用 pivot_wider() 替换 spread()

Question

I've got a dataset I'm working on and editing in R with the dplyr package. My code is:

    hiphop%>%
  mutate( sex = 
    case_when(
      sex == 1 ~ "female",
      sex == 0 ~ "male"
    )
  )%>%
  group_by(sex)%>%
  summarise_at(vars(intl,vocal,classical,folk,rock,country,pop,alternative,hiphop,unclassifiable),funs(mean))%>%
  pivot_longer(c(intl,vocal,classical,folk,rock,country,pop,alternative,hiphop,unclassifiable),names_to = "genre")%>%
spread(sex,value)%>%
  mutate(
    genredifference = abs(female-male)
  )%>%
  arrange(genredifference)%>%
  top_n(3)

Where I get this output:

Selecting by genredifference
# A tibble: 3 x 4
  genre   female  male genredifference
  <chr>    <dbl> <dbl>           <dbl>
1 country  0.786 0.392           0.394
2 vocal    0.880 1.57            0.688
3 rock     1.93  3.06            1.13 

I would like to get the same output but by replacing the spread() function with pivot_wider() (I believe that would be the one to be used). However, I cannot figure out how to do it.

Thank you!

PS: This is my dataset, in case you are interested:

hiphop <- read_csv("https://www.dropbox.com/s/5d8fwxrj3jtua1z/hiphop.csv?dl=1")

Answer 1

Based on the dropbox input data, some of the steps were already done. We can make some steps more compact by utilizing the select_helpers ie if we have a range of columns to select, use : , similarly in pivot_longer , we can also specify the columns not to be selected with - . With pivot_wider , make sure to specify the arguments ( names_from , values_from ) as there are other arguments as well and without specifying arguments, it could match the arguments in the order of occurence

library(dplyr)
library(tidyr)
 hiphop %>%  
    group_by(sex)%>%
    summarise_at(vars(intl:unclassifiable), mean) %>%
    pivot_longer(cols = -sex) %>% 
    pivot_wider(names_from = sex, values_from = value) %>%
    mutate(genredifference = abs(Female-Male))%>%
    arrange(genredifference)%>%
    top_n(3)
# A tibble: 3 x 4
#  name    Female  Male genredifference
#  <chr>    <dbl> <dbl>           <dbl>
#1 country  0.786 0.392           0.394
#2 vocal    0.880 1.57            0.688
#3 rock     1.93  3.06            1.13