Welcome to my Data Analysis Projects repository!
This collection showcases various analytical workflows, data exploration exercises, visualizations, and insights generated using Python and modern data-science libraries.
The goal of this repository is to demonstrate practical applications of data analysis, storytelling with data, and hands-on experience with real-world datasets.
This repository acts as a central hub for all my analytical projects.
It highlights:
- Data cleaning and preprocessing techniques
- Exploratory Data Analysis (EDA)
- Visualization of complex datasets
- Pattern discovery and insights
- Hands-on use of Python libraries
- Improving analytical thinking and problem-solving
Whether you're a recruiter, fellow data enthusiast, or someone learning data science, this repo provides examples of how I approach and solve analytical problems.
This repository uses a wide range of data-analysis tools, including but not limited to:
- Python
- Pandas
- NumPy
- Matplotlib
- Seaborn
- Plotly (optional, for interactive visuals)
- Scikit-learn (optional, for basic ML tasks)
- Jupyter Notebook
- VS Code
- Google Colab
Each project in this repository follows a similar structure for better organization and readability: