sms_detector.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "51a4cc4f",
   "metadata": {},
   "outputs": [],
   "source": [
    "pip install pandas"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "99f9df91",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Requirement already satisfied: numpy in c:\\users\\hp\\appdata\\local\\anaconda3\\lib\\site-packages (1.23.5)\n",
      "Note: you may need to restart the kernel to use updated packages.\n"
     ]
    }
   ],
   "source": [
    "pip install numpy"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "d230e0ad",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Requirement already satisfied: nltk in c:\\users\\hp\\appdata\\local\\anaconda3\\lib\\site-packages (3.7)\n",
      "Requirement already satisfied: regex>=2021.8.3 in c:\\users\\hp\\appdata\\local\\anaconda3\\lib\\site-packages (from nltk) (2022.7.9)\n",
      "Requirement already satisfied: click in c:\\users\\hp\\appdata\\local\\anaconda3\\lib\\site-packages (from nltk) (8.0.4)\n",
      "Requirement already satisfied: tqdm in c:\\users\\hp\\appdata\\local\\anaconda3\\lib\\site-packages (from nltk) (4.64.1)\n",
      "Requirement already satisfied: joblib in c:\\users\\hp\\appdata\\local\\anaconda3\\lib\\site-packages (from nltk) (1.1.1)\n",
      "Requirement already satisfied: colorama in c:\\users\\hp\\appdata\\roaming\\python\\python310\\site-packages (from click->nltk) (0.4.6)\n",
      "Note: you may need to restart the kernel to use updated packages.\n"
     ]
    }
   ],
   "source": [
    "pip install nltk"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 79,
   "id": "df92a303",
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "from sklearn.preprocessing import LabelEncoder\n",
    "import pandas as pd\n",
    "import nltk\n",
    "import string\n",
    "from sklearn.feature_extraction.text import CountVectorizer\n",
    "from sklearn import svm\n",
    "from sklearn.model_selection import GridSearchCV"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "5f9d4555",
   "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>Label</th>\n",
       "      <th>EmailText</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>ham</td>\n",
       "      <td>Go until jurong point, crazy.. Available only ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>ham</td>\n",
       "      <td>Ok lar... Joking wif u oni...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>spam</td>\n",
       "      <td>Free entry in 2 a wkly comp to win FA Cup fina...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>ham</td>\n",
       "      <td>U dun say so early hor... U c already then say...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>ham</td>\n",
       "      <td>Nah I don't think he goes to usf, he lives aro...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5567</th>\n",
       "      <td>spam</td>\n",
       "      <td>This is the 2nd time we have tried 2 contact u...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5568</th>\n",
       "      <td>ham</td>\n",
       "      <td>Will Ã_ b going to esplanade fr home?</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5569</th>\n",
       "      <td>ham</td>\n",
       "      <td>Pity, * was in mood for that. So...any other s...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5570</th>\n",
       "      <td>ham</td>\n",
       "      <td>The guy did some bitching but I acted like i'd...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5571</th>\n",
       "      <td>ham</td>\n",
       "      <td>Rofl. Its true to its name</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5572 rows × 2 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     Label                                          EmailText\n",
       "0      ham  Go until jurong point, crazy.. Available only ...\n",
       "1      ham                      Ok lar... Joking wif u oni...\n",
       "2     spam  Free entry in 2 a wkly comp to win FA Cup fina...\n",
       "3      ham  U dun say so early hor... U c already then say...\n",
       "4      ham  Nah I don't think he goes to usf, he lives aro...\n",
       "...    ...                                                ...\n",
       "5567  spam  This is the 2nd time we have tried 2 contact u...\n",
       "5568   ham             Will Ã_ b going to esplanade fr home?\n",
       "5569   ham  Pity, * was in mood for that. So...any other s...\n",
       "5570   ham  The guy did some bitching but I acted like i'd...\n",
