问题
Suppose I have the following data frame:
> a <- data_frame(my_type_1_num_widgets = c(1, 2, 3), my_type_2_num_widgets = c(4, 5, 6))
> a
Source: local data frame [3 x 2]
my_type_1_num_widgets my_type_2_num_widgets
1 1 4
2 2 5
3 3 6
I want to do two things:
- gather the "num_widgets" columns.
- rename the resulting keys to remove the "num_widgets" suffix.
The way I'm doing this currently, and the correct/desired output that I'm getting:
> a %>%
rename(my_type_1 = my_type_1_num_widgets,
my_type_2 = my_type_2_num_widgets) %>%
gather(type, num_widgets, my_type_1:my_type_2)
Source: local data frame [6 x 2]
type num_widgets
1 my_type_1 1
2 my_type_1 2
3 my_type_1 3
4 my_type_2 4
5 my_type_2 5
6 my_type_2 6
Is there a way to do this in one step?
回答1:
Try:
a %>%
gather(type, num_widgets) %>% ## gather the "num_widgets" columns
mutate(type = sub("_num_widgets", "", type)) ## remove the suffix
Which gives:
#Source: local data frame [6 x 2]
#
# type num_widgets
#1 my_type_1 1
#2 my_type_1 2
#3 my_type_1 3
#4 my_type_2 4
#5 my_type_2 5
#6 my_type_2 6
回答2:
since tidyr 1.0.0 you can do:
library(tidyverse)
a <- tibble(my_type_1_num_widgets = c(1, 2, 3), my_type_2_num_widgets = c(4, 5, 6))
pivot_longer(a, everything(),
names_to = c("type",".value"),
names_pattern = "(.*?)_(num_widgets)") %>%
arrange(type)
#> # A tibble: 6 x 2
#> type num_widgets
#> <chr> <dbl>
#> 1 my_type_1 1
#> 2 my_type_1 2
#> 3 my_type_1 3
#> 4 my_type_2 4
#> 5 my_type_2 5
#> 6 my_type_2 6
Created on 2019-09-19 by the reprex package (v0.3.0)
来源:https://stackoverflow.com/questions/30901442/tidyr-gather-simultaneously-gather-and-rename-key