Manipulate data with dplyr

The dplyr package is based on a data manipulation ‘grammar’. This grammar provides a consistent set of ‘verbs’ that solve the most common data manipulation tasks. I illustrate five of these ‘verbs’: filter(), arrange(), select(), mutate(), and summarise().


Tidy corpus linguistics data with tidyr

The tidyr package is part of the tidyverse. As its name indicates, it is meant to help you create tidy data or tidy messy data according to the tidy data principles: each variable forms a column; each observation forms a row; each type of observational unit forms a table. This post illustrates how to tidy a data set in R using two tidyr functions: pivot_longer() and separate().


Should corpus linguists embrace the tidyverse?

Since the publication of my book on corpus linguistics with R, many colleagues have asked me if I was planning to switch the whole code to the tidy style (some of the code in the book makes use of some tidyverse packages. If you want to know my answer, please read on.

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