       "5571   ham                         Rofl. Its true to its name\n",
       "\n",
       "[5572 rows x 2 columns]"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = pd.read_csv('spam.csv')\n",
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "ec0a0cce",
   "metadata": {},
   "outputs": [],
   "source": [
    "encoder = LabelEncoder()\n",
    "df['Label'] = encoder.fit_transform(df['Label'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "791b914e",
   "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>Label</th>\n",
       "      <th>EmailText</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>ham</td>\n",
       "      <td>Go until jurong point, crazy.. Available only ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>ham</td>\n",
       "      <td>Ok lar... Joking wif u oni...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>spam</td>\n",
       "      <td>Free entry in 2 a wkly comp to win FA Cup fina...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>ham</td>\n",
       "      <td>U dun say so early hor... U c already then say...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>ham</td>\n",
       "      <td>Nah I don't think he goes to usf, he lives aro...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5567</th>\n",
       "      <td>spam</td>\n",
       "      <td>This is the 2nd time we have tried 2 contact u...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5568</th>\n",
       "      <td>ham</td>\n",
       "      <td>Will Ã_ b going to esplanade fr home?</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5569</th>\n",
       "      <td>ham</td>\n",
       "      <td>Pity, * was in mood for that. So...any other s...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5570</th>\n",
       "      <td>ham</td>\n",
       "      <td>The guy did some bitching but I acted like i'd...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5571</th>\n",
       "      <td>ham</td>\n",
       "      <td>Rofl. Its true to its name</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5572 rows × 2 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     Label                                          EmailText\n",
       "0      ham  Go until jurong point, crazy.. Available only ...\n",
       "1      ham                      Ok lar... Joking wif u oni...\n",
       "2     spam  Free entry in 2 a wkly comp to win FA Cup fina...\n",
       "3      ham  U dun say so early hor... U c already then say...\n",
       "4      ham  Nah I don't think he goes to usf, he lives aro...\n",
       "...    ...                                                ...\n",
       "5567  spam  This is the 2nd time we have tried 2 contact u...\n",
       "5568   ham             Will Ã_ b going to esplanade fr home?\n",
       "5569   ham  Pity, * was in mood for that. So...any other s...\n",
       "5570   ham  The guy did some bitching but I acted like i'd...\n",
       "5571   ham                         Rofl. Its true to its name\n",
       "\n",
       "[5572 rows x 2 columns]"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "526f16ed",
   "metadata": {},
   "outputs": [],
   "source": [
    "# removing all the duplicate values and keeping only the first\n",
    "df = df.drop_duplicates(keep='first')\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "6c519407",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(5169, 2)"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "id": "19c22867",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "ham     4516\n",
       "spam     653\n",
       "Name: Label, dtype: int64"
      ]
     },
     "execution_count": 40,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['Label'].value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "id": "c63f3fd4",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "plt.pie(df['Label'].value_counts(), labels=['ham','spam'], autopct='%0.2f')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "id": "c7a38a82",
   "metadata": {},
   "outputs": [],
   "source": [
    "import nltk"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "id": "ba4d742c",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "[nltk_data] Downloading package punkt to\n",
      "[nltk_data]     C:\\Users\\hp\\AppData\\Roaming\\nltk_data...\n",
      "[nltk_data]   Unzipping tokenizers\\punkt.zip.\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "True"
      ]
     },
