This repository focus on a PDF where the general data analysis workflow I applied along my MSc thesis. It starts with multivariate analysis of both flavors: unsupervised and supervised. Later, analysis of MetaboRank output, showing how to look for suggested metabolites in a set of features.
The workflow covers an introduction to the experimental data to afterwards show the data manipulation and data analysis performed with Python.
Furthermore, as at the end of my thesis I had a few Python modules I developed with the aim of making my code less redundant, more readable and speed-up my analysis. I show how to use what soon will be my first Python library. The aim is to provide of high-level tools to perform chemometrics analysis using Python programming language.