An interactive, intelligent data-cleaning library with ML-based user adaptation
Project description
DataCleanerAI
DataCleanerAI is an interactive, intelligent Python library for data cleaning, designed to analyze, prompt, and adapt to user preferences for data cleaning tasks, with particular support for large financial or textual datasets.
Key Features
- Automatic Data Analysis: Detects missing values, outliers, duplicates, and type inconsistencies.
- Interactive Prompting: Prompts users for specific cleaning actions based on identified issues, learning from user responses over time.
- ML-Based Preference Prediction: Learns from user interactions and predicts future actions based on historical responses.
- Memory Optimization for Large Datasets: Supports efficient processing of large datasets with Dask for out-of-core data handling.
- Reusable Cleaning Pipelines: Enables creating automated, reusable workflows for repetitive data cleaning tasks.
- Enhanced NLP for Text Data: Utilizes NLP techniques to clean and standardize textual data fields.
- Preference Export/Import: Allows exporting and importing user-defined preferences for collaborative or repeated projects.
- Detailed Reporting: Generates visual insights and summary reports on data quality.
- ETL Integration: Seamlessly integrates with ETL workflows for scheduled data cleaning tasks.
- Multi-User Support: Supports multi-user configurations, with individualized or shared preferences.
Installation
You can install DataCleanerAI via pip:
pip install DataCleanerAI
Project details
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