8.5 Resources

This section provides some pointers on resources related to joining data.

8.5.1 Help on joining tables

For more details on joining data tables with the two-table verbs of the dplyr package (Wickham, François, Henry, & Müller, 2022):

• read Chapter 13: Relational data (Wickham & Grolemund, 2017);

• study the vignette vignette("two-table") for two-table verbs, and vignette("dplyr") for one-table verbs of dplyr;

• study the documentation for ?left_join, ?right_join, ?full_join, ?inner_join, etc.;

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

• study (the second page of) the RStudio cheatsheet on data transformation:

Figure 8.3: Joining tables with dplyr from RStudio cheatsheets.

• A quick tutorial on merging data with the *_join() family of functions in dplyr (by Steven V. Miller, 2021-01-22) explains mutating and filtering joins with additional datasets.

Read and follow the links on Wikipedia:Join_SQL for additional information.

8.5.2 Miscellaneous

For animated images of common data transformations (e.g., by using mutating or filtering joins), see

• gadenbuie/tidyexplain at GitHub.com

For more general information on various tidyverse topics (Wickham, 2019c):

• Tidyverse.org provides information on recent developments

• Bookdown.org and its archive page contain books on a wide array of topics.

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[08_join.Rmd updated on 2022-07-15 18:31:57 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