### 1. tokeniser"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "7ca44ec3",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-08-10T07:34:38.552255Z",
     "iopub.status.busy": "2023-08-10T07:34:38.551811Z",
     "iopub.status.idle": "2023-08-10T07:34:38.573443Z",
     "shell.execute_reply": "2023-08-10T07:34:38.572466Z"
    },
    "papermill": {
     "duration": 0.036603,
     "end_time": "2023-08-10T07:34:38.575956",
     "exception": false,
     "start_time": "2023-08-10T07:34:38.539353",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "token = nltk.word_tokenize(example)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5d56b42f",
   "metadata": {
    "papermill": {
     "duration": 0.010751,
     "end_time": "2023-08-10T07:34:38.597728",
     "exception": false,
     "start_time": "2023-08-10T07:34:38.586977",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "### 2. part of speech tagging\n",
    " grammatical tagging : it will simply tag the related part of speech as an abvreviation."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "36ff385c",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-08-10T07:34:38.621903Z",
     "iopub.status.busy": "2023-08-10T07:34:38.621193Z",
     "iopub.status.idle": "2023-08-10T07:34:38.780788Z",
     "shell.execute_reply": "2023-08-10T07:34:38.779742Z"
    },
    "papermill": {
     "duration": 0.17489,
     "end_time": "2023-08-10T07:34:38.783643",
     "exception": false,
     "start_time": "2023-08-10T07:34:38.608753",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "tag = nltk.pos_tag(token)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d81c0e7f",
   "metadata": {
    "papermill": {
     "duration": 0.010681,
     "end_time": "2023-08-10T07:34:38.806235",
     "exception": false,
     "start_time": "2023-08-10T07:34:38.795554",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "### 3. chunk the tagged tokens\n",
    "Use NLTK's currently recommended named entity chunker to chunk the given list of tagged tokens"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "bef26055",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-08-10T07:34:38.831269Z",
     "iopub.status.busy": "2023-08-10T07:34:38.830841Z",
     "iopub.status.idle": "2023-08-10T07:34:39.004301Z",
     "shell.execute_reply": "2023-08-10T07:34:39.002792Z"
    },
    "papermill": {
     "duration": 0.189239,
     "end_time": "2023-08-10T07:34:39.007067",
     "exception": false,
     "start_time": "2023-08-10T07:34:38.817828",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "chunk = nltk.chunk.ne_chunk(tag)\n",
    "# chunk.pprint()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3b71abf7",
   "metadata": {
    "papermill": {
     "duration": 0.011071,
     "end_time": "2023-08-10T07:34:39.029129",
     "exception": false,
     "start_time": "2023-08-10T07:34:39.018058",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "# Step 3. VADER Sentiment Scoring\n",
    "We will use NLTK's `SentimentIntensityAnalyzer` to get the neg/neu/pos scores of the text.\n",
    "\n",
    "This uses a \"bag of words\" approach:\n",
    "Stop words are removed\n",
    "each word is scored and combined to a total score."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "799ca0d2",
   "metadata": {
    "papermill": {
     "duration": 0.010725,
     "end_time": "2023-08-10T07:34:39.050869",
     "exception": false,
     "start_time": "2023-08-10T07:34:39.040144",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "### 1. Create a object of `SentimentIntensityAnalyzer`"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "4dcc4c4b",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-08-10T07:34:39.075605Z",
     "iopub.status.busy": "2023-08-10T07:34:39.075129Z",
     "iopub.status.idle": "2023-08-10T07:34:39.105100Z",
     "shell.execute_reply": "2023-08-10T07:34:39.103665Z"
    },
    "papermill": {
     "duration": 0.045332,
     "end_time": "2023-08-10T07:34:39.107951",
     "exception": false,
     "start_time": "2023-08-10T07:34:39.062619",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "sia = SentimentIntensityAnalyzer()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "ed8443c1",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-08-10T07:34:39.132857Z",
     "iopub.status.busy": "2023-08-10T07:34:39.132393Z",
