📊 Exploratory Data Analysis Projects

This repository contains multiple Exploratory Data Analysis (EDA) projects performed on datasets from various sources. The goal is to analyze, visualize, and extract insights using Python's powerful data analysis and visualization libraries. Each project focuses on exploring data, cleaning it, handling missing values, and uncovering meaningful patterns through interactive and static visualizations.

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🚀 Tech Stack & Libraries

• Python – Core programming language
• Pandas – Data handling & manipulation with DataFrames
• NumPy – Numerical computations
• Matplotlib – Static data visualization
• Seaborn – Statistical & advanced plots
• Plotly – Interactive visualizations

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📂 Features

• Data loading from multiple sources
• Data cleaning & preprocessing
• Statistical summaries & correlations
• Visualizations for trends & patterns
• Interactive dashboards using Plotly

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🛠️ Installation & Usage

Clone the repository:

git clone https://github.com/YourUsername/Exploratory-Data-Analysis-Projects.git
cd Exploratory-Data-Analysis-Projects

Install required libraries:

pip install pandas numpy matplotlib seaborn plotly

Run Jupyter Notebook or Python scripts for any project:

jupyter notebook

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📊 Example Visualizations

• Histograms & Bar Charts
• Heatmaps & Correlation Plots
• Interactive Scatter Plots
• Pie & Box Plots

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🤝 Contributing

Pull requests are welcome. For major changes, please open an issue first to discuss what you would like to change.