John Smith and Brittany Barker (Aggregate co-organizers) will give a brief demonstration on tidy evaluation. Tidy evaluation (selection) provides a concise dialect of R for selecting variables based on their names or properties. We'll cover some example operations such as using tidy selection to select columns by name, position, or type, and to summarise a column or data frame.
References:
We are taking inspiration from this diagram:
We aim to provide an example of using a symbol and a character string to
- Specify one column
- Specify several columns
- Name a new column in mutate or summarise
The beauty of the tidyselect framework is that it can be used in other tidyverse packages, like ggplot or gt
Many uses of ggplot construct a graph step by step -- creating a unique representation that will never be repeated. But sometimes we need ggplot to produce many similar plots and using functions in their construction is needed to avoid repeating yourself or generating a vast amount of code.
Note from https://community.rstudio.com/t/passing-an-input-parameter-to-data/130214/9
scale_fill_manual(values = gender_colours[unique(.data %>% pull({{gender_column}}))])
The gt package is designed to be "tidyselect-aware". How much can we standardize gt through the use of functions?