How to detect Credit Card Fraud Using Python Pandas
Detecting fraud in credit card transactions is an important application of Machine Learning. Given below is a step-by-step guide on how to approach fraud detection using Python (Pandas and Scikit-Learn) with the Credit Card Fraud Detection Dataset from Kaggle: Data source: Credit Card Fraud Detection Dataset https://www.kaggle.com/mlg-ulb/creditcardfraud Step 1: Data Preprocessing Start by importing the necessary libraries and loading the dataset into a Pandas DataFrame. import pandas as pd # Load the dataset data = pd.read_csv('creditcard.csv') #replace with the downloaded file path # Explore the dataset print(data.head()) Output: Step 2: Data Exploration Understand the dataset by checking its structure, summary statistics, and class distribution (fraudulent vs. non-fraudulent transactions). # Check the dataset shape print (data.shape) # Check summary statistics #print(data.describe()) # Check class distribution print (data[ 'Class' ].value_counts()) Output: ( 284