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Visualization of a Correlation Matrix using plotnine

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ggcorrplot: Visualization of a correlation matrix using plotnine

ggcorrplot is an open source Python package dedicated to matrix of correlation visualization. It os distributed under the MIT License.

Contents

1. Overview

2. Installation

3. Example

4. Documentation

5. About us

Overview

The ggcorrplot package can be used to visualize easily a correlation matrix using plotnine. It provides a solution for reordering the correlation matrix and displays the significance level on the correlogram. It includes also a function for computing a matrix of correlation p-values.

ggcorrplot package provides three functions:

  • cor_pmat which computes a matrix of correlation p-values.
  • get_melt which convert DataFrama from wide to long
  • ggcorrplot for correlation matrix visualization

Installation

Global environment

You can directly install discrimintools using pip :

pip install ggcorrplot

or set a virtual environment.

Virtual environment

Install the 64-bit version of Python 3, for instance from the official website. Now create a virtual environment (venv) and install ggcorrplot.

The virtual environment is optional but strongly recommended, in order to avoid potential conflicts with other packages.

PS C:\> python -m venv ggcorrplot-env # create virtual env
PS C:\> ggcorrplot-env\Scripts\activate  # activate
PS C:\> pip install -U ggcorrplot  # install ggcorrplot

Version

In order to check your installation, you can use.

import ggcorrplot
print(ggcorrplot.__version__)

Using an isolated environment such as pip venv or conda makes it possible to install a specific version of discrimintools with pip and conda and its dependencies independently of any previously installed Python packages.

You should always remember to activate the environment of your choice prior to running any Python command whenever you start a new terminal session.

Dependencies

ggcorrplot is compatible with python version which supports both dependencies :

Packages Version
numpy 2.3.4
pandas 2.3.3
scipy 1.16.3
plotnine 0.15.1

Example

See examples

Documentation

The official documentation is hosted on https://discrimintools.readthedocs.io.

About Us

Authors

ggcorrplot is developed and maintained by Duvérier DJIFACK ZEBAZE, the founder of djifacklab (Djifack Laboratory of Mathematics, Statistics and Economics books and packages production using Python Programming Language).

The djifacklab laboratory maintains others python librairies such as scientisttools, scientistmetrics, scientistshiny, scientisttseries and discrimintools.

Feedbacks

If you have found ggcorrplot useful in your work, research, or company, please let us know by writing to email djifacklab@gmail.com.

Citing ggcorrplot

If ggcorrplot has been significant in your research, and you would like to acknowledge the project in your academic publication, we suggest citing it using the following BibTeX format:

@misc{DJIFACK ZEBAZE_2023, 
    url = {https://github.com/enfantbenidedieu/ggcorrplot}, 
    journal = {ggcorrplot}, 
    publisher = {ggcorrplot: Visualization of a correlation matrix using plotnine}, 
    author = {DJIFACK ZEBAZE, Duvérier}, 
    year = {2023}
}

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