     "execution_count": 48,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "nltk.download('punkt')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "id": "6dd0b940",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "[nltk_data] Downloading package stopwords to\n",
      "[nltk_data]     C:\\Users\\hp\\AppData\\Roaming\\nltk_data...\n",
      "[nltk_data]   Unzipping corpora\\stopwords.zip.\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "True"
      ]
     },
     "execution_count": 55,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "nltk.download('stopwords')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "id": "741e8af3",
   "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>Label</th>\n",
       "      <th>EmailText</th>\n",
       "      <th>imp_feature</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>ham</td>\n",
       "      <td>Go until jurong point, crazy.. Available only ...</td>\n",
       "      <td>[go, until, jurong, point, crazy, available, o...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>ham</td>\n",
       "      <td>Ok lar... Joking wif u oni...</td>\n",
       "      <td>[ok, lar, joking, wif, u, oni]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>spam</td>\n",
       "      <td>Free entry in 2 a wkly comp to win FA Cup fina...</td>\n",
       "      <td>[free, entry, in, 2, a, wkly, comp, to, win, f...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>ham</td>\n",
       "      <td>U dun say so early hor... U c already then say...</td>\n",
       "      <td>[u, dun, say, so, early, hor, u, c, already, t...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>ham</td>\n",
       "      <td>Nah I don't think he goes to usf, he lives aro...</td>\n",
       "      <td>[nah, i, do, think, he, goes, to, usf, he, liv...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5567</th>\n",
       "      <td>spam</td>\n",
       "      <td>This is the 2nd time we have tried 2 contact u...</td>\n",
       "      <td>[this, is, the, 2nd, time, we, have, tried, 2,...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5568</th>\n",
       "      <td>ham</td>\n",
       "      <td>Will Ã_ b going to esplanade fr home?</td>\n",
       "      <td>[will, b, going, to, esplanade, fr, home]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5569</th>\n",
       "      <td>ham</td>\n",
       "      <td>Pity, * was in mood for that. So...any other s...</td>\n",
       "      <td>[pity, was, in, mood, for, that, so, any, othe...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5570</th>\n",
       "      <td>ham</td>\n",
       "      <td>The guy did some bitching but I acted like i'd...</td>\n",
       "      <td>[the, guy, did, some, bitching, but, i, acted,...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5571</th>\n",
       "      <td>ham</td>\n",
       "      <td>Rofl. Its true to its name</td>\n",
       "      <td>[rofl, its, true, to, its, name]</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5169 rows × 3 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     Label                                          EmailText  \\\n",
       "0      ham  Go until jurong point, crazy.. Available only ...   \n",
       "1      ham                      Ok lar... Joking wif u oni...   \n",
       "2     spam  Free entry in 2 a wkly comp to win FA Cup fina...   \n",
       "3      ham  U dun say so early hor... U c already then say...   \n",
       "4      ham  Nah I don't think he goes to usf, he lives aro...   \n",
       "...    ...                                                ...   \n",
       "5567  spam  This is the 2nd time we have tried 2 contact u...   \n",
       "5568   ham             Will Ã_ b going to esplanade fr home?   \n",
       "5569   ham  Pity, * was in mood for that. So...any other s...   \n",
       "5570   ham  The guy did some bitching but I acted like i'd...   \n",
       "5571   ham                         Rofl. Its true to its name   \n",
       "\n",
       "                                            imp_feature  \n",
       "0     [go, until, jurong, point, crazy, available, o...  \n",
       "1                        [ok, lar, joking, wif, u, oni]  \n",
       "2     [free, entry, in, 2, a, wkly, comp, to, win, f...  \n",
       "3     [u, dun, say, so, early, hor, u, c, already, t...  \n",
       "4     [nah, i, do, think, he, goes, to, usf, he, liv...  \n",
       "...                                                 ...  \n",
       "5567  [this, is, the, 2nd, time, we, have, tried, 2,...  \n",
       "5568          [will, b, going, to, esplanade, fr, home]  \n",
