Select columns using starts_with()-CodePudding

With select(starts_with("A") I can select all the columns in a dataframe/tibble starting with "A".

But how can I select all the columns in a dataframe/tibble starting with one of the letters in a vector?

Example:

columns_to_select <- c("A", "B", "C")
df %>% select(starts_with(columns_to_select))

I would like to select A1, A2, A3... and B1, B2, B3, ... and C1, C2, Cxy...

CodePudding user response：

This currently seems to be working the way you're describing:

library(tidyverse)

df <- tibble(A1 = 1:10, B1 = 1:10, C3 = 21:30, D2 = 11:20)

columns_to_select <- c("A", "B", "C")

df |> 
  select(starts_with(columns_to_select))
#> # A tibble: 10 × 3
#>       A1    B1    C3
#>    <int> <int> <int>
#>  1     1     1    21
#>  2     2     2    22
#>  3     3     3    23
#>  4     4     4    24
#>  5     5     5    25
#>  6     6     6    26
#>  7     7     7    27
#>  8     8     8    28
#>  9     9     9    29
#> 10    10    10    30

Do you mean to select only by one of the letters at a time? (you can use columns_to_select[1] for this) Apologies if I've misunderstood the question - can delete this response if not relevant.

CodePudding user response：

Not sure if this is relevant, but if you're passing the columns_to_select vector into a function you may need to 'unquote it' using e.g. the bang bang operator (!!):

library(tidyverse)
df <- tibble(A1 = 1:10, A2 = 1:10,
             B1 = 1:10, BB = 1:10,
             C3 = 21:30, D2 = 11:20)

columns_to_select <- c("A", "B", "C")

test <- function(df, cols) {
  df %>%
    select(starts_with(!!cols))
}

test(df, columns_to_select)
#> # A tibble: 10 × 5
#>       A1    A2    B1    BB    C3
#>    <int> <int> <int> <int> <int>
#>  1     1     1     1     1    21
#>  2     2     2     2     2    22
#>  3     3     3     3     3    23
#>  4     4     4     4     4    24
#>  5     5     5     5     5    25
#>  6     6     6     6     6    26
#>  7     7     7     7     7    27
#>  8     8     8     8     8    28
#>  9     9     9     9     9    29
#> 10    10    10    10    10    30

^{Created on 2023-01-17 with reprex v2.0.2}