Group by multiple columns in dplyr, using string vector input?

Question

I'm trying to transfer my understanding of plyr into dplyr, but I can't figure out how to group by multiple columns. # make data with weird column names that can't be hard coded data = data.frame( asihckhdoydkhxiydfgfTgdsx = sample(LETTERS[1:3], 100, replace=TRUE), a30mvxigxkghc5cdsvxvyv0ja = sample(LETTERS[1:3], 100, replace=TRUE), value = rnorm(100) ) # get the columns we want to average within columns = names(data)[-3] # plyr - works ddply(data, columns, summarize, value=mean(value)) # dplyr - raises error data %.% group_by(columns) %.% summarise(Value = mean(value)) #> Error in eval(expr, envir, enclos) : index out of boundsWhat am I missing to translate the plyr example into a dplyr-esque syntax?**Edit 2017**: Dplyr has been updated, so a simpler solution is available. See the currently selected answer.

Answer 1

Tidyselection

One approach is using tidyselect syntax¹. Specifically, to select columns whose names are in a string vector, we use the all_of() helper².

Some functions like select()³ accept our tidyselection directly...

library(dplyr)

# |-------------|

data %>% select(all_of(columns))

#> asihckhdoydkhxiydfgfTgdsx a30mvxigxkghc5cdsvxvyv0ja

#> 1 B A

#> 2 C C

#> 3 B B

#> 4 C B

#> 5 A C

#> ... ... ...

...but group_by()⁴ does not, so we must wrap it in across()⁵.

# |---------------------|

data %>% group_by(across(all_of(columns)))

#> # A tibble: 100 × 3

#> # Groups: asihckhdoydkhxiydfgfTgdsx, a30mvxigxkghc5cdsvxvyv0ja [9]

#> asihckhdoydkhxiydfgfTgdsx a30mvxigxkghc5cdsvxvyv0ja value

#> <chr> <chr> <dbl>

#> 1 B A 1.61

#> 2 C C -2.31

#> 3 B B 1.06

#> 4 C B -0.612

#> 5 A C -0.260

#> ... ... ...

Quasiquotation

Another approach is using quasiquotation⁶ to build our code dynamically. Here we convert the column names into a list of symbols⁷, which we "splice" into our group_by() using the !!! operator⁸.

col_syms <- syms(columns)

col_syms

#> [[1]]

#> asihckhdoydkhxiydfgfTgdsx

#>

#> [[2]]

#> a30mvxigxkghc5cdsvxvyv0ja

# |---------|

data %>% group_by(!!!col_syms)

#> # A tibble: 100 × 3

#> # Groups: asihckhdoydkhxiydfgfTgdsx, a30mvxigxkghc5cdsvxvyv0ja [9]

#> asihckhdoydkhxiydfgfTgdsx a30mvxigxkghc5cdsvxvyv0ja value

#> <chr> <chr> <dbl>

#> 1 B A 1.61

#> 2 C C -2.31

#> 3 B B 1.06

#> 4 C B -0.612

#> 5 A C -0.260

#> ... ... ...

This behaves the same as hard-coding the columns by hand, but it is much more convenient.

# |--------------------------------------------------|

data %>% group_by(asihckhdoydkhxiydfgfTgdsx, a30mvxigxkghc5cdsvxvyv0ja)

¹ https://tidyselect.r-lib.org/reference/language

² https://tidyselect.r-lib.org/reference/all_of

³ https://dplyr.tidyverse.org/reference/select

⁴ https://dplyr.tidyverse.org/reference/group_by

⁵ https://dplyr.tidyverse.org/reference/across

⁶ https://adv-r.hadley.nz/quasiquotation

⁷ https://adv-r.hadley.nz/expressions#symbols

⁸ https://adv-r.hadley.nz/quasiquotation#unquoting-many-arguments