Here are a few resources for plotting scientific data that is accessible and accurate.
- Creating publication-quality figures with Matplotlib — A great tutorial on different aspects of plotting, with matplotlib examples.
- Creating Reproducible, Publication-Quality Plots with Matplotlib and Seaborn — Another tutorial, focused on the reproducible aspects of plotting, with Matplotlib and Seaborn examples
- Visualization of Color Palettes using Maps Notice the sequential, divergent and qualitative options as those are crucial.
- YellowBrick — A matplotlib-based library for data-science. It has several templates for evaluating classifiers, exploring data, …
- missingno — A visualization library for understanding missing data in datasets.
- LovelyPlots – A theme for beautiful and TeX-compatible matplotlib themes.