Programming with R

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Analytical Information Systems

Learn about the use of programming for data analysis, data management, and statistical analysis techniques.

Applied Data Visualization

The workshop Applied Data Visualization introduces students to the theory and methods underlying data visualization. Data analysts face an ever-increasing amount of data (→ big data) and rather revolutionary technological developments allow researchers to visually engage with data in unprecedented ways. Hence, data visualization is one of the most exciting fields in data science right now. In this workshop students acquire the skills to visualize data in R both for exploratory purposes as well as for the purpose of explanation/presentation. We'll rely on R, the most-popular statistical programming environment when it comes to visualization and we'll make use of popular R packages such as ggplot2 and plotly. Besides creating static graphs we'll also have a look at interactive graphs and discuss how interactive visualization may revolutionize how we present data & findings.
 

Data handling tutorials

Practical tutorials to manage and handle research data for particular software packages: SPSS, R, ArcGIS and N-Vivo. Tutorials contain many practical exercises.

Utrecht University : workshop data handling in R

Educational materials used in the workshop 'Data handling in R' run at Utrecht University

It focuses on raw data handling using R, though a Jupyter notebook, run on CoCalc or SURF.

Contents covered: 

- Naming conventions for files

- Ordering scripts

- Layout of scripts

- Commenting code: best practices

Temporal Network Analysis with R

Learn how to use R to analyze networks that change over time.

Temporal Network Analysis is still a pretty new approach in fields outside epidemiology and social network analysis. This tutorial introduces methods for visualizing and analyzing temporal networks using several libraries written for the statistical programming language R. With the rate at which network analysis is developing, there will soon be more user friendly ways to produce similar visualizations and analyses, as well as entirely new metrics of interest. For these reasons, this tutorial focuses as much on the principles behind creating, visualizing, and analyzing temporal networks (the “why”) as it does on the particular technical means by which we achieve these goals (the “how”). It also highlights some of the unhappy oversimplifications that historians may have to make when preparing their data for temporal network analysis, an area where our discipline may actually suggest new directions for temporal network analysis research.

Core Curriculum

The lessons introduce terms, phrases, and concepts in software development and data science, how to best work with data structures, and use regular expressions in finding and matching data. We introduce the Unix-style command line interface, and teach basic shell navigation, as well as the use of loops and pipes for linking shell commands. We also introduce grep for searching and subsetting data across files. Exercises cover the counting and mining of data. In addition, we cover working with OpenRefine to transform and clean data, and the benefits of working collaboratively via Git/GitHub and using version control to track your work.

Social Science Curriculum

This workshop uses a tabular interview dataset from the SAFI Teaching Database and teaches data cleaning, management, analysis and visualization. There are no pre-requisites, and the materials assume no prior knowledge about the tools. We use a single dataset throughout the workshop to model the data management and analysis workflow that a researcher would use.

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GESIS Notebooks

Have a Binder-Ready repository? With GESIS Notebooks, turn this repository into a persistent Jupyter environment, allowing you to continue your analysis from anywhere at any time.

This service is intended for use by social scientists. You can build and launch all binder-ready projects without logging in. If you want to have more persistent projects, you need to log in.

GESIS Training

At GESIS we offer a wide range of events, especially training courses on empirical social research methods. Our theory founded and hands-on courses develop participants’ methods skills and are aimed at both early career and senior researchers from Germany, Europe, and the whole world.

Library Carpentry

Library Carpentry workshops teach people working in library- and information-related roles how to:

  • Cut through the jargon terms and phrases of software development and data science and apply concepts from these fields in library tasks;
  • Identify and use best practices in data structures;
  • Learn how to programmatically transform and map data from one form to another;
  • Work effectively with researchers, IT, and systems colleagues;
  • Automate repetitive, error prone tasks.