问题
I have something like this:
id role1 Approved by Role1 role2 Approved by Role2
1 Amy 1/1/2019 David 4/4/2019
2 Bob 2/2/2019 Sara 5/5/2019
3 Adam 3/3/2019 Rachel 6/6/2019
I want something like this:
id Name Role Approved
1 Amy role1 1/1/2019
2 Bob role1 2/2/2019
3 Adam role1 3/3/2019
1 David role2 4/4/2019
2 Sara role2 5/5/2019
3 Rachel role2 6/6/2019
I thought something like this would work
melt(df,id.vars= id,
measure.vars= list(c("role1", "role2"),c("Approved by Role1", "Approved by Role2")),
variable.name= c("Role","Approved"),
value.name= c("Name","Date"))
but i am getting Error: measure variables not found in data:c("role1", "role2"),c("Approved by Role1", "Approved by Role2")
I have tried replacing this with the number of the columns as well and haven't had any luck.
Any suggestions?? Thanks!
回答1:
I really like the new tidyr::pivot_longer()
function. It's still only available in the dev version of tidyr
, but should be released shortly. First I'm going to clean up the column names slightly, so they have a consistent structure:
> df
# A tibble: 3 x 5
id name_role1 approved_role1 name_role2 approved_role2
<dbl> <chr> <chr> <chr> <chr>
1 1 Amy 1/1/2019 David 4/4/2019
2 2 Bob 2/2/2019 Sara 5/5/2019
3 3 Adam 3/3/2019 Rachel 6/6/2019
Then it's easy to convert to long format with pivot_longer()
:
library(tidyr)
df %>%
pivot_longer(
-id,
names_to = c(".value", "role"),
names_sep = "_"
)
Output:
id role name approved
<dbl> <chr> <chr> <chr>
1 1 role1 Amy 1/1/2019
2 1 role2 David 4/4/2019
3 2 role1 Bob 2/2/2019
4 2 role2 Sara 5/5/2019
5 3 role1 Adam 3/3/2019
6 3 role2 Rachel 6/6/2019
来源:https://stackoverflow.com/questions/57549204/wide-to-long-multiple-columns-issue