23 July 2016
This course provides basics of data visualization in R & Python. Course outline: Grammar of Graphics. Principles of information design (coding information through color, size and area, choosing right chart type etc.). Overview of plotting libraries in R & Python. Creating charts and maps in R & Python.
Grammar of Graphics, Data Visualization, Plotting, Mapping
R (dplyr, tidyr/reshape2, ggplot2, rbokeh, ggvis, leaflet), Python (pandas, matplotlib, bokeh, seaborn, ggplot, plotly).
Basics of R & Python (reading data from source, data manipulation – select, filter, group_by, summarise etc.)
Mr. Andriy Gazin
Data Journalist & Analyst at Texty.org.ua
Former head of analytics and infographics department at Korrespondent (2010-2014) and Novoe Vremya (2014-2015) weekly magazines. Currently working as a data journalist and analyst for Texty.or
This course is targeted to bachelors, masters, PhD students, lecturers and specialists in Computer Science Bioinformatics and Computational Biology, Statistics, Mathematics, Electrical and Computer Engineering, Chemical and Biological Engineering, Industrial Engineering, Material Science and Engineering, Neuroscience, Human-Computer Interaction, Psychology, Business and related discipines
This course is a part of Lviv Computer Science Summer School (whole school's credit cost is 3 ects)
EUR 300: This course is a part of Lviv Computer Science Summer School (whole school's cost is 300 EUR)
EUR 350: This course is a part of Lviv Computer Science Summer School (whole school's cost is 350 EUR)