     "iopub.status.idle": "2023-08-10T07:34:39.141399Z",
     "shell.execute_reply": "2023-08-10T07:34:39.140082Z"
    },
    "papermill": {
     "duration": 0.025086,
     "end_time": "2023-08-10T07:34:39.144169",
     "exception": false,
     "start_time": "2023-08-10T07:34:39.119083",
     "status": "completed"
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    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'neg': 0.138, 'neu': 0.569, 'pos': 0.293, 'compound': 0.7345}"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sia.polarity_scores(example)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "560c8e01",
   "metadata": {
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    "tags": []
   },
   "source": [
    "### 2. Getting `polarity_scores` for all `'review_decription'`"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "d42c9c83",
   "metadata": {
    "execution": {
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     "exception": false,
     "start_time": "2023-08-10T07:34:39.178442",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "a5e2c209563049708c9f2751faf717ba",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "  0%|          | 0/36943 [00:00<?, ?it/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "result = {}\n",
    "for i , rows in tqdm(df.iterrows(),total = len(df)):\n",
    "    text = rows['review_description']\n",
    "    id_ = rows['index']\n",
    "    result[id_] = sia.polarity_scores(text)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "563f9a4d",
   "metadata": {
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     "start_time": "2023-08-10T07:34:51.458897",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "### 3. Result (all polarity score)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "f0970346",
   "metadata": {
    "execution": {
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     "start_time": "2023-08-10T07:34:51.481328",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
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       "      <th></th>\n",
       "      <th>index</th>\n",
       "      <th>neg</th>\n",
       "      <th>neu</th>\n",
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       "      <th>compound</th>\n",
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       "      <th>1</th>\n",
       "      <td>1</td>\n",
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       "      <td>0.808</td>\n",
       "      <td>0.6369</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>4</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.295</td>\n",
       "      <td>0.705</td>\n",
       "      <td>0.3384</td>\n",
       "    </tr>\n",
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       "</table>\n",
       "</div>"
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      "text/plain": [
       "   index    neg    neu    pos  compound\n",
       "0      0  0.000  0.000  1.000    0.4404\n",
       "1      1  0.492  0.508  0.000   -0.4404\n",
       "2      2  0.000  0.532  0.468    0.9201\n",
       "3      3  0.000  0.192  0.808    0.6369\n",
       "4      4  0.000  0.295  0.705    0.3384"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "final = pd.DataFrame(result).T\n",
    "final.head().reset_index()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0daee866",
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     "status": "completed"
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    "tags": []
   },
   "source": [
    "### 4. Concating the result with dataset"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "365f0530",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-08-10T07:34:52.866886Z",
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     "status": "completed"
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    "tags": []
   },
   "outputs": [],
   "source": [
    "final = pd.concat([final,df],axis = 1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "e963d0a3",
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       "     neg    neu    pos  compound  index       source  \\\n",
       "0  0.000  0.000  1.000    0.4404      0  Google Play   \n",
       "1  0.492  0.508  0.000   -0.4404      1  Google Play   \n",
       "2  0.000  0.532  0.468    0.9201      2  Google Play   \n",
