Data Analysis with Tidyverse
7
Reshaping data (todo)
R for Computational Social Science
1
Preface
Data Analysis with Tidyverse
2
Fun with R: A look at the Dutch voter
3
Meet the Tidyverse
4
Data cleaning
5
Transforming data
6
Visualizing data
7
Reshaping data (todo)
Text and Image Analysis
8
Dealing with Text: stringr (todo)
9
Scraping: rvest (todo)
10
Text as Data: tidytext (todo)
11
Using LLMs: tidyllm (todo)
12
Dealing with Images (todo)
Machine Learning
13
Basics of Machine Learning: tidymodels (todo)
14
Supervised Text Classification: textrecipes (todo)
15
Dimensionality Reduction: Clustering and Embeddings (todo)
16
Neural Networks, Deep Learning, and Transformers: torch (todo)
Programming Concepts
17
Flow Control: if/else, while, for (todo)
18
Data Structures: Lists, JSON, Matrix (todo)
19
From Script to Software (todo)
20
References
Table of contents
7.1
Pivotting data: wide vs long
7.2
Joining multiple data sets
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Data Analysis with Tidyverse
7
Reshaping data (todo)
7
Reshaping data (todo)
7.1
Pivotting data: wide vs long
7.2
Joining multiple data sets
6
Visualizing data
8
Dealing with Text: stringr (todo)