What is an efficient way to group and filter data in R for subsetting?

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The most efficient way to group and filter data in R for subsetting is by using the dplyr package. The dplyr package provides a set of functions such as filter(), select(), group_by(), and summarize() that allow for easy grouping and filtering of data.

For example, the code below groups and filters the mtcars dataset by the number of cylinders and only selects the rows where the mpg is greater than 20:

library(dplyr) 

mtcars %>%
  group_by(cyl) %>%
  filter(mpg > 20) %>%
  select(mpg, wt, cyl)

This code first groups the mtcars dataset by the number of cylinders using the group_by() function. Then, it filters the grouped data to only include rows where the mpg is greater than 20 using the filter() function. Finally, it selects only the columns mpg, wt, and cyl using the select() function.

Using the dplyr package in this way is not only efficient but also very readable and easy to understand.