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Lightweight EDA tool for automated data analysis with insights and visualizations

Project description

shahEDA ๐Ÿš€

Lightweight Automated Exploratory Data Analysis Tool


๐Ÿ“Œ Overview

shahEDA is a lightweight Python package that automates the process of Exploratory Data Analysis (EDA). It helps you quickly understand your dataset by generating structured insights, statistics, and suggestions โ€” all in one run.


โšก Features

  • ๐Ÿ“‚ Load datasets (CSV supported)
  • ๐Ÿ“Š Basic dataset overview (shape, columns, data types)
  • โŒ Missing values detection
  • ๐Ÿ” Duplicate detection
  • ๐Ÿ“ˆ Statistical summaries (mean, std, quartiles, etc.)
  • ๐Ÿง  Smart suggestions for preprocessing & ML readiness
  • ๐ŸŽ›๏ธ Optional verbose and display modes

๐Ÿ› ๏ธ Installation

Clone the repository: git clone https://github.com/codingsheep17/shahEDA.git cd shahEDA Install dependencies: pip install -r requirements.txt


๐Ÿš€ Usage

๐Ÿ”น Simple Usage (Recommended)

from shahEDA import analyze results = analyze("your_dataset.csv", verbose=True, display=True)


๐Ÿ”น Advanced Usage

from shahEDA import AnalyzerEDA eda = AnalyzerEDA("your_dataset.csv", verbose=True, display=True) results = eda.run()


๐Ÿ“Š Example Output

Loaded file in csv format === BASIC INFO === Shape: (100, 14) Columns: [...]

=== MISSING VALUES === No missing values found

=== DUPLICATES === 0 duplicates

=== STATISTICS === (mean, std, quartiles...)

=== SUGGESTIONS ===

  • Encode categorical columns for ML
  • Check feature distributions

๐Ÿง  Suggestions System

The tool automatically identifies:

  • Categorical columns โ†’ suggests encoding
  • Data readiness for ML
  • Potential preprocessing steps

๐Ÿ“ Project Structure

shahEDA/ โ”‚ โ”œโ”€โ”€ init.py # Public API โ”œโ”€โ”€ pipeline.py # Main Analyzer class โ”œโ”€โ”€ _loader.py # Data loading โ”œโ”€โ”€ _eda_engine.py # Core EDA logic โ”œโ”€โ”€ _stats.py # Statistics


๐ŸŽฏ Goal

To simplify and automate EDA so developers and data enthusiasts can:

  • Save time
  • Focus on insights
  • Prepare data faster for ML models

๐Ÿšง Future Improvements

  • ๐Ÿ“Š Advanced visualizations
  • ๐Ÿ“‰ Outlier detection
  • ๐Ÿ” Correlation analysis
  • ๐Ÿ“ฆ PyPI package release

๐Ÿ‘จโ€๐Ÿ’ป Author

Syed Haseeb Shah


โญ Support

If you find this useful, consider giving it a โญ on GitHub!

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