       "5569  [pity, was, in, mood, for, that, so, any, othe...  \n",
       "5570  [the, guy, did, some, bitching, but, i, acted,...  \n",
       "5571                   [rofl, its, true, to, its, name]  \n",
       "\n",
       "[5169 rows x 3 columns]"
      ]
     },
     "execution_count": 56,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "id": "aa737a7a",
   "metadata": {},
   "outputs": [],
   "source": [
    "from nltk.stem.porter import PorterStemmer\n",
    "ps = PorterStemmer()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "id": "e6935e2a",
   "metadata": {},
   "outputs": [],
   "source": [
    "def get_importantFeatures(sent):\n",
    "    sent = sent.lower()\n",
    "    returnList = []\n",
    "    sent = nltk.word_tokenize(sent)\n",
    "    for i in sent:\n",
    "        if i.isalnum():\n",
    "            returnList.append(i)\n",
    "    return returnList"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "id": "dcc65998",
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['hi', 'how', 'are', 'you']"
      ]
     },
     "execution_count": 59,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "get_importantFeatures('hi how are you')\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "id": "d66a2f89",
   "metadata": {},
   "outputs": [],
   "source": [
    "def get_importantFeatures(sent):\n",
    "    sent = sent.lower()\n",
    "    \n",
    "    returnList = []\n",
    "    sent = nltk.word_tokenize(sent)\n",
    "    for i in sent:\n",
    "        if i.isalnum():\n",
    "            returnList.append(i)\n",
    "    return returnList\n",
    "\n",
    "def removing_stopWords(sent):\n",
    "    returnList = []\n",
    "    for i in sent:\n",
    "        if i not in nltk.corpus.stopwords.words('english') and i not in string.punctuation:\n",
    "            returnList.append(i)\n",
    "    return returnList\n",
    "\n",
    "def potter_stem(sent):\n",
    "    returnList = []\n",
    "    for i in sent:\n",
    "        returnList.append(ps.stem(i))\n",
    "    return \" \".join(returnList)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "id": "eadd23b8",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\hp\\AppData\\Local\\Temp\\ipykernel_18500\\877423605.py:1: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\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",
      "  df['imp_feature'] = df['EmailText'].apply(get_importantFeatures)\n"
     ]
    }
   ],
   "source": [
    "df['imp_feature'] = df['EmailText'].apply(get_importantFeatures)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "id": "135399a5",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\hp\\AppData\\Local\\Temp\\ipykernel_18500\\606255062.py:1: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\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",
      "  df['imp_feature'] = df['EmailText'].apply(get_importantFeatures)\n",
      "C:\\Users\\hp\\AppData\\Local\\Temp\\ipykernel_18500\\606255062.py:2: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\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",
      "  df['imp_feature'] = df['imp_feature'].apply(removing_stopWords)\n",
      "C:\\Users\\hp\\AppData\\Local\\Temp\\ipykernel_18500\\606255062.py:3: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\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",
      "  df['imp_feature'] = df['imp_feature'].apply(potter_stem)\n"
     ]
    }
   ],
   "source": [
    "df['imp_feature'] = df['EmailText'].apply(get_importantFeatures)\n",
    "df['imp_feature'] = df['imp_feature'].apply(removing_stopWords)\n",
    "df['imp_feature'] = df['imp_feature'].apply(potter_stem)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "id": "6ae7e3fa",
   "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>Label</th>\n",
       "      <th>EmailText</th>\n",
       "      <th>imp_feature</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>ham</td>\n",
       "      <td>Go until jurong point, crazy.. Available only ...</td>\n",
       "      <td>go jurong point crazi avail bugi n great world...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>ham</td>\n",
       "      <td>Ok lar... Joking wif u oni...</td>\n",
       "      <td>ok lar joke wif u oni</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>spam</td>\n",
       "      <td>Free entry in 2 a wkly comp to win FA Cup fina...</td>\n",
       "      <td>free entri 2 wkli comp win fa cup final tkt 21...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>ham</td>\n",