       "3  0.000  0.192  0.808    0.6369      3  Google Play   \n",
       "4  0.000  0.295  0.705    0.3384      4  Google Play   \n",
       "\n",
       "                              review_id                   user_name  \\\n",
       "0  7cd90e5b-4829-43b9-9fb4-c8c6d1e339c1             Eddie Clark Jr.   \n",
       "1  6deb8265-2bac-4524-bcb6-f90829fa4e69                     Rasa RT   \n",
       "2  91ef61ce-0f05-4f3b-b3d3-5d19cd408ab8  SITI NUR HAFIZA BINTI AZIZ   \n",
       "3  b7721b78-6b77-4f8c-a1d3-a854af4c1f0f               Asap Khalifah   \n",
       "4  c89ef522-c94c-4171-878f-1d672dce7f11                Syed Hussein   \n",
       "\n",
       "                                  review_description  rating  thumbs_up  \\\n",
       "0                                               Good       5        0.0   \n",
       "1                               Weak copy of Twitter       1        0.0   \n",
       "2  i wish threads have a save button for images a...       3        0.0   \n",
       "3                                            Love it       5        0.0   \n",
       "4                                           Very god       5        0.0   \n",
       "\n",
       "           review_date laguage_code country_code  \n",
       "0  2023-08-07 19:14:36           en           us  \n",
       "1  2023-08-07 19:07:04           en           us  \n",
       "2  2023-08-07 18:57:07           en           us  \n",
       "3  2023-08-07 18:37:16           en           us  \n",
       "4  2023-08-07 18:14:15           en           us  "
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     "execution_count": 18,
     "metadata": {},
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   ],
   "source": [
    "final.head()"
   ]
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       "      <td>Good morning for new opportunities to tweeter</td>\n",
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       "      <td>0.0</td>\n",
       "      <td>2023-07-06 12:05:47</td>\n",
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       "      <td>Better than having to deal with the freaking p...</td>\n",
       "      <td>5</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2023-07-06 20:49:30</td>\n",
       "      <td>en</td>\n",
       "      <td>us</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11005</th>\n",
       "      <td>0.000</td>\n",
       "      <td>1.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>11005</td>\n",
       "      <td>Google Play</td>\n",
       "      <td>8298ca68-2d69-4b52-8249-ef143794f220</td>\n",
       "      <td>Grant whitman</td>\n",
       "      <td>The app was using about 99% of my battery. Del...</td>\n",
       "      <td>1</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2023-07-10 01:54:35</td>\n",
       "      <td>en</td>\n",
       "      <td>us</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>31832</th>\n",
       "      <td>0.000</td>\n",
       "      <td>0.877</td>\n",
       "      <td>0.123</td>\n",
       "      <td>0.2724</td>\n",
       "      <td>31832</td>\n",
       "      <td>Google Play</td>\n",
       "      <td>b34d47b5-a7a3-4ecd-af2f-5aceb10dac61</td>\n",
       "      <td>VIKASH BARAIYA</td>\n",
       "      <td>Very good this app but this app in privacy see...</td>\n",
       "      <td>4</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2023-07-06 13:48:27</td>\n",
       "      <td>en</td>\n",
       "      <td>us</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22928</th>\n",
       "      <td>0.000</td>\n",
       "      <td>0.385</td>\n",
       "      <td>0.615</td>\n",
       "      <td>0.4927</td>\n",
       "      <td>22928</td>\n",
       "      <td>Google Play</td>\n",
       "      <td>14384004-ff40-4c30-8506-5ac16237c6d1</td>\n",
       "      <td>Abdou Belloumi</td>\n",
       "      <td>Very good app</td>\n",
       "      <td>5</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2023-07-07 09:39:27</td>\n",
       "      <td>en</td>\n",
       "      <td>us</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28789</th>\n",
       "      <td>0.000</td>\n",
       "      <td>1.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>28789</td>\n",
       "      <td>Google Play</td>\n",
