Author Archives: Markus Konrad

Linkdump #115

Python
Interesting articles, projects and news

A Twitter network of members of the 19th German Bundestag – part II

This is the second part about my project that deals with the Twitter network of members of the Bundestag. After getting the necessary data, which was explained in part 1, we will now focus on creating a network graph with links between the representatives’ Twitter accounts for exploratory network analysis.

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A Twitter network of members of the 19th German Bundestag – part I

For the R tutorial that I gave at the WZB in the previous semester, I gave an introduction on how to query web APIs – specifically the Twitter API – and automated data extraction from websites (i.e. web scraping). I showed an example that combined both of these techniques for the goal of getting data about the Twitter activities of members of the current (19th) German Bundestag, which is the federal German parliament. The focus was especially on the question “who follows who” on Twitter. I thought it’s a nice little project showing how to use the Twitter API, do web scraping, combine the collected data and do some exploratory network analysis – all within the R environment. So I decided to polish the code a little bit, put in on GitHub and wrote two blog posts. The first part, i.e. this part, is all about getting the data.

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Linkdump #114

R
Python
Interesting articles, projects and news

Linkdump #113

R
Python
Interesting articles, projects and news

Linkdump #112

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Python
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Linkdump #111

R
Python
Interesting articles, projects and news

Zooming in on maps with sf and ggplot2

When working with geo-spatial data in R, I usually use the sf package for manipulating spatial data as Simple Features objects and ggplot2 with geom_sf for visualizing these data. One thing that comes up regularly is “zooming in” on a certain region of interest, i.e. displaying a certain map detail. There are several ways to do so. Three common options are:

  • selecting only certain areas of interest from the spatial dataset (e.g. only certain countries / continent(s) / etc.)
  • cropping the geometries in the spatial dataset using sf_crop()
  • restricting the display window via coord_sf()

I will show the advantages and disadvantages of these options and especially focus on how to zoom in on a certain point of interest at a specific “zoom level”. We will see how to calculate the coordinates of the display window or “bounding box” around this zoom point.

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Linkdump #110

R
Python
Interesting articles, projects and news

Linkdump #109

R
Interesting articles, projects and news