Instructor: Tim Riffe

Session 1 (Monday)
1) Introduction to R and RStudio
2) Using the editor: main characteristics of RStudio, packages
3) Data handling: import/export data to/from R
4) Tidy data
5) Fundamentals of ggplot2

Session 2 (Tuesday)
1) Tidy data wrangling
2) Data processing pipelines
3) Worked examples

Session 3 (Wednesday)
1) Function writing
2) Modularity
3) Using functions in pipelines

Session 4 (Thursday)
1) Conditional execution: the ‘if’ command
2) Introduction to for-loops
3) Combining `if` and for-loops
4) More complex functions

Session 5 (Friday)
1) Join operations
2) Group challenges
3) Review of the module

Instructor: Marie-Pier Bergeron

Session 1 (Monday)
1) Basic demographic measures
2) The Lexis diagram
3) Rates, probabilities and proportions

Session 2 (Tuesday)
1) Life table
2) Life expectancy
3) The Human Mortality Database (HMD)

Session 3 (Wednesday)
1) Standardization of demographic measures
2) Rate decomposition (Kitagawa method)
3) Life expectancy decomposition (Arriaga method)

Session 4 (Thursday)
1) Population growth
2) Population models
3) The Leslie matrix

Session 5 (Friday)
1) Introduction to population forecast
2) The Lee-Carter model
3) Review of the module

Instructor: Ilya Kashnitsky

Session 1 (Monday)
1) Basic dataviz principles
2) Impressive dataviz showcasess
3) Tidy approach to data
4) {ggplot2} basics

Session 2 (Tuesday)
1) More advanced {ggplot2}
2) Colors in dataviz
3) Themes and fonts
4) Population pyramids and animation

Session 3 (Wednesday)
1) Useful types of dataviz
2) Dotplots – the most neglected and powerful type of dataviz
3) Heatmaps, equality-line, ggridges, treemap
4) Ternaty plots and ternary colorcoding

Session 4 (Thursday)
1) the basics of map projections
2) {sf} – the game changer in #rspatial, `geom_sf`
3) Mapping Europe with {eurostat}
4) Mapping the US with {tidycensus}

Session 5 (Friday)
1) dataviz challenge in teams
2) brief presentations by teams and discussion
3) course wrap-up

Instructor: Juan Galeano

Session 1 (Monday)
1) Basic data manipulation using dplyr
2) %>% the pipe function
3) Group your data and summarise
4) Tidy your data
5) Plot your data: ggplot2

Session 2 (Tuesday)
1) Read shapefiles into R
2) General manipulation of spatial objects.
3) Univariate Class Intervals
4) Color palettes.
5) Thematic maps (I).

Session 3 (Wednesday)
1) Conversion between projection systems.
2) The ggmap package.
3) Thematic maps (II).

Session 4 (Thursday)
1) Spatial Statistics
2) Neighborhood Matrix.
3) Spatial autocorrelation: Global and Local Indicators of Spatial Autocorrelation (LISA).

Session 5 (Friday)
1) Plot Raster Data.
2) Web-mapping: Leaflet and ggiraph.
3) Animated maps: the gganimate library
4) Review of module.

ilya.kashnitsky@gmail.com
University of Southern Denmark, Odense, Denmark

Ilya Kashnitsky is a postdoctoral researcher at the Interdisciplinary Centre on Population Dynamics, University of Southern Denmark. He holds BA in Geography from Moscow State University, a master in Demography from National Research University Higher School of Economics and expects to obtain a PhD in Demography from University of Groningen. His research focuses on regional variations in population age structures across Europe, the demographic processes shaping them, their dynamics and possible implications for economies and societies. Ilya is an avid R user and advocate of open science, he runs a blog (ikashnitsky.github.io ) that is indexed in R-bloggers project.

mpbergeron@sdu.dk
Marie-Pier is an Assistant Professor at the Interdisciplinary Centre on Population Dynamics (CPop) at the University of Southern Denmark. She is a demographer interested in the study of human mortality, longevity and ageing, with a particular interest in exploring new demographic methods to help understand and forecast changes in health and mortality in industrialised societies. Her research can be divided into three broad strands: i) mortality forecasting, including the development of new models; ii) lifespan differentials, with a focus on developing and applying decomposition methods; iii) changes in the causes of death structure.

riffe@demogr.mpg.de
Max Planck Institute for Demographic Research, Rostock, Germany

Tim Riffe is a research scientist at the Max Planck Institute for Demographic Research. His theoretical work focuses on population renewal and temporal relationships over the life course. His empirical work uses original methodological approaches to study relationships between longevity and health in ageing populations, based on both administrative and survey data.

jgaleano@ced.uab.cat
NCCR On the Move, Université de Gèneve

Juan Galeano is post-doctoral researcher at the University of Geneve. He holds a PhD in Demography from the Center for Demographic Studies (CED) and the Autonomous University of Barcelona (UAB). Master in Demography from the European Doctoral School of Demography (EDSD), Master in Territorial and Population Studies from CED and UAB, and BA in Sociology from the University of Barcelona (UB). His current research focuses on how life events influences international and internal migration in Switzerland and the construction of longitudinal demographic datasets from crossing administrative registers.