python_visualization_tutorial

A comprehensive guide of how to make publication-ready figures in python

I am planning to share how to make publication-quality figures in python, I will publish all the tutorial in TowardDatascience Medium platform. In the meantime, I will share some sporadic tricks as separate jupyter nodebook at the bottom of the page.

Phase I: Static Figure (basic matplotlib and seaborn)

1. Tutorial I (Understanding Fig and Ax object)
2. Turorial II (Line plot, colors and legends)
3. Tutorial III (boxplot, scatter plot, heatmap, colormap, barplot, histogram)
4. Tutorial IV (Violin plot, dendrogram)
5. Tutorial V (Seaborn)

Phase II: Advanced tutorials

1. Plotly, interactive network
2. Sankey plot strategies (Matplotlib Path and Patch)

Do you want to know some tricks?

1. gridspec
2. how to move yaxis ticks to the right spines
3. how to extract certain number of colors?
4. legend,flexibly adjust it
5. transformation, bbox
6. stacked legend
7. Markersize
8. stay tuned