Metadata-Version: 2.4
Name: datacleanerpro
Version: 0.1.1
Summary: A simple and efficient data cleaning library for CSV files
Home-page: https://github.com/yourusername/datacleanerpro
Author: Nabiya Inamdar
Author-email: Nabiya Inamdar <nabiya.inamdar@example.com>
License: MIT License
        
        Copyright (c) 2025
        
        Permission is hereby granted, free of charge, to any person obtaining a copy
        of this software and associated documentation files (the "Software"), to deal
        in the Software without restriction, including without limitation the rights
        to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
        copies of the Software, and to permit persons to whom the Software is
        furnished to do so, subject to the following conditions:
        [...]
        
Project-URL: Homepage, https://github.com/yourusername/datacleanerpro
Project-URL: Bug Tracker, https://github.com/yourusername/datacleanerpro/issues
Project-URL: Documentation, https://github.com/yourusername/datacleanerpro#readme
Project-URL: Source Code, https://github.com/yourusername/datacleanerpro
Keywords: data cleaning,csv,pandas,data processing
Classifier: Development Status :: 3 - Alpha
Classifier: Intended Audience :: Developers
Classifier: Topic :: Software Development :: Libraries :: Python Modules
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: 3.8
Classifier: Programming Language :: Python :: 3.9
Classifier: Programming Language :: Python :: 3.10
Classifier: Programming Language :: Python :: 3.11
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Requires-Python: >=3.7
Description-Content-Type: text/markdown
License-File: LICENSE
Requires-Dist: pandas
Dynamic: author
Dynamic: home-page
Dynamic: license-file
Dynamic: requires-python

# DataCleanerPro

A lightweight Python library for cleaning CSV datasets quickly and efficiently.

## Features
- Remove duplicate rows
- Fill missing values (mean, median, mode, zero)
- Drop unnecessary columns
- Save cleaned datasets easily

## Installation
```bash
pip install datacleanerpro
```

## Usage
```python
from datacleanerpro import DataCleaner

cleaner = DataCleaner("data.csv")
cleaner.remove_duplicates()
cleaner.fill_missing("mean")
cleaner.drop_columns(["unnecessary_column"])
cleaner.save_cleaned_data("cleaned.csv")
```
