Advanced Visualisation in R

obligatory courses

The aim of the course is to teach advanced visualisation methods in R for design adequate and publication ready graphs. For this purpose ggplot2 package will be presented thoroughly from the basics to the advanced applications. Participants will learn about syntax rules of ggplot2, different geometries (e.g. geom_line, geom_point, geom_bar), editing each of the element of the graph (theme, scale functions). Finally the overview of advanced type of graphs will be presented including maps and 2 dimensional distribution. During the semester interactive graphs in various packages will be discussed. An important part of the course will be showing how to use R packages for data visualisation effectively.

R-CRAN is currently one of the most prevalent language for quantitative data analysis. One of the strongest aspect of R are data visualization packages with ggplot2 at the head. The course is designed for people who are familiar with the R program, want to specialize in it and want to master visualisation methods in this environment and then use it in quantitative analysis.

1. Introduction to ggplot2 (functions: ggplot(), aes(), geom_point(), ggsave())

2. Theme editing (functions: themes(), guide_legend(), guides(), labs(), packages: extrafont, ggthemes)

3. Labels on the graph (functions: geom_text(), geom_label(), geom_text_repel(), geom_label_repel())

4. Scale editing: (family of scale_* functions)

5. Barplot and pie plot (functions: geom_bar() and geom_arcpie())

6. Linear plot (functions: geom_line(), geom_vline(), geom_hline(), geom_rect())

7. Multiple graphs in ggplot2 (multiplot(), grid.arrange(), viewport())

8. Estimating trend on graph (geom_smooth())

9. Visualising 1d distributions: (functions: geom_histogram(), geom_density(), geom_boxplot(), geom_violin())

10. Visualising 2d dimentional distribution: (functions: geom_bin2d(), geom_hexbin(), geom_tile())

11. Maps in ggplot2 (functions: geom_polygon, ggmap)

12. Interactive visualisation in ggplot2(packages: ggiraph

13. Stat functions (stat_ family function)

14. htmlwidgets in R

15. Project presentations

- własne materiały

Literatura obowiązkowa:

-Biecek P., 2017, Przewodnik po pakiecie R, wydanie 4, Oficyna Wydawnicza GIS, Wrocław

- Kopczewska K., Kopczewski T., Wójcik P., (red), 2016, Metody ilościowe w R. Aplikacje ekonomiczne i finansowe, CeDeWu, wydanie 2,Warszawa

- Wickham, Hadley. Advanced R. CRC Press, 2014.

- Wickham, Hadley. ggplot2: elegant graphics for data analysis. Springer, 2016.

KNOWLEDGE

1) Student at the end of the course knows how to use the R visualization packages to create advanced and publication ready graphs in R

2) Will have an in-depth knowledge of visualization techniques in R

3) Participant knows the application possibilities of visualization techniques in quantitative data analysis

SKILLS

1) Participant is skilled at working with statistical data using the R package, can automate and optimize data visualization

2) Student can design and write advanced procedures in the R program

SOCIAL SKILLS

1) The participant understands that the expert user of the R program is constantly learning about this environment and improving the workshop.

2) The student is aware that the R program with additional packages is constantly being developed and offers new opportunities over time.

3) The participant is aware that the R program is a universal tool and can be used in various fields of knowledge and that the course provides the basis for self-seeking such adaptations.

Students who complete the least-proficient course will know the program at the proficiency level, which will be a valuable position in the CV and a clear signal for employers with high analytical skills.

K_U02, K_U05

The final grade includes:

• credits for solving tasks performed in the course of self-study in class and homework (30 credits),

• points for preparing the semester project (70 points),

• extra points for activity.

Marks:

Point Mark

[0-60] ndst

(60-70] Dst

(70-80] dst +

(80-90] Db

(90-100] db +

(100-110] Bdb

>110 bdb !