R programming, data transformations and data visualization

General data

Course ID:	1000-1M16RWD
Erasmus code / ISCED:	11.1 Kod klasyfikacyjny przedmiotu składa się z trzech do pięciu cyfr, przy czym trzy pierwsze oznaczają klasyfikację dziedziny wg. Listy kodów dziedzin obowiązującej w programie Socrates/Erasmus, czwarta (dotąd na ogół 0) – ewentualne uszczegółowienie informacji o dyscyplinie, piąta – stopień zaawansowania przedmiotu ustalony na podstawie roku studiów, dla którego przedmiot jest przeznaczony. / (0541) Mathematics The ISCED (International Standard Classification of Education) code has been designed by UNESCO.
Course title:	R programming, data transformations and data visualization
Name in Polish:	Programowanie w R i wizualizacja danych
Organizational unit:	Faculty of Mathematics, Informatics, and Mechanics
Course groups:	(in Polish) Przedmioty obieralne na studiach drugiego stopnia na kierunku bioinformatyka
ECTS credit allocation (and other scores):	(not available) Basic information on ECTS credits allocation principles: the annual hourly workload of the student’s work required to achieve the expected learning outcomes for a given stage is 1500-1800h, corresponding to 60 ECTS; the student’s weekly hourly workload is 45 h; 1 ECTS point corresponds to 25-30 hours of student work needed to achieve the assumed learning outcomes; weekly student workload necessary to achieve the assumed learning outcomes allows to obtain 1.5 ECTS; work required to pass the course, which has been assigned 3 ECTS, constitutes 10% of the semester student load. view allocation of credits
Language:	English
Type of course:	elective monographs
Prerequisites (description):	At least one semester course in Statistics.
Short description:	During this course we will cover intermediate and advanced topics related to programming in R, topics related to data manipulation, processing exploration and visualization. You will learn both tools for static graphics (ggplot2) as well as tools for interactive graphics (plotly, rcharts). In addition, we will also talk about basic principles that are important when working with data visualization, like geometry of the plot, data composition and so on. The lecture is divided into two parts, first is related to R programming, packages like dplyr, tidyr, functions, writing own packages, shiny applications. Second part is related to data visualization libraries in R.
Full description:	Topics for consecutive lectures: - Introduction to R, RStudio - Loops, functions and conditional instructions, - Data types, lists, pipe processing, advanced topics related to functions - How to build own package - Unit tests - Code profiling - Tidyverse, package boom, tidydata, forcats, dplyr, tidyr - Shiny - Graphics 101 - Grammar of graphics – ggplot2, plotly
Bibliography:	(in Polish) P. Biecek, Zbiór esejów o sztuce pokazywania danych, 2014. E. R. Tufte, The visual display of quantitative information, 2001. L. Wilkinson ,,The Grammar of Graphics'' Springer 2005.

This course is not currently offered.

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Copyright by University of Warsaw.