Skip columns and specify column types in readr without warnings

General
1

Is it possible to specify col_types for a subset of columns and only import those columns, without getting warnings? I don't know in advance how many columns there will be, so I can't name them.

I have tried the following:

library(readr)

csv <- "foo,bar,baz\n1,2,3"

read_csv(csv, col_types = "nn")
#> Warning: Unnamed `col_types` should have the same length as `col_names`.
#> Using smaller of the two.
#> Warning: 1 parsing failure.
#> row col  expected    actual         file
#>   1  -- 2 columns 3 columns literal data
#> # A tibble: 1 x 2
#>     foo   bar
#>   <dbl> <dbl>
#> 1     1     2

read_csv(csv,
         col_types = cols(col_number(), col_number(), .default = col_skip()))
#> Warning: Unnamed `col_types` should have the same length as `col_names`. Using smaller of the two.

#> Warning: 1 parsing failure.
#> row col  expected    actual         file
#>   1  -- 2 columns 3 columns literal data
#> # A tibble: 1 x 2
#>     foo   bar
#>   <dbl> <dbl>
#> 1     1     2

read_csv(csv,
         skip = 1,
         col_names = c("one", "two"),
         col_types = cols(col_number(), col_number(), .default = col_skip()))
#> Warning: 1 parsing failure.
#> row col  expected    actual         file
#>   1  -- 2 columns 3 columns literal data
#> # A tibble: 1 x 2
#>     one   two
#>   <dbl> <dbl>
#> 1     1     2

Created on 2019-02-28 by the reprex package (v0.2.0.9000).

Session info 
devtools::session_info()
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#>  date     2019-02-28                  
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2

If you're getting the right functionality but just don't like the warnings, you could wrap your call in suppressWarnings()

1 Like
3

I think ideally we might relax this constraint and let you provide a list of unnamed column types in the future.

However maybe there is a different way to tackle the problem. How are you determining how many columns you want to read if you don't know how many columns there are?

4

The order of existing columns is guaranteed, but new columns are sometimes added at the end, so I know which ones I need, but I don't know how many dummy column names to create. For now I create dummy names for columns that will be skipped anyway, e.g.

read_csv(csv,
         skip = 1,
         col_names = c("one", "two", paste0("dummy", seq_len(no_of_cols - 2)),
         col_types = cols(col_number(), col_number(), .default = col_skip()))
1 Like
5

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