Metadata-Version: 2.4
Name: media-calc
Version: 0.2.4
Summary: A comprehensive Python library for statistical calculations including mean, median, mode, variance, and standard deviation
Author: Omardev29
Author-email: omaroficial365@gmail.com
License: MIT
Project-URL: Source Code, https://github.com/omardev29/media-calc
Project-URL: Bug Tracker, https://github.com/omardev29/media-calc/issues
Project-URL: Documentation, https://github.com/omardev29/media-calc#readme
Keywords: mathematics,statistics,average,mean,calculator,median,mode,variance,standard deviation,data analysis
Classifier: Development Status :: 3 - Alpha
Classifier: Intended Audience :: Developers
Classifier: License :: OSI Approved :: MIT License
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.6
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: 3.8
Classifier: Programming Language :: Python :: 3.9
Requires-Python: >=3.6
Description-Content-Type: text/markdown
Dynamic: author
Dynamic: author-email
Dynamic: classifier
Dynamic: description
Dynamic: description-content-type
Dynamic: keywords
Dynamic: license
Dynamic: project-url
Dynamic: requires-python
Dynamic: summary

# media-calc

[![PyPI version](https://badge.fury.io/py/media-calc.svg)](https://badge.fury.io/py/media-calc)
[![Python Versions](https://img.shields.io/pypi/pyversions/media-calc.svg)](https://pypi.org/project/media-calc/)
[![License: MIT](https://img.shields.io/badge/License-MIT-yellow.svg)](https://opensource.org/licenses/MIT)

A comprehensive Python library for statistical calculations. Simple, efficient, and easy to use.

## Description

This library provides a set of robust statistical functions for data analysis. Perfect for students, researchers, and data analysts who need quick and reliable statistical calculations.

### Key Features
- Basic and advanced statistical analysis
- Clean and intuitive API
- Comprehensive documentation
- No external dependencies
- Efficient calculations
- Handles empty lists gracefully

## Installation

```bash
pip install media-calc
```

## Usage

```python
from media import (
    media, 
    mediana, 
    moda, 
    varianza, 
    desviacion_estandar
)

# Sample data
numbers = [2, 4, 4, 4, 5, 5, 7, 9]

# Calculate basic statistics
print(f"Mean: {media(numbers)}")          # Output: 5.0
print(f"Median: {mediana(numbers)}")      # Output: 4.5
print(f"Mode: {moda(numbers)}")           # Output: 4
print(f"Variance: {varianza(numbers)}")   # Output: 4.0
print(f"Std Dev: {desviacion_estandar(numbers)}")  # Output: 2.0
```

## Available Functions

### Basic Statistics
- `media(lista)`: Calculate arithmetic mean of a list of numbers
- `mediana(lista)`: Find the middle value of a sorted list
- `moda(lista)`: Find the most frequent value

### Advanced Statistics
- `varianza(lista)`: Calculate the variance of the data
- `desviacion_estandar(lista)`: Calculate the standard deviation

### Empty List Handling
All functions handle empty lists gracefully:
- `media()`: returns 0
- `mediana()`: returns 0
- `moda()`: returns None
- `varianza()`: returns 0
- `desviacion_estandar()`: returns 0

### Version Information
You can check the current version of the library:
```python
import media
print(media.__version__)  # Shows current version
```

# 2.0: more funcioanalities added
# 2.1: better documentation
## License

This project is licensed under the MIT License.
