using_model.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "b7826f6a",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 1600000 entries, 0 to 1599999\n",
      "Data columns (total 2 columns):\n",
      " #   Column     Non-Null Count    Dtype \n",
      "---  ------     --------------    ----- \n",
      " 0   sentiment  1600000 non-null  int64 \n",
      " 1   text       1600000 non-null  object\n",
      "dtypes: int64(1), object(1)\n",
      "memory usage: 24.4+ MB\n",
      "              precision    recall  f1-score   support\n",
      "\n",
      "           0       0.81      0.79      0.80     80313\n",
      "           2       0.80      0.81      0.80     79687\n",
      "\n",
      "    accuracy                           0.80    160000\n",
      "   macro avg       0.80      0.80      0.80    160000\n",
      "weighted avg       0.80      0.80      0.80    160000\n",
      "\n",
      "              precision    recall  f1-score   support\n",
      "\n",
      "           0       0.82      0.81      0.81     80313\n",
      "           2       0.81      0.82      0.82     79687\n",
      "\n",
      "    accuracy                           0.82    160000\n",
      "   macro avg       0.82      0.82      0.82    160000\n",
      "weighted avg       0.82      0.82      0.82    160000\n",
      "\n",
      "              precision    recall  f1-score   support\n",
      "\n",
      "           0       0.83      0.82      0.83     80313\n",
      "           2       0.82      0.83      0.83     79687\n",
      "\n",
      "    accuracy                           0.83    160000\n",
      "   macro avg       0.83      0.83      0.83    160000\n",
      "weighted avg       0.83      0.83      0.83    160000\n",
      "\n",
      "                                        text sentiment\n",
      "0            Sagar is the best player I know  Positive\n",
      "1  nah, man not the best but yeah he is okay  Negative\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 4 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from ipynb.fs.full.twitter_sentiment_analysis import load_models, predict"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "605b488e",
   "metadata": {},
   "outputs": [],
   "source": [
    "text = ['why is he always doing the same thing?', 'i have never seen anyone run that fast']\n",
    "v, lr = load_models()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9d684161",
   "metadata": {},
   "source": [
    "Import functions predict and load_models from twitter_sentiment_analysis using the above code."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "ea538bd8",
   "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>sentiment</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>why is he always doing the same thing?</td>\n",
       "      <td>Negative</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>i have never seen anyone run that fast</td>\n",
       "      <td>Positive</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                     text sentiment\n",
       "0  why is he always doing the same thing?  Negative\n",
       "1  i have never seen anyone run that fast  Positive"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = predict(v, lr, text)\n",
    "df.head()"
   ]
  }
 ],
 "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": "3.11.0"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}