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.
- Python – Core programming language
- Pandas – Data handling & manipulation with DataFrames
- NumPy – Numerical computations
- Matplotlib – Static data visualization
- Seaborn – Statistical & advanced plots
- Plotly – Interactive visualizations
- Data loading from multiple sources
- Data cleaning & preprocessing
- Statistical summaries & correlations
- Visualizations for trends & patterns
- Interactive dashboards using Plotly
Clone the repository:
git clone https://github.com/YourUsername/Exploratory-Data-Analysis-Projects.git
cd Exploratory-Data-Analysis-ProjectsInstall required libraries:
pip install pandas numpy matplotlib seaborn plotlyRun Jupyter Notebook or Python scripts for any project:
jupyter notebook- Histograms & Bar Charts
- Heatmaps & Correlation Plots
- Interactive Scatter Plots
- Pie & Box Plots
Pull requests are welcome. For major changes, please open an issue first to discuss what you would like to change.