Metadata-Version: 2.1
Name: dataperpkit
Version: 1
Summary: DataPrepKit is a Python class for data preparation and analysis. It provides functionalities for reading various data formats, summarizing statistics, handling missing values, and encoding categorical data.
Home-page: https://github.com/ahmed-eldesoky284/dataperpkit
Author: Ahmed Eldesoky
Author-email: ahmedeldesoky284@gmail.com
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Description-Content-Type: text/markdown
License-File: LICENSE


# DataPrepKit

DataPrepKit is a Python class for data preparation and analysis. It provides functionalities for reading various data formats, summarizing statistics, handling missing values, and encoding categorical data.

## Key Features

- **Data Reading:** Read data from CSV, Excel, or JSON formats.
- **Data Summarization:** Summarize statistics such as mean, median, standard deviation, mode, minimum, and maximum values.
- **Missing Value Handling:** Handle missing values by removing or imputing them.
- **Categorical Data Encoding:** Encode categorical data using one-hot encoding.

## Usage

DataPrepKit offers methods to perform these key tasks, making data preparation and analysis more efficient and convenient.

To install DataPrepKit, simply use pip:

```bash
pip install dataperpkit
```

Once installed, you can import the `DataPrepKit` class in your Python code and start using its functionalities.

## Requirements

- pandas
- numpy

## Author

This code is authored by [Ahmed ELdesoky].
```

Replace `[Ahmed ELdesoky]` with the appropriate author's name and update any other placeholders accordingly.
