Task 2 - Email Spam Detection using Naive Bayes .ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "54daeab7",
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd \n",
    "import numpy as np \n",
    "from sklearn.model_selection import GridSearchCV\n",
    "import sklearn as svm\n",
    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "8d638159",
   "metadata": {},
   "source": [
    "# Upload Data "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "fdea2c98",
   "metadata": {},
   "outputs": [],
   "source": [
    "df = pd.read_csv(\"D:\\Virtual Programs\\Oasis Internship\\spam.csv\", encoding = 'latin1')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ff76117d",
   "metadata": {},
   "source": [
    "# Rename Columns "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "85001859",
   "metadata": {},
   "outputs": [],
   "source": [
    "df= df.rename(columns={'v1': 'Target','v2':'EmailText'})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "8bd9b617",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "    .dataframe thead th {\n",
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       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Target</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",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  Target                                          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..."
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head()\n",
    "#df=df.drop(columns=[\"Unnamed: 0\"])"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f50dd6b1",
   "metadata": {},
   "source": [
    "# Clean Dataset "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "492000be",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "    .dataframe tbody tr th:only-of-type {\n",
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       "    .dataframe tbody tr th {\n",
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       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Target</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 Ì_ 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": [
       "     Target                                          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 Ì_ 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": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# remove duplicates from dataset \n",
    "df.drop_duplicates()\n",
    "    \n",
    "# remove rows with any null values\n",
    "df.dropna(axis=0)\n",
    "\n",
    "# remove columns with any null values\n",
    "df.dropna(axis=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "c0002ca1",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(5572, 2)"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "a6f27183",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
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       "\n",
       "    .dataframe tbody tr th {\n",
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       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Target</th>\n",
       "      <th>EmailText</th>\n",
       "      <th>Spam</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>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>ham</td>\n",
       "      <td>Ok lar... Joking wif u oni...</td>\n",
       "      <td>0</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>1</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>0</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>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  Target                                          EmailText  Spam\n",
       "0    ham  Go until jurong point, crazy.. Available only ...     0\n",
       "1    ham                      Ok lar... Joking wif u oni...     0\n",
       "2   spam  Free entry in 2 a wkly comp to win FA Cup fina...     1\n",
       "3    ham  U dun say so early hor... U c already then say...     0\n",
       "4    ham  Nah I don't think he goes to usf, he lives aro...     0"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['Spam']=df['Target'].apply(lambda x:1 if x=='spam' else 0)\n",
    "df.head(5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "ffcf53f6",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['Target', 'EmailText', 'Spam'], dtype='object')"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.columns"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "07a5fbec",
   "metadata": {},
   "source": [
    "# Split & Train model with data set "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "b033893d",
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.model_selection import train_test_split \n",
    "\n",
    "y =df['Target']\n",
    "x =df['EmailText']\n",
    "\n",
    "x_train,  x_test, y_train , y_test = train_test_split(x,y,test_size=0.4, random_state=42)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "1f1a0f82",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "d62d45f1",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "f58680bf",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "85805ac1",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "48b30ab7",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Target       object\n",
      "EmailText    object\n",
      "Spam          int64\n",
      "dtype: object\n"
     ]
    }
   ],
   "source": [
    "print(df.dtypes)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "5a767a98",
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.feature_extraction.text import CountVectorizer\n",
    "\n",
    "from sklearn.naive_bayes import MultinomialNB\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "5b2f3461",
   "metadata": {},
   "outputs": [],
   "source": [
    "# cv = CountVectorizer()\n",
    "# features = cv.fit_transform(y_train)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "84d8e60d",
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.pipeline import Pipeline\n",
    "clf=Pipeline([\n",
    "    ('vectorizer',CountVectorizer()),\n",
    "    ('nb',MultinomialNB())\n",
    "])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "c083b572",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Pipeline(steps=[('vectorizer', CountVectorizer()), ('nb', MultinomialNB())])"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "clf.fit(x_train,y_train)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d856c1dd",
   "metadata": {},
   "source": [
    "# Model Predictions \n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "5a5c8af9",
   "metadata": {},
   "outputs": [],
   "source": [
    "emails=[\n",
    "    'Sounds great! Are you home now?',\n",
    "    'Will u meet ur dream partner soon? Is ur career off 2 a flyng start? 2 find out free, txt HORO followed by ur star sign, e. g. HORO ARIES'\n",
    "   \n",
    "]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "5f7868d4",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array(['ham', 'spam'], dtype='<U4')"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "clf.predict(emails)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "9ce39b32",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.9834006280843428"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "clf.score(x_test,y_test)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "e71c5bb0",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "4557ce93",
   "metadata": {},
   "outputs": [],
   "source": []
  }
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