DPLYR: Convert multiple columns from character to integer

user_13794366 0
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I am working with a long table, but need to convert (part of) it to a wide table to use the data in the staistical package Vegan. However, when I use the pivot-wider function, all columns end up as characters. I can't find the solution how to convert the colums (with scientific species names as headers) into integers. I've read many posts but all solutions so far won't work. The code I used to create the table:

biota_C <- (biota_species) %>%
  ungroup() %>% 
  select(Species, Station, Numbers) %>%
  pivot_wider(names_from = Station, values_from = Numbers) %>%
  t() %>%
  row_to_names(row_number = 1)

The resulting table looks fine to me except for the datatypes.Species table

> glimpse(biota_C)
 chr [1:306, 1:27] "0" "1" "0" " 0" " 1" " 2" "1" "2" "0" "4" "0" "0" "0" "0" "0" "3" "0" "1" "0" "0" "0" " 0" ...
 - attr(*, "dimnames")=List of 2
  ..$ : chr [1:306] "X00A2" "X00A4" "X00A6" "X00B2" ...
  ..$ : chr [1:27] "Aphelochaeta marioni" "Arenicola marine" "Aricidea minuta" "Bathyporeia saris" ...

Obviously I am overlooking something.

Best, Berry

dplyr character r integer type-conversion
3 Answers

You transposed the whole data.frame with the row.names, hence everything is converted to character.

try something like this:

df = data.frame(Species = rep(c("Aphelochaeta marioni","Arenicola marine","Aricidea minuta","Bathyporeia saris"),each=5),
Station=rep(letters[1:5],4),Numbers=rpois(20,20))

df %>% 
pivot_wider(names_from = Station, values_from = Numbers) %>%
column_to_rownames("Species") %>% 
t() %>% glimpse()

 int [1:5, 1:4] 15 19 19 22 27 25 20 21 17 23 ...
 - attr(*, "dimnames")=List of 2
  ..$ : chr [1:5] "a" "b" "c" "d" ...
  ..$ : chr [1:4] "Aphelochaeta marioni" "Arenicola marine" "Aricidea minuta" "Bathyporeia saris"
user_122584590

Looking at the picture of the table, you can see some additional whitespace in the species table, so the columns in this table are characters. You can use mutate_all from dplyr together with as.numeric to convert the type:

biota_C <- biota_C %>% 
  mutate_all(as.numeric)
user_126473150

We can use across with mutate in dplyr 1.0.0

library(dplyr)
biota_C <- biota_C  %>%
              mutate(across(everything(), as.numeric))
user_37322710
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