DPLYR Mutate function to "transmute"?

Question

I've just started picking up R a few weeks ago. I'm having some problems trying to transmute (if this is the right R term?) the gender row to column.

    > brfss %>%
    +     filter(hours1 >=1,hours1 <=24) %>%
    +     group_by(hours1, gender) %>%
    +     summarise(count = n())
    # A tibble: 48 x 3
    # Groups:   hours1 [?]
       hours1   gender count
          <int> <fctr> <int>
     1        1   Male    96
     2        1 Female   132
     3        2   Male   464
     4        2 Female   612
     5        3   Male  1433
     6        3 Female  2063
     7        4   Male  5749
     8        4 Female  8512
     9        5   Male 13231
    10        5 Female 20205

    # ... with 38 more rows

I want to display the column as:

    hours1   Male  Female count

basically transmuting the whole Male/Female to column instead of rows. Can someone give me some pointers? thanks.

Possible duplicate of R how to create pivot table-like data frame while 3 variables are involved? — Psidom
Thanks for the reply, I've already checked that post, its not really to do with obtaining a mean of a value (I would probably use transmute/summarise for those), rather transmuting the whole gender from row to column. But let me google on Dcast from reshape2 — junhao82

Samuel Samuel · Accepted Answer · 2017-10-14T01:11:06

You can try something like this:

library(dplyr)
library(tidyr)
library(magrittr)

brfss2013 %>% 
  select(hours1 = sleptim1, gender = sex) %>% 
  na.omit() %>%
  group_by(hours1, gender) %>%
  summarize(count = n()) %>%
  spread(key = gender, value = count)

DPLYR Mutate function to "transmute"?

2 Answers