Dplyr Mutate Function to "Transmute"?
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...
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.
2 Answers
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)
try this.. brfss %>% spread(key = gender, value = gender) %>% select(hours1, Male, Female, count)
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