Data science

This online resource provides information on how to use ggplot2 in R. It also offers downloadable cheatsheets in pdf format in a wide range of languages including English, Chinese, Dutch, French, German, Japanese, Portuguese, Spanish, Turkish and Vietnamese.

This online resource provides some basic information about ggplot2 and how to use it to create plots such as scatter plots, line plots, histograms, density plots and other plots. It also details how to e.g. add title and axis labels, add a legend, carry out log transformations and other functionalities.

This online book titled "R graphics cookbook" by Winston Chang mainly focuses on creating graphs using ggplot2. It covers basics such as installing, loading and updating a package in R, exploring data, as well as in-depth information on making bar graphs, line graphs, scatter plots and other types of graphs (e.g. histograms, basic box plot, dot plot).

This is the Matplotlib website that allows you to create graphics in Python.

This site provides access to cheatsheets and handouts about using Matplotlib in pdf format.

This site provides links to e.g. the quick start guide with examples and FAQs, information about figures and backends, axes and subplots, colours, style sheets and text in Matplotlib.

This website provides information about a large number of graph / chart types that can be generated in R. It offers foundational tutorials and step-by-step guides for the different chart types, such as boxplots, histograms, scatter plots, treemaps, pie charts, time series, maps, network and lots of other charts.

This online book, titled "R gallery book" by Kyle W. Brown is a complete guide to the R graph gallery website.

This is the site for seaborn, a Python visualisation library based on Matplotlib. This site provides links to the installation guide as well as to tutorials (e.g. relational plots, categorial plots, regression plots, multi-plot grids).

This online resource offers an introduction to data visualisation with seaborn. It covers a range of topics, e.g. visualising statistical relationships, distributions of data and categorical data, statistical estimation and error bars and choosing colour palettes.

This online resource is a step-by-step guide that can be used by itself or alongside the official seaborn page and provides a range of examples.

This is the BioRender website, which allows you to create professional looking figures / graphics using a wide range of pre-made icons and templates available in the program.