BITL1 - Introduction to Visualization Labs - Spring 2022

Other offerings of this course: Spring 2022, Spring 2023

Time: Tuesdays 11:10 - 12:50
Lecture instructors: Leo Selavo, Oskars Radzins
Lab instructor: Jānis Lazovskis, janis.lazovskis@rbs.lv
Internal page: ORTUS e-studijas
Office: 404, Skolas iela 11
Office hours: Every day, bookable at Calendly
Syllabus: link

Projects

Project 1

Overview: List of topics + grading scheme
Peer review: feedback for others' presentations

Project 2

Overview: Description + grading scheme

Lab material

Instructions and additional files for the weekly labs.

4 January: data types, reading data, plotting data
- auxiliary files to use for plots in lab
- Python template for producing the plots
11 January: data sources, different representations
- Python code for first exercise
18 January: color
- Python notebook to accompany lab
25 January: data wrangling
- Python notebook to accompany lab
1 February: big data
- adjacency matrix to use for the lab (taken from the BlueBrain portal)
- Python notebook to accompany lab
8 February: lines of best fit, outliers, basic statistics
- Python notebook to accompany lab
15 February: different online visualization tools
1 March: visualizing networks
8 March: visualizing data errors
15 March: analyzing and critiquing visual stories
22 March: introducing choropleth maps in Python
29 March: more on choropleth maps
5 April: interpreting and improving misleading visualizations