datalib-ym 1.0.1
A comprehensive library for data manipulation, analysis, and visualization
License: MIT
Requires Python: >=3.7

### `README.md`

````markdown
# 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:

```python
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](examples/) folder and the project documentation.

## Documentation

For more detailed information on how to use DataLib, please refer to our [documentation](docs/index.md). 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](docs/contributing.md) for more information on how to contribute to the project.

## License

This project is licensed under the MIT License. See the [LICENSE](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.
```