Skip to content
A Little Book of Python for Multivariate Analysis
Jupyter Notebook
Branch: master
Clone or download
Fetching latest commit…
Cannot retrieve the latest commit at this time.
Permalink
Type Name Latest commit message Commit time
Failed to load latest commit information.
doc
.gitignore initial Feb 21, 2016
README.md
a_little_book_of_python_for_multivariate_analysis.ipynb

README.md

A Little Book of Python for Multivariate Analysis

This booklet tells you how to use the Python ecosystem to carry out some simple multivariate analyses, with a focus on principal components analysis (PCA) and linear discriminant analysis (LDA).

Jump to the notebook, or read it on Read the Docs.

Notes

This booklet assumes that the reader has some basic knowledge of multivariate analyses, and the principal focus of the booklet is not to explain multivariate analyses, but rather to explain how to carry out these analyses using Python.

The naming conventions in the functions were kept like in the original source for compliance. The variables were renamed to more generic names, so it would be possible to load your own dataset and run the notebook as it is if the first column of your data contains the data classes. See the cell that does the reading of the data.

The Python code was aimed to be easy to understand, like the R code in the original source, rather than be computationally and memory efficient.

License

Creative Commons License
A Little Book of Python for Multivariate Analysis by Yiannis Gatsoulis is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.
Based on a work at A Little Book of R for Multivariate Analysis by Avril Coghlan licensed under CC-BY-3.0.

You can’t perform that action at this time.