Data Visualization: Course overview
About this course
Session 1️⃣ - Foundations & Graphic Semiology
Hour 1: Course Introduction & Visual Variables
- Course overview (i.e. the file you're currently reading)
- Graphic Semiology Fundamentals
Hour 2: Python: installation and philosophy
- [Recommended] Installing Python, the clean way
- The Zen of Python
Hour 3: Data types & first graphs
- Data Types Classification and introduction to
matplotlib - Data Visualization Project : Group constitution and project data requirements
- Practical work with
matplotlib(1/2)
Session 2️⃣ - Static data visualization panorama
Any issue related to the proper execution of code on your machine must be solved during this session. Feel free to ask for help.
Hours 1 & 2: Static graphical representation panorama
Hour 3: Group work: project setup
- Data Visualization Project : Data selection & project planning
Session 3️⃣ - Advanced data visualization
Each group must have selected a dataset and a project scope during Hour 3.
It's good practice to think about the story you want to tell with your data. Combined with the characteristics of your data, this will help you to choose the relevant graph types.
Even though data modeling is not the scope of this course, preliminary knowledge of the correlations and/or causations and "forces at play" can help a lot to build a statistically defensible story.
Hour 1
- Practical work with
matplotlib(2/2) - Exercises 4 to 6
Hour 3
- Data Visualization Project : Story scripting & first graphs
- Data Visualization Project : Advanced visualizations (
bokeh)
Session 4️⃣ - Practical Work
Hours 1 & 2
Hour 3
- Data Visualization Project : Advanced visualizations (
bokeh)
Session 5️⃣ - Final session & project presentations
Hours 2 & 3
- Data Visualization Project : final polish
- Data Visualization Project : presentation
Datasets
- GDP dataset
- Download: Download link
- Download: Download link
- COVID-19 in the US dataset
- Download: Download link
- Download: Download link
Corrections
- Practical work with
matplotlib(1/2)- Correction
- Download: Download link
- Practical work with
matplotlib(2/2) - Practical work with
bokehserver applications- 01_simple_slider.py
- Download: Download link
- 03_real_time_streaming.py
- Download: Download link
- 05_linked_plots.py
- Download: Download link
- 06_interactive_presentation.py
- 01_simple_slider.py
- Practical work: COVID 19 in the US
- Correction
- Download: Download link
- Practical work: COVID 19 in the US: cartographic representation
- Correction
- Download: Download link
- Practical work: COVID 19 in the US - Python scripts (matplotlib)
- covid_data_prep.py - Data preparation module
- Download: Download link
- covid_matplotlib_01.py - Cumulative deaths by administration
- Download: Download link
- covid_matplotlib_02.py - Top 5 states (small multiples)
- Download: Download link
- covid_matplotlib_03.py - Cases vs deaths scatter
- Download: Download link
- covid_matplotlib_04.py - Death rate distributions
- Download: Download link
- covid_matplotlib_12.py - Time-lagged correlation
- Download: Download link
- covid_data_prep.py - Data preparation module
- Practical work: COVID 19 in the US - Python scripts (bokeh server)
- covid_bokeh_10.py - Interactive state explorer
- Download: Download link
- covid_bokeh_11.py - Trend decomposition dashboard
- Download: Download link
- covid_bokeh_10.py - Interactive state explorer
