3.6 Resources

This section contains links to resources on transforming data.

3.6.1 Help on data transformation

For more details on dplyr (Wickham, François, Henry, & Müller, 2022):

• study vignette("dplyr") and the documentation for ?arrange, ?filter, ?select, etc.

• study https://dplyr.tidyverse.org and its examples;

• read Chapter 5: Data transformation of r4ds (Wickham & Grolemund, 2017) and complete the corresponding exercises;

• study the RStudio cheatsheet on data transformation:

Figure 3.8: Data transformation with dplyr summary from RStudio cheatsheets.

3.6.2 Tidyverse tools

For general information about the tidyverse (Wickham, 2019c) and its principles:

• see the announcements and articles at https://www.tidyverse.org;

• read The tidy tools manifesto.

The topic of data transformation will stay with us for the rest of this book, as various later chapters cover more advanced aspects. For instance, Chapter 8 on Joining data will cover so-called 2-table-verbs of dplyr.

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[03_transform.Rmd updated on 2022-07-15 18:31:56 by hn.]

References

Wickham, H. (2019c). tidyverse: Easily install and load the ’tidyverse’. Retrieved from https://CRAN.R-project.org/package=tidyverse

Wickham, H., François, R., Henry, L., & Müller, K. (2022). Dplyr: A grammar of data manipulation. Retrieved from https://CRAN.R-project.org/package=dplyr

Wickham, H., & Grolemund, G. (2017). R for data science: Import, tidy, transform, visualize, and model data. Retrieved from http://r4ds.had.co.nz