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📊 Data Visualization Techniques course for DS studies in Winter 2021/22

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Data Visualization Techniques

Winter Semester 2021/22 @kozaka93 @hbaniecki

Previous: Winter Semester 2020/21

Schedule

# Month-Day Lecture Lab Project Points
1 10-07 Course introduction, data types, visualization tools
10-04 R: review: proton, GitHub Introducing  P1
10-06
10-08
2 10-14 The Grammar of Graphics
10-11 R: dplyr, tidyr, forcats Group work P1 (1p)
10-13
10-15
3 10-19 Colors and scales
10-18 R: ggplot2 - introduction Data exploration P1 (1p)
HW1 (5p)
10-20
10-22
4 10-21 Don't do this at home
10-25 R: ggplot2 - plot modification, theme, facets First visualizations P1 (1p)
10-27
10-29
5 10-28 Other plot types
11-08 R: ggplot2 - advanced, extensions: patchwork, ggstatsplot, map, ggrepel Consultations HW2 (5p)
11-03
11-05
6 11-04 The International Business Communication Standards
11-15 Python: pandas, numpy, pandas.plot Advanced visualizations P1 (1p)
11-17
11-19
7 11-10 History of Statistical Graphics
11-22 Python: matplotlib, seaborn Prototype P1 (1p)
HW3 (10p)
11-24
11-26
8 11-18 How to work in a graphics program? Hans Rosling: The best stats you've ever seen, Let my dataset change your mindset
11-29 R: plotly - interactive visualization Consultations HW4 (5p)
12-01
12-03
9 11-25 Dashboards
12-06 R: Shiny - introduction Discussing P1
Introducing P2
12-08
12-10
10 12-02 Presentation of P1 (part 1) P1 (20p)
12-13 R: Shiny - advanced Group work P2 (1p)
HW5 (5p)
12-15
12-17
11 12-09 Presentation of P1 (part 2)
12-20 R: Xmas trees - gganimate, RBokeh, ggiraph, vegalite, googleVis Data analysis P2 (2p)
HW6 (10p)
12-22
12-21
12 12-16 Scrollytelling: Pockets, Powerless , Here’s How America Uses Its Land
01-03 R: tidycharts, rpivotTable, visNetwork Prototype P2 (2p)
HW7 (5p)
01-05
01-10
13 01-13 Guest lecturer
01-17 R: DataExplorer, visdat etc. Consultations
01-12
01-14
14 01-20 Presentation of P2 (part 1) P2 (20p)
01-24 Python: pandas-profiler etc. Discussing P2 HW8 (5p)
01-19
01-21
15 01-27 Presentation of P2 (part 2)
01-31 --- ---
01-26
01-28

General rules and course assessment

You can obtain up to 100 points during the term, which will be assigned according to the following list:

  • Projects (2 x 25 points)
  • Homeworks (2 x 10 points, 6 x 5 points)

You need at least 51 points overall, in this at least 13 points from each of the projects, in order to pass the course.

The grades will be given according to the table:

Grade 3 3.5 4 4.5 5
Score (50, 60] (60, 70] (70, 80] (80, 90] (90, ∞)

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📊 Data Visualization Techniques course for DS studies in Winter 2021/22

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