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A Python package for data cleaning and preprocessing.

Project description

Cleano

Cleano is a Python package designed to simplify the process of data cleaning and preprocessing. It provides a set of tools that help users efficiently clean, transform, and prepare their data for analysis.

Features

  • Data Cleaning: Remove duplicates, fill missing values, and perform various cleaning operations with ease.
  • Data Preprocessing: Normalize data, encode categorical variables, and prepare data for machine learning models.
  • Utility Functions: Access helper functions for data validation and logging.

Installation

To install the cleano package, you can use pip:

pip install cleano

Usage

Here is a simple example of how to use the cleano package:

from cleano.cleaning import DataCleaner
from cleano.preprocessing import DataPreprocessor

# Create a cleano instance
cleaner = cleano()

# Clean your data
cleaned_data = cleaner.remove_dup(data)
cleaned_data = cleaner.fill_missing_val(cleaned_data)

# Create a DataPreprocessor instance
preprocessor = DataPreprocessor()

# Preprocess your data
normalized_data = preprocessor.normalize_data(cleaned_data)

Contributing

Contributions are welcome! If you have suggestions for improvements or new features, please open an issue or submit a pull request.

License

This project is licensed under the MIT License - see the LICENSE file for details.

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