举一个像这样的示例数据框(真实的数据框有更多列):
df <- data.frame(A = seq(1, 3, 1),
B = seq(4, 6, 1))
Run Code Online (Sandbox Code Playgroud)
我可以用来pivot_longer收集我感兴趣的列(A和B),如下所示:
library(dplyr)
library(tidyr)
df <- df %>%
pivot_longer(cols = c("A", "B"), names_to = "Letter", values_to = "Number")
df
Letter Number
<chr> <dbl>
1 A 1
2 B 4
3 A 2
4 B 5
5 A 3
6 B 6
Run Code Online (Sandbox Code Playgroud)
现在假设C我的数据框中还有另一列,使其不再整洁
C <- seq(7, 12, 1)
df_2 <- data.frame(df, C)
df_2
Letter Number C
1 A 1 7
2 B 4 8
3 A 2 9
4 B 5 10
5 A 3 11
6 B 6 12
Run Code Online (Sandbox Code Playgroud)
我想pivot_longer再次使用来整理df_2并获得以下输出:
data.frame(Letter = c(rep("A", 3), rep("B", 3), rep("C", 3)),
Number = seq(1, 12, 1))
Letter Number
1 A 1
2 A 2
3 A 3
4 B 4
5 B 5
6 B 6
7 C 7
8 C 8
9 C 9
10 C 10
11 C 11
12 C 12
Run Code Online (Sandbox Code Playgroud)
但使用相同的策略会产生错误:
df_2 %>%
pivot_longer(cols = "C", names_to = "Letter", values_to = "Number")
Run Code Online (Sandbox Code Playgroud)
Run Code Online (Sandbox Code Playgroud)Error: Failed to create output due to bad names. * Choose another strategy with `names_repair`
设置names_repair为minimal运行但不会产生我想要的输出。
像这样跟随
library(tidyverse)
df <- data.frame(A = seq(1, 3, 1),
B = seq(4, 6, 1))
df <- df %>%
pivot_longer(cols = c("A", "B"), names_to = "Letter", values_to = "Number")
C <- seq(7, 12, 1)
df_2 <- data.frame(C)
df_2 <- df_2 %>% pivot_longer(cols = C, names_to = "Letter", values_to = "Number")
df_result <- rbind(df, df_2)
Run Code Online (Sandbox Code Playgroud)
输出
> df_result
# A tibble: 12 x 2
Letter Number
<chr> <dbl>
1 A 1
2 B 4
3 A 2
4 B 5
5 A 3
6 B 6
7 C 7
8 C 8
9 C 9
10 C 10
11 C 11
12 C 12
Run Code Online (Sandbox Code Playgroud)