datacmp 0.1.0

A lightweight library for exploring and cleaning datasets for ML workflows.

Datacmp

Datacmp is a lightweight and modular Python library for exploratory data analysis (EDA) and data cleaning using pandas.
It helps you quickly generate clean summaries, standardize column names, and handle missing values — all with professional tabulated outputs and optional YAML configuration.

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Features

• Dataset Summary
  • Report total rows, columns, data types, missing values, and basic statistics
• Column Name Cleaning
  • Standardize column names for readability and consistency
• Missing Value Handling (clean_missing_data)
  • Convert data types (numeric and datetime)
  • Drop columns with excessive missing values
  • Fill missing values using intelligent strategies (mean, median, mode)
  • Optionally remove duplicate rows
• YAML Configuration Support
  • Customize behavior using config.yaml without touching your code
• Formatted Output
  • Display insights with beautiful, readable tables powered by tabulate

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Installation

Clone the repository:

git clone https://github.com/MoustafaMohamed01/datacmp.git
cd dataforge

Install dependencies:

pip install -r requirements.txt

Or install them manually:

pip install pandas tabulate

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Project Structure

datacmp/
│
├── datacmp/
│   ├── __init__.py            # Main package initializer
│   ├── column_cleaning.py      # Functions to clean column names
│   ├── detailed_info.py       # EDA functions for summarizing datasets
│   ├── data_cleaning.py     # Functions to handle missing values intelligently
│
├── config.yaml                # Optional configuration file
├── LICENSE                    # MIT license
├── requirements.txt           # Project dependencies
├── setup.py                   # Setup script for packaging
├── README.md                  # Project documentation

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Requirements

• pandas
• tabulate

All required packages are listed in requirements.txt.

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License

This project is licensed under the MIT License.

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Author

Developed by Moustafa Mohamed

• LinkedIn
• Kaggle