Visualization using Python ========================== Basics ------ - `Ten simple rules for better figures `__ - [1]: Know Your Audience; [2]: Identify Your Message; [3]: Adapt the Figure to the Support Medium; [4]: Captions are not Optional; [5]: Do Not trust the Defaults; [6]: Use Color Effectively; [7]: Do Not Mislead the Reader; [8]: Avoid ‘‘Chartjunk’’; [9]: Message Trumps Beauty; [10]: Get the Right Tool - `Basic guide for plotting with Matplotlib `__ - This is a very good introduction for Matplotlib Great Examples -------------- - `Textbook Figures for Statistics, Data Mining, and Machine Learning in Astronomy `__ SciPy John Hunter Excellence in Plotting Contest ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ - `The 2013 gallery `__ - Many are astronomy related and excellent examples - `The 2014 gallery `__ - `The 2015 gallery `__ Link not working… - `The 2018 entries `__ Color and Colour ---------------- - `Your Friendly Guide to Colors in Data Visualisation `__ - Pretty much the only thing you need to read about color. - `Why rainbow colormap is harmful `__ Matplotlib ~~~~~~~~~~ - `Gallery of named colors in Matplotlib `__ - `Gallery of colormaps in Matplotlib `__ Fancier and Better ~~~~~~~~~~~~~~~~~~ - `ColorBrewer2 - Interactive colormap builder `__ - `Nippon Colors - Fancy traditional Japanese colors `__ Better Colormaps ~~~~~~~~~~~~~~~~ - `Palettable - Color palettes for Python `__ - Really useful, with a lot of nice selections. Including color palettable from Wes Anderson movies. - `CMasher: Scientific colormaps for making accessible, informative and cmashing plots `__ - “The colormaps in CMasher are all designed to be perceptually uniform sequential using the viscm package; most of them are color-vision deficiency (CVD; color blindness) friendly” - `Scientific Colour-Maps by Fabio Crameri `__ - “Scientific colour-maps, like the colour maps devon, davos, oslo, and broc, are perceptually uniform, perceptually ordered, readable as B&W print and colour-vision-deficiency (CVD) friendly.”