This repository shows the 3D Principal Component Analysis (PCA) of amino acid content in African indigenous vegetables (see original publication, and the mother git repository).

The R code has been developed with reference to R for Data Science (2e), and the official documentation of tidyverse, and DataBrewer.co. See breakdown of modules below:

• Data visualization with ggplot2 (tutorial of the fundamentals; and data viz. gallery).

• Data wrangling with the following packages:

• tidyr: transform (e.g., pivoting) the dataset into tidy structure.

• dplyr: a basic tool to work with data frames.

• stringr: work with strings.

• regular expression: search and match a string pattern.

• purrr: functional programming (e.g., iterating functions across elements of columns).

• tibble: work with data frames in the modern tibble structure.