Exploratory Data Analyses

Repository Overview

This repository contains a collection of my Exploratory Data Analyses (EDAs) across various datasets and domains. Each project focuses on understanding data structure, uncovering patterns, and generating insights through visualization and statistical exploration.

---

Contents

• Individual EDA Notebooks/Reports
  Each folder or notebook corresponds to a specific dataset or topic. Inside, you’ll typically find:

  • Data cleaning & preprocessing steps
  • Univariate, bivariate, and multivariate analyses
  • Visualizations for key insights
  • Observations and conclusions

• Supporting Files

  • Raw or processed datasets (where licensing allows)
  • Utility scripts for reusable plotting or analysis functions

---

Tools & Libraries

The analyses primarily use Python with:

• Data Handling: pandas, numpy
• Visualization: matplotlib, seaborn, plotly
• Statistics & ML (when needed): scipy, scikit-learn