Brief summary of the course
This course provides a basic introduction to data visualization for data science using Python programming language and Altair library. It combines theoretical knowledge with practical skills.
After completing this course, students will:
- Know how to visually encode data
- Be able to explore data using visualization
- Be able to create interactive analytical visualizations and maps
- Be able to identify and correct errors in visualizations
- Be able to adapt the design of visualizations according to certain conditions and requirements (for example, to style guides and brand books)
|How and why data visualization works? Visual encoding and interpretation of visual information. Data visualization structure. How do we evaluate data visualization? Intro to data visualization using Python and Altair|
How to choose data visualization method or chart type? Data visualization functions and corresponding chart types. How to use maps and visualize geospatial data?
Exploratory data analysis using Python and Altair. Geospatial data visualization using Python and Altair.
|How to create multiview and interactive data visualizations using Python and Altair. How to spot and fix mistakes in data visualization? How to edit data visualization to reduce noise and emphasize message?|
The final project aims to certify that students have mastered all course materials, and are able to independently choose the required visualization method, depending on the tasks and available data. It also aims to certify that students are able to identify and correct errors in data visualizations, and optimize visualizations for the audience.
For the final project, a dataset (or a couple of datasets to choose from) and a set of questions for it will be offered. Students will need to create at least three visualizations that will answer the questions from the list. Students will also have to justify the choice of visualization method in each individual case, analyze its advantages and disadvantages.