Metadata-Version: 2.1
Name: dataMnp
Version: 0.1.0
Summary: A comprehensive library for data preprocessing tasks
Home-page: https://github.com/mudar123t/DataAnalyse
Author: Mudar Shawakh
Author-email: shawakhmudar@gmail.com
License: MIT
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Requires-Python: >=3.6
Description-Content-Type: text/markdown
License-File: LICENSE.txt
Requires-Dist: pandas
Requires-Dist: scikit-learn
Requires-Dist: nltk

DataAnalyse is a comprehensive Python library for data preprocessing tasks. 
It provides a set of functions and classes for handling missing values, outliers,
text manipulation, feature engineering, data type conversion, categorical encoding,
date and time manipulation, and more.

## Features

- **Data Cleaning:** Handle missing values, outliers, and text data.
- **String Manipulation:** Remove stopwords, lowercase text, remove punctuation, and lemmatize text.
- **Data Transformation:** Convert data types, encode categorical variables, create new features, and handle date and time data.
- **Date and Time Manipulation:** Extract date components.
- **Scalable:** Works efficiently with large datasets.
- **Easy to Use:** Simple and intuitive API.

## Installation

You can install DataAnalyse from PyPI using pip:

## Usage

```python
import DataAnalyse


# Example usage of DataAnalyse module
import DataAnalyse

# Example usage of specific modules within DataAnalyse
from DataAnalyse import OutlierHandler, StringManipulation

# Use cases
# Handle outliers
data = pd.read_csv('data.csv')
cleaned_data = OutlierHandler.remove_outliers_iqr(data, threshold=1.5)

# Text preprocessing
processed_text = StringManipulation.remove_stopwords(data, column='text_column')
