The NSC-R Tidy Tuesday workshop sessions are inspired by the Tidy Tuesday initiative, which was aimed at providing a safe and supportive forum for individuals to practice their data processing and visualization skills in R while working with real-world data.
In this workshop, Wim will explore a Tidy Tuesday dataset about the Erasmus student mobility program. This dataset was used in the main Tidy Tuesday of week 10 in 2022. For more information on this data, including the codebook, see the RForDataScience GitHub registry.
In today’s workshop, the focus will be on exploring, analyzing, and maybe visualizing student streams between countries. Example questions to be answered include:
- How many students studied abroad?
- What are the top-10 receiving countries?
- What are the top-10 sending countries?
- Which are the 10 most frequent origin-destination country combinations
- Are reverse flows (the flow from A to B and the flow from B to A) correlated?
- How does total number of students from country A to country B depend on the total number of student from A and the total number of students from B?
- Do adjacent countries attract more or less students than non-adjacent countries?
Join this workshop meeting on Zoom by clicking this link
Wim Bernasco is a senior researcher at the Netherlands Institute for the Study of Crime and Law Enforcement (NSCR) and a professor in Spatial analysis of crime at the School of Business and Economics at the Vrije Universiteit Amsterdam. Most of his work in criminology is about the geography of crime, offender decision making and situational causes of crime.
Materials
- This GitHub repository contains a startup script (
script_student_mobility.R)and two helper data files (country_names.csvandadjacency.csv).
Wim will use the packages here, tidyverse and tidytuesdayR in the workshop.
Citation
For attribution, please cite this work as (Bernasco 2022)