       "      <td>7a3244bd-0e03-4e38-b4f5-94081b54df8a</td>\n",
       "      <td>pankaj tholia</td>\n",
       "      <td>Thik s le</td>\n",
       "      <td>3</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2023-07-06 19:08:42</td>\n",
       "      <td>en</td>\n",
       "      <td>us</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19793</th>\n",
       "      <td>0.000</td>\n",
       "      <td>0.263</td>\n",
       "      <td>0.737</td>\n",
       "      <td>0.4215</td>\n",
       "      <td>19793</td>\n",
       "      <td>Google Play</td>\n",
       "      <td>7b28e389-c129-4964-9f12-d5c1f4f4ce1d</td>\n",
       "      <td>Haris Kahn</td>\n",
       "      <td>Nice app</td>\n",
       "      <td>5</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2023-07-07 17:55:25</td>\n",
       "      <td>en</td>\n",
       "      <td>us</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "         neg    neu    pos  compound  index       source  \\\n",
       "9199   0.000  0.263  0.737    0.4215   9199  Google Play   \n",
       "32785  0.000  0.913  0.087    0.3182  32785  Google Play   \n",
       "17333  0.000  1.000  0.000    0.0000  17333  Google Play   \n",
       "32635  0.000  0.476  0.524    0.6705  32635  Google Play   \n",
       "35924  0.178  0.637  0.185    0.0258  35924    App Store   \n",
       "11005  0.000  1.000  0.000    0.0000  11005  Google Play   \n",
       "31832  0.000  0.877  0.123    0.2724  31832  Google Play   \n",
       "22928  0.000  0.385  0.615    0.4927  22928  Google Play   \n",
       "28789  0.000  1.000  0.000    0.0000  28789  Google Play   \n",
       "19793  0.000  0.263  0.737    0.4215  19793  Google Play   \n",
       "\n",
       "                                  review_id       user_name  \\\n",
       "9199   25c64078-7989-4d88-9e26-add258a3ff3c      RADHE SONI   \n",
       "32785  08dd890e-b7bc-44d8-a9a6-11adfb839295    Los Kingster   \n",
       "17333  1e314c06-ecd8-496e-960f-4252f1cb3694    Eniola Rufus   \n",
       "32635  5688dc2f-480c-4007-b169-645a4e689190      Faraz Khan   \n",
       "35924  dd909fad-e362-4170-897c-a9dc9c58d719    IDFK!!!!!!!!   \n",
       "11005  8298ca68-2d69-4b52-8249-ef143794f220   Grant whitman   \n",
       "31832  b34d47b5-a7a3-4ecd-af2f-5aceb10dac61  VIKASH BARAIYA   \n",
       "22928  14384004-ff40-4c30-8506-5ac16237c6d1  Abdou Belloumi   \n",
       "28789  7a3244bd-0e03-4e38-b4f5-94081b54df8a   pankaj tholia   \n",
       "19793  7b28e389-c129-4964-9f12-d5c1f4f4ce1d      Haris Kahn   \n",
       "\n",
       "                                      review_description  rating  thumbs_up  \\\n",
       "9199                                            Nice app       5        0.0   \n",
       "32785  App not working all content messing up cluster...       1        4.0   \n",
       "17333                                  Thread 🤘😁🤘 we are       5        0.0   \n",
       "32635      Good morning for new opportunities to tweeter       5        0.0   \n",
       "35924  Better than having to deal with the freaking p...       5        NaN   \n",
       "11005  The app was using about 99% of my battery. Del...       1        0.0   \n",
       "31832  Very good this app but this app in privacy see...       4        0.0   \n",
       "22928                                      Very good app       5        0.0   \n",
       "28789                                          Thik s le       3        0.0   \n",
       "19793                                           Nice app       5        0.0   \n",
       "\n",
       "               review_date laguage_code country_code  \n",
       "9199   2023-07-11 08:41:48           en           us  \n",
       "32785  2023-07-06 11:44:38           en           us  \n",
       "17333  2023-07-08 01:32:55           en           us  \n",
       "32635  2023-07-06 12:05:47           en           us  \n",
       "35924  2023-07-06 20:49:30           en           us  \n",
       "11005  2023-07-10 01:54:35           en           us  \n",
       "31832  2023-07-06 13:48:27           en           us  \n",
       "22928  2023-07-07 09:39:27           en           us  \n",
       "28789  2023-07-06 19:08:42           en           us  \n",
       "19793  2023-07-07 17:55:25           en           us  "
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