dataLibFarah 0.0.1

A library for data manipulation, analysis, and visualization.

DataLib

DataLib is a Python library designed to simplify data manipulation, analysis, and visualization. It provides tools for both basic and advanced users, enabling efficient handling of datasets, statistical computations, and machine learning tasks.

Features

Data Manipulation

• Load and save CSV files.
• Normalize data.
• Handle missing values.

Statistical Calculations

• Compute mean, median, mode, and standard deviation.
• Perform statistical tests (t-test, chi-squared).

Data Visualization

• Create scatter plots, bar charts, and histograms.
• Generate advanced visualizations like correlation matrices.

Advanced Analysis

• Perform linear and polynomial regression.
• Apply PCA for dimensionality reduction.
• Use k-means clustering.
• Perform supervised classification (k-NN, decision trees).

Installation

1. Clone the repository:

   git clone https://github.com/riahiFarah/DataLib.git
   

2. Navigate to the project directory:

   cd dataLibFarah
   

3. Install the library:

   pip install .
   

Usage

Example 1: Load and Save CSV

from datalib import DataLib

df = DataLib.load_csv("data.csv")
DataLib.save_csv(df, "output.csv")

Example 2: Normalize Data

normalized_df = DataLib.normalize_data(df)

Example 3: Perform Linear Regression

x = [[1], [2], [3]]
y = [4, 5, 6]
model, coef, intercept = DataLib.linear_regression(x, y)

Development

Setting Up for Development

1. Install development dependencies:

   pip install .[dev]
   

2. Run tests:

   pytest tests/
   

Contributing

Contributions are welcome! Please open an issue or submit a pull request to discuss potential changes.

License

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