datalib-ym 0.1.0

A comprehensive library for data manipulation, analysis, and visualization

DataLib

DataLib is a comprehensive library for data manipulation, analysis, and visualization in Python.

Features

• Data manipulation: Load, save, and filter CSV files
• Data transformation: Normalize data and handle missing values
• Statistical analysis: Calculate mean, median, mode, standard deviation, correlation, and perform statistical tests
• Data visualization: Create bar plots, histograms, scatter plots, and correlation matrices
• Advanced analysis: Perform linear and polynomial regression, classification (logistic regression, decision trees, k-NN), and clustering (k-means, PCA)

Installation

You can install DataLib using pip:

Project Structure

``` datalib_ym/ │ ├── src/ │ └── datalib_ym/ │ ├── init.py │ ├── data_manipulation.py │ ├── statistics.py │ ├── visualization.py │ └── advanced_analysis.py │ ├── tests/ │ ├── init.py │ ├── test_data_manipulation.py │ ├── test_statistics.py │ ├── test_visualization.py │ └── test_advanced_analysis.py │ ├── docs/ │ ├── index.md │ ├── installation.md │ ├── quickstart.md │ ├── api_reference.md │ ├── examples.md │ ├── contributing.md │ ├── changelog.md │ └── components/ │ ├── index.md │ ├── data_manipulation.md │ ├── data_transformation.md │ ├── statistical_analysis.md │ ├── data_visualization.md │ └── advanced_analysis.md │ ├── examples/ │ └── datalib_demo.py │ ├── .github/ │ └── workflows/ │ └── ci.yml │ ├── README.md ├── setup.py ├── pyproject.toml ├── setup.cfg └── .gitignore ```

Quick Start

For a comprehensive example of how to use DataLib, check out the examples/datalib_demo.py file in the project repository. This demo covers all major features of the library.

Here's a simple example to get you started with DataLib:

[Rest of the Quick Start section remains unchanged]

Detailed Usage

[Detailed Usage section remains unchanged]

Documentation

For more detailed information on how to use DataLib, please refer to our documentation. The documentation includes:

• Installation guide
• Quick start tutorial
• Detailed component descriptions
• API reference
• Examples
• Contribution guidelines

You can find the documentation in the docs/ directory of the project repository.