       "      <td>U dun say so early hor... U c already then say...</td>\n",
       "      <td>u dun say earli hor u c alreadi say</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>ham</td>\n",
       "      <td>Nah I don't think he goes to usf, he lives aro...</td>\n",
       "      <td>nah think goe usf live around though</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5567</th>\n",
       "      <td>spam</td>\n",
       "      <td>This is the 2nd time we have tried 2 contact u...</td>\n",
       "      <td>2nd time tri 2 contact u pound prize 2 claim e...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5568</th>\n",
       "      <td>ham</td>\n",
       "      <td>Will Ã_ b going to esplanade fr home?</td>\n",
       "      <td>b go esplanad fr home</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5569</th>\n",
       "      <td>ham</td>\n",
       "      <td>Pity, * was in mood for that. So...any other s...</td>\n",
       "      <td>piti mood suggest</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5570</th>\n",
       "      <td>ham</td>\n",
       "      <td>The guy did some bitching but I acted like i'd...</td>\n",
       "      <td>guy bitch act like interest buy someth els nex...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5571</th>\n",
       "      <td>ham</td>\n",
       "      <td>Rofl. Its true to its name</td>\n",
       "      <td>rofl true name</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5169 rows × 3 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     Label                                          EmailText  \\\n",
       "0      ham  Go until jurong point, crazy.. Available only ...   \n",
       "1      ham                      Ok lar... Joking wif u oni...   \n",
       "2     spam  Free entry in 2 a wkly comp to win FA Cup fina...   \n",
       "3      ham  U dun say so early hor... U c already then say...   \n",
       "4      ham  Nah I don't think he goes to usf, he lives aro...   \n",
       "...    ...                                                ...   \n",
       "5567  spam  This is the 2nd time we have tried 2 contact u...   \n",
       "5568   ham             Will Ã_ b going to esplanade fr home?   \n",
       "5569   ham  Pity, * was in mood for that. So...any other s...   \n",
       "5570   ham  The guy did some bitching but I acted like i'd...   \n",
       "5571   ham                         Rofl. Its true to its name   \n",
       "\n",
       "                                            imp_feature  \n",
       "0     go jurong point crazi avail bugi n great world...  \n",
       "1                                 ok lar joke wif u oni  \n",
       "2     free entri 2 wkli comp win fa cup final tkt 21...  \n",
       "3                   u dun say earli hor u c alreadi say  \n",
       "4                  nah think goe usf live around though  \n",
       "...                                                 ...  \n",
       "5567  2nd time tri 2 contact u pound prize 2 claim e...  \n",
       "5568                              b go esplanad fr home  \n",
       "5569                                  piti mood suggest  \n",
       "5570  guy bitch act like interest buy someth els nex...  \n",
       "5571                                     rofl true name  \n",
       "\n",
       "[5169 rows x 3 columns]"
      ]
     },
     "execution_count": 63,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "id": "1ca0da22",
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.model_selection import train_test_split\n",
    "X = df['imp_feature']\n",
    "y = df['Label']\n",
    "X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.25, random_state=42)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "id": "3a2f923e",
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.feature_extraction.text import TfidfVectorizer"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 66,
