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Data Visualization in Python

The course is divided in two parts.

At the beginning, I will talk about general concepts of visualization.
There is a link below to retrieve the slides.
Then I will try to give you some feebacks from the plotting library, tips and reusable codes (I hope so)...

The second part is more technical. There is 5 modules, 5 notebooks about different topics.
During each one, try to save one figure you will organize in a final panel that you will send me back.
I'll send you an empty one with publication ready dimensions.

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How the session is organized ? - 1h30

1. Generalities ( Slides ~20 mins )

   1. WhoAmI
   2. Libraries in Python
   3. Figures in Science
   4. Guidelines
   5. Plots

2. Hands-on Seaborn ( Jupyter Notebook ~15 mins / topic )

   1. Simple plots
   2. Composite Plots
   3. Heatmaps
   4. Multidimensionality (Binary or Multiclass examples)
   5. A little Transgression with R

3. Create your own scientific panel of figures. ( ~ 10 mins )

   1. Inkscape / PowerPoint

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Session 2

1. Module 3 : Heatmap, Dendogram & ClusterHeatmap. (20 min)

2. Module 4 : PCA & T-SNE (Module4b is a model to resolve exercise 4a). (20 min)

3. Module 5 : Examples in R (removed this year).

4. Module 6 : A simple Venn Diagram (20 min)