R Case Studies
1
Introduction
2
Beginning
R
Usage
2.1
Everything is an Object
2.2
Calculations
2.3
Loading Data
2.4
Matrices, data.frames
2.5
Exporting/Saving Data
3
Advanced Data Manipulation in
R
3.1
The Tidyverse
3.1.1
Maxims of “Tidy” Data
3.1.2
Long and Wide
3.1.3
ggplot
4
Survey Data in
R
4.1
The test case: Pew Research Data
5
Data Aggregation and Merges
6
Reshape from Wide to Long: WorldBank Data
7
Going (Wide-to-) Long with the Minnesota Twins
8
Multiple Transformations for Complete Data Happiness
9
Accessing Data on the Web with APIs
9.1
Social Networking Data with Twitter
9.2
On-the-Fly Survey Data from HuffPost
9.3
Census ACS Data
9.4
Internet Archive Television Database
10
Dealing with Untidy Data
10.1
JSON
10.2
XML
10.3
Raw HTML
11
Disparate Times Call for Disparate Measures
12
Other
R
Things of Note
References
Published with bookdown
Political Science Data Manipulation: A Case Study Approach in R
Ch. 7
Going (Wide-to-) Long with the Minnesota Twins
Sometimes wide is the way to go. I’ll use a twin study to illustrate.