   "id": "a1af4bb0",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<style>#sk-container-id-1 {color: black;background-color: white;}#sk-container-id-1 pre{padding: 0;}#sk-container-id-1 div.sk-toggleable {background-color: white;}#sk-container-id-1 label.sk-toggleable__label {cursor: pointer;display: block;width: 100%;margin-bottom: 0;padding: 0.3em;box-sizing: border-box;text-align: center;}#sk-container-id-1 label.sk-toggleable__label-arrow:before {content: \"▸\";float: left;margin-right: 0.25em;color: #696969;}#sk-container-id-1 label.sk-toggleable__label-arrow:hover:before {color: black;}#sk-container-id-1 div.sk-estimator:hover label.sk-toggleable__label-arrow:before {color: black;}#sk-container-id-1 div.sk-toggleable__content {max-height: 0;max-width: 0;overflow: hidden;text-align: left;background-color: #f0f8ff;}#sk-container-id-1 div.sk-toggleable__content pre {margin: 0.2em;color: black;border-radius: 0.25em;background-color: #f0f8ff;}#sk-container-id-1 input.sk-toggleable__control:checked~div.sk-toggleable__content {max-height: 200px;max-width: 100%;overflow: auto;}#sk-container-id-1 input.sk-toggleable__control:checked~label.sk-toggleable__label-arrow:before {content: \"▾\";}#sk-container-id-1 div.sk-estimator input.sk-toggleable__control:checked~label.sk-toggleable__label {background-color: #d4ebff;}#sk-container-id-1 div.sk-label input.sk-toggleable__control:checked~label.sk-toggleable__label {background-color: #d4ebff;}#sk-container-id-1 input.sk-hidden--visually {border: 0;clip: rect(1px 1px 1px 1px);clip: rect(1px, 1px, 1px, 1px);height: 1px;margin: -1px;overflow: hidden;padding: 0;position: absolute;width: 1px;}#sk-container-id-1 div.sk-estimator {font-family: monospace;background-color: #f0f8ff;border: 1px dotted black;border-radius: 0.25em;box-sizing: border-box;margin-bottom: 0.5em;}#sk-container-id-1 div.sk-estimator:hover {background-color: #d4ebff;}#sk-container-id-1 div.sk-parallel-item::after {content: \"\";width: 100%;border-bottom: 1px solid gray;flex-grow: 1;}#sk-container-id-1 div.sk-label:hover label.sk-toggleable__label {background-color: #d4ebff;}#sk-container-id-1 div.sk-serial::before {content: \"\";position: absolute;border-left: 1px solid gray;box-sizing: border-box;top: 0;bottom: 0;left: 50%;z-index: 0;}#sk-container-id-1 div.sk-serial {display: flex;flex-direction: column;align-items: center;background-color: white;padding-right: 0.2em;padding-left: 0.2em;position: relative;}#sk-container-id-1 div.sk-item {position: relative;z-index: 1;}#sk-container-id-1 div.sk-parallel {display: flex;align-items: stretch;justify-content: center;background-color: white;position: relative;}#sk-container-id-1 div.sk-item::before, #sk-container-id-1 div.sk-parallel-item::before {content: \"\";position: absolute;border-left: 1px solid gray;box-sizing: border-box;top: 0;bottom: 0;left: 50%;z-index: -1;}#sk-container-id-1 div.sk-parallel-item {display: flex;flex-direction: column;z-index: 1;position: relative;background-color: white;}#sk-container-id-1 div.sk-parallel-item:first-child::after {align-self: flex-end;width: 50%;}#sk-container-id-1 div.sk-parallel-item:last-child::after {align-self: flex-start;width: 50%;}#sk-container-id-1 div.sk-parallel-item:only-child::after {width: 0;}#sk-container-id-1 div.sk-dashed-wrapped {border: 1px dashed gray;margin: 0 0.4em 0.5em 0.4em;box-sizing: border-box;padding-bottom: 0.4em;background-color: white;}#sk-container-id-1 div.sk-label label {font-family: monospace;font-weight: bold;display: inline-block;line-height: 1.2em;}#sk-container-id-1 div.sk-label-container {text-align: center;}#sk-container-id-1 div.sk-container {/* jupyter's `normalize.less` sets `[hidden] { display: none; }` but bootstrap.min.css set `[hidden] { display: none !important; }` so we also need the `!important` here to be able to override the default hidden behavior on the sphinx rendered scikit-learn.org. See: https://github.com/scikit-learn/scikit-learn/issues/21755 */display: inline-block !important;position: relative;}#sk-container-id-1 div.sk-text-repr-fallback {display: none;}</style><div id=\"sk-container-id-1\" class=\"sk-top-container\"><div class=\"sk-text-repr-fallback\"><pre>GridSearchCV(estimator=SVC(),\n",
       "             param_grid={&#x27;C&#x27;: [1, 10, 100, 1000], &#x27;gamma&#x27;: [0.001, 0.0001],\n",
       "                         &#x27;kernel&#x27;: [&#x27;linear&#x27;, &#x27;rbf&#x27;]})</pre><b>In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook. <br />On GitHub, the HTML representation is unable to render, please try loading this page with nbviewer.org.</b></div><div class=\"sk-container\" hidden><div class=\"sk-item sk-dashed-wrapped\"><div class=\"sk-label-container\"><div class=\"sk-label sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-1\" type=\"checkbox\" ><label for=\"sk-estimator-id-1\" class=\"sk-toggleable__label sk-toggleable__label-arrow\">GridSearchCV</label><div class=\"sk-toggleable__content\"><pre>GridSearchCV(estimator=SVC(),\n",
       "             param_grid={&#x27;C&#x27;: [1, 10, 100, 1000], &#x27;gamma&#x27;: [0.001, 0.0001],\n",
