Data Analysis Projects

Exploratory data analysis projects using Python. Covers data cleaning, feature engineering, statistical analysis, and insight extraction from real-world datasets.

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Tools and Libraries

• Python
• Pandas
• NumPy
• Matplotlib
• Seaborn
• Scikit-learn (preprocessing and feature engineering)
• Jupyter Notebook

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Topics Covered

Data Cleaning

• Handling missing values
• Removing duplicates
• Fixing inconsistent data types
• Outlier detection and treatment

Exploratory Data Analysis (EDA)

• Univariate and bivariate analysis
• Distribution analysis
• Correlation analysis
• Statistical summaries

Feature Engineering

• Creating new features from existing data
• Encoding categorical variables
• Feature scaling and normalization
• Handling skewed distributions
• Binning and discretization

Data Visualization

• Bar charts, histograms, box plots
• Heatmaps and correlation matrices
• Pair plots and scatter plots
• Time series plots

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Repository Structure

data-analysis/
    project-1/
        dataset/
        notebook.ipynb
        README.md
    project-2/
        dataset/
        notebook.ipynb
        README.md
    ...

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How to Run

1. Clone the repository

git clone https://github.com/your-username/data-analysis.git

2. Install dependencies

pip install pandas numpy matplotlib seaborn scikit-learn jupyter

3. Open any project notebook

jupyter notebook

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Author

Arifudheen M GitHub: Arif-1411