Data Visualization 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.org.ua. Running blog about infographics and dataviz – textura.in.ua, providing training programs on data analysis and visualizations for journalists and NGO’s.
Fields of interests: Statistics, Data Analysis & Visualization, Mapping, R, ggplot2, Python, Open Data