       "                         &#x27;kernel&#x27;: [&#x27;linear&#x27;, &#x27;rbf&#x27;]})</pre></div></div></div><div class=\"sk-parallel\"><div class=\"sk-parallel-item\"><div class=\"sk-item\"><div class=\"sk-label-container\"><div class=\"sk-label sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-2\" type=\"checkbox\" ><label for=\"sk-estimator-id-2\" class=\"sk-toggleable__label sk-toggleable__label-arrow\">estimator: SVC</label><div class=\"sk-toggleable__content\"><pre>SVC()</pre></div></div></div><div class=\"sk-serial\"><div class=\"sk-item\"><div class=\"sk-estimator sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-3\" type=\"checkbox\" ><label for=\"sk-estimator-id-3\" class=\"sk-toggleable__label sk-toggleable__label-arrow\">SVC</label><div class=\"sk-toggleable__content\"><pre>SVC()</pre></div></div></div></div></div></div></div></div></div></div>"
      ],
      "text/plain": [
       "GridSearchCV(estimator=SVC(),\n",
       "             param_grid={'C': [1, 10, 100, 1000], 'gamma': [0.001, 0.0001],\n",
       "                         'kernel': ['linear', 'rbf']})"
      ]
     },
     "execution_count": 66,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "tfidf = TfidfVectorizer()\n",
    "feature = tfidf.fit_transform(X_train)\n",
    "\n",
    "tuned_parameters = {'kernel':['linear','rbf'],'gamma':[1e-3,1e-4], 'C':[1,10,100,1000]}\n",
    "\n",
    "model = GridSearchCV(svm.SVC(),tuned_parameters)\n",
    "model.fit(feature, y_train)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 67,
   "id": "89df1373",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Accuracy: 0.9814385150812065\n"
     ]
    }
   ],
   "source": [
    "y_predict = tfidf.transform(X_test)\n",
    "print(\"Accuracy:\",model.score(y_predict,y_test))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 68,
   "id": "f8055c81",
   "metadata": {},
   "outputs": [
    {
     "ename": "AttributeError",
     "evalue": "'GridSearchCV' object has no attribute 'save'",
     "output_type": "error",
     "traceback": [
      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[1;31mAttributeError\u001b[0m                            Traceback (most recent call last)",
      "Cell \u001b[1;32mIn[68], line 1\u001b[0m\n\u001b[1;32m----> 1\u001b[0m \u001b[43mmodel\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43msave\u001b[49m(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mspam_detector\u001b[39m\u001b[38;5;124m\"\u001b[39m)\n",
      "\u001b[1;31mAttributeError\u001b[0m: 'GridSearchCV' object has no attribute 'save'"
     ]
    }
   ],
   "source": [
    "model.save(\"spam_detector\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "215611e7",
   "metadata": {},
   "outputs": [],
   "source": [
    "import pickle\n",
    "filename = 'finalized_model.sav'\n",
    "pickle.dump(model, open(filename, 'wb'))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "21eff8f2",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "text is not spam\n",
      "text is spam\n"
     ]
    }
   ],
   "source": [
    "from tkinter import *\n",
    "import tkinter as tk\n",
    "\n",
    "spam_model = pickle.load(open(\"finalized_model.sav\",'rb'))\n",
    "\n",
    "def check_spam():\n",
    "    text = spam_text_Entry.get()\n",
    "    is_spam = spam_model.predict(tfidf.transform([text]))\n",
    "    if is_spam == 1:\n",
    "        print(\"text is spam\")\n",
    "        my_string_var.set(\"Result: text is spam\")\n",
    "    else:\n",
    "        print(\"text is not spam\")\n",
    "        my_string_var.set(\"Result: text is not spam\")\n",
    "win = Tk()\n",
    "\n",
    "win.geometry(\"400x600\")\n",
    "win.configure(background=\"cyan\")\n",
    "win.title(\"Sms Spam Detector\")\n",
    "\n",
    "title = Label(win, text=\"SMS Spam Detector\", bg=\"gray\",width=\"300\",height=\"2\",fg=\"white\",font=(\"Calibri 20 bold italic underline\")).pack()\n",
    "\n",
    "spam_text = Label(win, text=\"Enter your Text: \",bg=\"cyan\", font=(\"Verdana 12\")).place(x=12,y=100)\n",
    "spam_text_Entry = Entry(win, textvariable=spam_text,width=33)\n",
    "spam_text_Entry.place(x=155, y=105)\n",
    "\n",
    "my_string_var = StringVar()\n",
    "my_string_var.set(\"Result: \")\n",
    "\n",
    "print_spam = Label(win, textvariable=my_string_var,bg=\"cyan\", font=(\"Verdana 12\")).place(x=12,y=200)\n",
    "\n",
    "Button = Button(win, text=\"Submit\",width=\"12\",height=\"1\",activebackground=\"red\",bg=\"Pink\",command=check_spam,font=(\"Verdana 12\")).place(x=12,y=150)\n",
