将列名作为字符串传递给 group_by 并汇总

Question

With dplyr starting version 0.7 the methods ending with underscore such as summarize_ group_by_ are deprecated since we are supposed to use quosures.

See: https://cran.r-project.org/web/packages/dplyr/vignettes/programming.html

I am trying to implement the following example using quo and !!

Working example:

df <- data.frame(x = c("a","a","a","b","b","b"), y=c(1,1,2,2,3,3), z = 1:6)

lFG <- df %>% 
   group_by( x,y) 
lFG %>% summarize( min(z))

However, in the case, I need to implement the columns to group by and summarize are specified as strings.

cols2group <- c("x","y")
col2summarize <- "z"

How can I get the same example as above working?

Answer 1

For this you can now use _at versions of the verbs

df %>%  
  group_by_at(cols2group) %>% 
  summarize_at(.vars = col2summarize, .funs = min)

Edit (2021-06-09): Please see Ronak Shah's answer, using muate(across(all_of(cols2summarize), min)) is now the preferred option

Answer 2

From dplyr 1.0.0 you can use across :

library(dplyr)

cols2group <- c("x","y")
col2summarize <- "z"

df %>%
  group_by(across(all_of(cols2group))) %>%
  summarise(across(all_of(col2summarize), min)) %>%
  ungroup

#   x       y     z
#  <chr> <dbl> <int>
#1 a         1     1
#2 a         2     3
#3 b         2     4
#4 b         3     5

Answer 3

Another option is to use non-standard evaluation (NSE), and have R interpret the string as quoted names of objects:

cols2group <- c("x","y")
col2summarize <- "z"

df %>%  
  group_by(!!rlang::sym(cols2group)) %>% 
  summarize(min(!!rlang::sym(col2summarize)))

The rlang::sym() function takes the strings and turns them into quotes, which are in turn unquoted by !! and used as names in the context of df where they refer to the relevant columns. There's different ways of doing the same thing, as always, and this is the shorthand I tend to use!

Answer 4

请参阅 ?dplyr::across 以了解执行此操作的更新方法，因为 group_by_at 和 summary_at 现在已被取代