Resources and links:
- "Data visualization: A view of every Points of View column" by Daniel Evanko, Nature Blogs
- "Data visualization tools drive interactivity and reproducibility in online publishing" by Jeffrey Perkel, Nature
- "Points of Significance" by Martin Krzywinski, Nature Methods column on statistics
- “Ten Simple Rules for Better Figures”
- "The Data Visualisation Catalogue" – A catalog of different types of plots
Software tools for data visualization and data processing:
- Microsoft Excel – The classic spreadsheet software, sufficient for uncomplicated data manipulation and storage, basic plots and curve-fitting. Google Docs offers many of the same features.
- Origin – Powerful plotting software with a graphical user interface, used by many without a penchant for programming. Your lab may have a license.
- MATLAB – The most popular computer algebra system, with a built-in plotting capabilities. As with most of the tools below, MATLAB can allow a user to very easily generate plots in batch, and regenerate them after tweaking, a workflow that is cumbersome in GUI-based tools.
- GNU Octave – Together with gnuplot, Octave has many of the same capabilities as MATLAB with compatible syntax.
- gnuplot * [matplotlib](https://matplotlib.org/) – Python has emerged as a competitor to MATLAB, offering all the features of a general purpose programming language and a very large community. Matplotlib is the most commonly used and supported module in Python for data visualization.
- seaborn – A Python module, built on top of matplotlib, designed especially to plot statistical data.
- pgfplots – If you are a LaTeX power user, give this package a try. It can be used in conjunction with TikZ to achieve very precisely specified generative plots.
- Mayavi – A Python module for visualizing 3D data.
General purpose drawing tools:
- Adobe Illustrator – Illustrator is well known among digital artists and designers, but is often used in the scientific community to make figures. Illustrator may be used to post-process or add illustrations to plots made in other software.
- Inkscape – A vector-graphics editor, similar to Illustrator, available for free under an open-source license.
- Biorender - Premade icons and templates for depicting science in presentations.
- On why rainbow color maps are bad - article 1, article 2
- On color palettes that are inclusive for color blind individuals - article 1, article 2
- "The Visual Display of Quantitative Information" by Edward Tufte
- "Visualize This: The FlowingData Guide to Design, Visualization, and Statistics" by Nathan Yau