    "\n",
    "win.mainloop()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 75,
   "id": "778f37d7",
   "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>Label</th>\n",
       "      <th>EmailText</th>\n",
       "      <th>imp_feature</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>ham</td>\n",
       "      <td>Go until jurong point, crazy.. Available only ...</td>\n",
       "      <td>go jurong point crazi avail bugi n great world...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>ham</td>\n",
       "      <td>Ok lar... Joking wif u oni...</td>\n",
       "      <td>ok lar joke wif u oni</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>spam</td>\n",
       "      <td>Free entry in 2 a wkly comp to win FA Cup fina...</td>\n",
       "      <td>free entri 2 wkli comp win fa cup final tkt 21...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>ham</td>\n",
       "      <td>U dun say so early hor... U c already then say...</td>\n",
       "      <td>u dun say earli hor u c alreadi say</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>ham</td>\n",
       "      <td>Nah I don't think he goes to usf, he lives aro...</td>\n",
       "      <td>nah think goe usf live around though</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5567</th>\n",
       "      <td>spam</td>\n",
       "      <td>This is the 2nd time we have tried 2 contact u...</td>\n",
       "      <td>2nd time tri 2 contact u pound prize 2 claim e...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5568</th>\n",
       "      <td>ham</td>\n",
       "      <td>Will Ã_ b going to esplanade fr home?</td>\n",
       "      <td>b go esplanad fr home</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5569</th>\n",
       "      <td>ham</td>\n",
       "      <td>Pity, * was in mood for that. So...any other s...</td>\n",
       "      <td>piti mood suggest</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5570</th>\n",
       "      <td>ham</td>\n",
       "      <td>The guy did some bitching but I acted like i'd...</td>\n",
       "      <td>guy bitch act like interest buy someth els nex...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5571</th>\n",
       "      <td>ham</td>\n",
       "      <td>Rofl. Its true to its name</td>\n",
       "      <td>rofl true name</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5169 rows × 3 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     Label                                          EmailText  \\\n",
       "0      ham  Go until jurong point, crazy.. Available only ...   \n",
       "1      ham                      Ok lar... Joking wif u oni...   \n",
       "2     spam  Free entry in 2 a wkly comp to win FA Cup fina...   \n",
       "3      ham  U dun say so early hor... U c already then say...   \n",
       "4      ham  Nah I don't think he goes to usf, he lives aro...   \n",
       "...    ...                                                ...   \n",
       "5567  spam  This is the 2nd time we have tried 2 contact u...   \n",
       "5568   ham             Will Ã_ b going to esplanade fr home?   \n",
       "5569   ham  Pity, * was in mood for that. So...any other s...   \n",
       "5570   ham  The guy did some bitching but I acted like i'd...   \n",
       "5571   ham                         Rofl. Its true to its name   \n",
       "\n",
       "                                            imp_feature  \n",
       "0     go jurong point crazi avail bugi n great world...  \n",
       "1                                 ok lar joke wif u oni  \n",
       "2     free entri 2 wkli comp win fa cup final tkt 21...  \n",
       "3                   u dun say earli hor u c alreadi say  \n",
       "4                  nah think goe usf live around though  \n",
       "...                                                 ...  \n",
       "5567  2nd time tri 2 contact u pound prize 2 claim e...  \n",
       "5568                              b go esplanad fr home  \n",
       "5569                                  piti mood suggest  \n",
       "5570  guy bitch act like interest buy someth els nex...  \n",
       "5571                                     rofl true name  \n",
       "\n",
       "[5169 rows x 3 columns]"
      ]
     },
     "execution_count": 75,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "a4d36514",
   "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": "3.10.9"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}