A comprehensive collection of data science and analysis projects powered by the Python ecosystem. This repository focuses on Exploratory Data Analysis (EDA), Data Cleaning, and Statistical Visualization.
- IPL 2025 Mega Auction Analysis: Predictive insights and budgetary analysis for team building.
- FIFA World Cup Data: Historical performance tracking and goal trend analysis.
- Airbnb Project: Pricing analysis and stay trends.
- New York Airbnb Listing 2024: Deep dive into the NYC market with the latest 2024 data.
- Financial Loan Project: Risk assessment and loan status classification.
- Zomato Data Analysis: Restaurant performance and customer rating correlations.
- Mall Customer Segmentation: Unsupervised learning for targeted marketing.
- Covid-19 Analysis: Global trend visualization and infection rate modeling.
Each notebook in this repository follows a standard professional pipeline:
- Data Acquisition: Loading raw CSV/Excel datasets.
- Data Wrangling: Handling missing values, duplicates, and type conversion using Pandas.
- EDA: Statistical summaries and distribution checks.
- Visualization: Creating insightful charts using Matplotlib and Seaborn.
- Insights: Summarizing key findings for business stakeholders.
- Clone the repository:
git clone [https://github.com/Pritam9952/Data_Analysis-Python-Projects.git](https://github.com/Pritam9952/Data_Analysis-Python-Projects.git)
- Install dependencies:
pip install pandas numpy matplotlib seaborn jupyter Open any .ipynb file in Jupyter Lab or VS Code to view the analysis.
- LinkedIn: Pritam Nagar
- Portfolio: My Personal Website