Data Analysis Case Studies

This repository contains multiple case studies demonstrating my learning and practical implementation of Python, NumPy, Pandas, and Data Visualization libraries, Data Preprocessing, and Feature Engineering techniques.

Case Studies Included

Bank Customer Transaction Management

• Python functions & dictionary
• Simulates basic banking operations

Car Price Analysis

• Data visualization using Seaborn & Matplotlib
• Insights on fuel type, pricing, and transmission

Insurance Data Transformation (NumPy)

• Data correction using NumPy
• Column swapping and aggregation

Customer Feedback Analysis

• Mixed data handling (numerical + text)
• Statistical insights using NumPy

Patient Records Analysis (Pandas)

• Data cleaning & preprocessing
• Grouping, aggregation, and sorting

Tourism Data Analysis (Plotly)

• Interactive visualizations
• Seasonal and country-wise trends

Titanic Data Preprocessing Case Study

• Missing value handling, outlier treatment, encoding, and feature scaling.
• Prepared a clean and machine-learning-ready dataset.

House Price Feature Engineering Case Study

• Created new features using property size, price, and location data.
• Applied feature transformation, binning, and encoding techniques

Tech Stack

• Python
• NumPy
• Pandas
• Matplotlib
• Seaborn
• Plotly
• Sciket-learn
• Jupyter Notebook

CONCLUSION

This repository documents my journey in Data Analytics by applying concepts learned through hands-on case studies. Each project focuses on developing practical skills that are commonly used in real-world data analysis and machine learning workflows.