datalib-ym 1.0.1

A comprehensive library for data manipulation, analysis, and visualization

README.md

# 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:

```bash
pip install datalib-ym
```

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:

from datalib_ym.data_manipulation import load_csv
from datalib_ym.statistics import calculate_mean
from datalib_ym.visualization import create_bar_plot

# Load a dataset
data = load_csv("data/sample.csv")

# Calculate the mean of a column
mean_value = calculate_mean(data, "column_name")
print(f"Mean: {mean_value}")

# Create a bar plot of the data
create_bar_plot(data, x="column_name", y="value")

Detailed Usage

For more detailed examples and usage, refer to the examples folder and the project documentation.

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.

Contributing

Contributions are welcome! Please see the contributing guidelines for more information on how to contribute to the project.

License

This project is licensed under the MIT License. See the LICENSE file for details.

---

### Explanation of the README Structure

1. **Introduction**: Briefly describes the purpose of the library.
2. **Features**: Highlights key capabilities.
3. **Installation**: Provides installation instructions using `pip`.
4. **Project Structure**: Shows the directory layout.
5. **Quick Start**: Offers a simple code example to help users get started.
6. **Detailed Usage**: Points to additional examples.
7. **Documentation**: Links to detailed documentation resources.
8. **Contributing**: Invites contributions and links to guidelines.
9. **License**: States the licensing terms.

This structure ensures clarity and ease of use for anyone accessing the repository.