Credit Card Fraud Detection.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "a6e82f24-f39f-4a3f-af6f-5b2101a8c2e8",
   "metadata": {},
   "source": [
    "Loading the dataset into a Pandas DataFrame"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "614cf819-a04c-44a8-97f4-e96629fcad64",
   "metadata": {},
   "outputs": [],
   "source": [
    "credit_card_data = pd.read_csv('./creditcard.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "00f90d5c-75ef-420f-ab1a-39950af0b02b",
   "metadata": {},
   "outputs": [
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       "      <th>Time</th>\n",
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       "   Time        V1        V2        V3        V4        V5        V6        V7  \\\n",
       "0   0.0 -1.359807 -0.072781  2.536347  1.378155 -0.338321  0.462388  0.239599   \n",
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       "3   1.0 -0.966272 -0.185226  1.792993 -0.863291 -0.010309  1.247203  0.237609   \n",
       "4   2.0 -1.158233  0.877737  1.548718  0.403034 -0.407193  0.095921  0.592941   \n",
       "\n",
       "         V8        V9  ...       V21       V22       V23       V24       V25  \\\n",
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       "4 -0.270533  0.817739  ... -0.009431  0.798278 -0.137458  0.141267 -0.206010   \n",
       "\n",
       "        V26       V27       V28  Amount  Class  \n",
       "0 -0.189115  0.133558 -0.021053  149.62      0  \n",
       "1  0.125895 -0.008983  0.014724    2.69      0  \n",
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       "\n",
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     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "credit_card_data.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "123ab97e-0384-411c-abed-570ebaf040bd",
   "metadata": {},
   "outputs": [
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       "            Time         V1         V2        V3        V4        V5  \\\n",
       "284802  172786.0 -11.881118  10.071785 -9.834783 -2.066656 -5.364473   \n",
       "284803  172787.0  -0.732789  -0.055080  2.035030 -0.738589  0.868229   \n",
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       "284805  172788.0  -0.240440   0.530483  0.702510  0.689799 -0.377961   \n",
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       "\n",
       "              V6        V7        V8        V9  ...       V21       V22  \\\n",
       "284802 -2.606837 -4.918215  7.305334  1.914428  ...  0.213454  0.111864   \n",
       "284803  1.058415  0.024330  0.294869  0.584800  ...  0.214205  0.924384   \n",
       "284804  3.031260 -0.296827  0.708417  0.432454  ...  0.232045  0.578229   \n",
       "284805  0.623708 -0.686180  0.679145  0.392087  ...  0.265245  0.800049   \n",
       "284806 -0.649617  1.577006 -0.414650  0.486180  ...  0.261057  0.643078   \n",
       "\n",
       "             V23       V24       V25       V26       V27       V28  Amount  \\\n",
       "284802  1.014480 -0.509348  1.436807  0.250034  0.943651  0.823731    0.77   \n",
       "284803  0.012463 -1.016226 -0.606624 -0.395255  0.068472 -0.053527   24.79   \n",
       "284804 -0.037501  0.640134  0.265745 -0.087371  0.004455 -0.026561   67.88   \n",
       "284805 -0.163298  0.123205 -0.569159  0.546668  0.108821  0.104533   10.00   \n",
       "284806  0.376777  0.008797 -0.473649 -0.818267 -0.002415  0.013649  217.00   \n",
       "\n",
       "        Class  \n",
       "284802      0  \n",
       "284803      0  \n",
       "284804      0  \n",
       "284805      0  \n",
       "284806      0  \n",
       "\n",
       "[5 rows x 31 columns]"
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     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
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   "source": [
    "credit_card_data.tail()"
   ]
  },
  {
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   "execution_count": 12,
   "id": "0cc5b3a8-fac3-43b5-b7a0-a740f1d98f9c",
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      "RangeIndex: 284807 entries, 0 to 284806\n",
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      " #   Column  Non-Null Count   Dtype  \n",
      "---  ------  --------------   -----  \n",
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      " 27  V27     284807 non-null  float64\n",
      " 28  V28     284807 non-null  float64\n",
      " 29  Amount  284807 non-null  float64\n",
      " 30  Class   284807 non-null  int64  \n",
      "dtypes: float64(30), int64(1)\n",
      "memory usage: 67.4 MB\n"
     ]
    }
   ],
   "source": [
    "# view datafram info\n",
    "credit_card_data.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "7426e6ef-bae4-488f-815a-1b62812f87e2",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Time      0\n",
       "V1        0\n",
       "V2        0\n",
       "V3        0\n",
       "V4        0\n",
       "V5        0\n",
       "V6        0\n",
       "V7        0\n",
       "V8        0\n",
       "V9        0\n",
       "V10       0\n",
       "V11       0\n",
       "V12       0\n",
       "V13       0\n",
       "V14       0\n",
       "V15       0\n",
       "V16       0\n",
       "V17       0\n",
       "V18       0\n",
       "V19       0\n",
       "V20       0\n",
       "V21       0\n",
       "V22       0\n",
       "V23       0\n",
       "V24       0\n",
       "V25       0\n",
       "V26       0\n",
       "V27       0\n",
       "V28       0\n",
       "Amount    0\n",
       "Class     0\n",
       "dtype: int64"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# check for missing values\n",
    "credit_card_data.isnull().sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "59dd8a7b-6365-4282-967e-eb073e0f3e01",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Class\n",
       "0    284315\n",
       "1       492\n",
       "Name: count, dtype: int64"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# distribution of legit & fraudulent transactions\n",
    "credit_card_data['Class'].value_counts()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "be3c6408-6dab-4ea5-8445-7c66b80c9fbf",
   "metadata": {},
   "source": [
    "Unbalanced Dataset\n",
    "\n",
    "0 --> Normal Transaction \n",
    "1 --> Fraudulent Transaction"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "f7446c05-9d9c-4c17-a985-b384e82fc470",
   "metadata": {},
   "outputs": [],
   "source": [
    "# seperate data for analysis\n",
    "legit = credit_card_data[credit_card_data.Class == 0]\n",
    "fraud = credit_card_data[credit_card_data.Class == 1]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "7410d1f1-d370-4054-8dde-e81929e767b3",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(284315, 31)\n",
      "(492, 31)\n"
     ]
    }
   ],
   "source": [
    "print(legit.shape)\n",
    "print(fraud.shape)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "556e994b-aeb4-4523-8714-4c91fd5a4e0e",
   "metadata": {},
   "outputs": [],
   "source": [
    "# statistical measures of transactions\n",
    "legit.Amount.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "c4dad501-2144-407d-951a-dcce5e87e26b",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "b498b54d-da43-4c10-98fd-3be0f1f1a4b7",
   "metadata": {},
   "outputs": [],
   "source": []
  }
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