autocleanss 0.1.0

An advanced and automated data cleaning toolkit for Python.

AutoClean: Advanced Automated Data Cleaning Toolkit

AutoClean is a Python package that automates the heavy-lifting of data cleaning and preparation. It provides a simple, high-level API to handle common data quality issues and generates a beautiful, insightful HTML report of the entire process.

Key Features

• Comprehensive Cleaning: Handles missing values, outliers, duplicate records, and data type inconsistencies.
• Smart Imputation: Includes standard (mean/median/mode) and ML-based (KNN) imputation methods.
• Outlier Detection: Uses the IQR method to detect and handle outliers in numerical data.
• Data Type Inference: Automatically detects and converts data types (e.g., object to datetime).
• Automated HTML Report: Generates a detailed, visual report with before-and-after statistics and visualizations.

Installation

You can install AutoClean using pip:

pip install autoclean

Quick Start

Clean your data and generate a report in just a few lines of code.

import pandas as pd
from autoclean import AutoClean

# 1. Load your messy data
df = pd.read_csv('your_messy_data.csv')

# 2. Initialize the cleaner
# You can specify the imputation strategy, e.g., 'knn'
cleaner = AutoClean(df, imputation_strategy='knn')

# 3. Run the cleaning process
cleaned_df = cleaner.clean()

# 4. Generate the HTML report
cleaner.generate_report(output_path='cleaning_report.html')

# 5. View the cleaned data
print("Cleaned DataFrame:")
print(cleaned_df.head())

This will create a file named cleaning_report.html in your current directory. Open it in your browser to see a full analysis of the cleaning process.

License

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