easy-data-analysis 0.1.4

Scientific research data analysis tools

# easy-data-analysis: plotting and statistical analysis tools for scientific research

## Overview

This package provides tools to analyze scientific research data, with a focus on plotting and statistical analysis.

## Compatibility and Installation

This package is written in Python 3.6 and was tested on Linux and MacOS 13. It depends on the following libraries: * matplotlib 3.1.3 * numpy 1.18.4 * pandas 0.25.3 * scipy 1.4.1

Installing these libraries is easily done with pip, simply run in a terminal: ` pip install --upgrade <library> `

easy-data-analysis is packaged and available through [PyPI](https://pypi.org), you can install it by running in a terminal: ` pip install --upgrade easy-data-analysis `

## Usage

At the moment easy-data-analysis is accessible through a command line interface, type this in your terminal for more information: ` eda --help `

Currently, the only available command is plot and give access to subommands spectrum and kinetics.

### spectrum subcommand

This subcommand plots absorption spectra from CSV files, run: ` eda plot spectrum [arguments] `

Arguments include: * -f or –file specify names of files to process * -l or –label specify labels on data for the plot legend

For example: ` eda plot spectrum -f file1.csv file2.csv -l experiment1 experiment2 `

For more information: ` eda plot spectrum -h `

### kinetics subcommand

This subcommand plots absorption kinetics curves from CSV files, run: ` eda plot kinetics [arguments] `

Arguments include: * -f or –file specify names of files to process * -l or –label specify labels on data for the plot legend * -m or –model is a flag indicating an exponential model should be fitted on the data

For example: ` eda plot kinetics -f file1.csv file2.csv -l experiment1 experiment2 -m `

For more information: ` eda plot kinetics -h `