Your Data Analysis Library Name

Overview

Datas is a Rust library designed to provide a comprehensive set of tools for data analysts. Whether you're working with large datasets or conducting complex analyses, this library aims to simplify the process and empower analysts with efficient and reliable functionalities.

Features

Array Creation:
- Easily create arrays from various data sources.
Indexing and Slicing:
- Access specific elements or subsets of data within arrays.
Element-Wise Operations:
- Perform basic arithmetic operations element-wise on arrays.
Descriptive Statistics:
- Calculate common descriptive statistics like mean, median, variance, and more.
Sorting:
- Sort data along specified axes.
Data Cleaning:
- Handle missing values, remove duplicates, and filter outliers.
Reshaping:
- Reshape arrays, transforming them from one dimension to another.
Concatenation and Splitting:
- Concatenate arrays along specified axes and split arrays into smaller ones.
Linear Algebra Operations:
- Perform basic linear algebra operations like matrix multiplication, determinant calculation, and eigenvalue computation.
Random Number Generation:
- Generate random numbers and arrays for simulations and statistical analyses.

Getting Started

Installation:
- Add Datas to your Cargo.toml file:
```
[dependencies]
datas = "0.1.4"
```
Usage:
- Import the library into your Rust project:
```
use datas::*;          
```
- Start using the powerful data analysis features in your project.

Examples

// Example code showcasing how to use key features
fn main(){
       let data: [f64; 4] = [1.0, 2.0, 3.0, 4.0];
       let mean = datas::mean_f(&data);
       print!("Mean: {}", mean);
     }
// ...

Contributing

Contributions are welcome! If you have ideas for improvements, new features, or bug fixes, please open an issue or submit a pull request.

License

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