dplyr returns 不会绑定到可比数据框的数据框
dplyr returns data frame that won't rbind to comparable data frame
我知道这里有其他方法可以得到结果,但我试图理解为什么在下面的代码中使用 rbind 会产生一个列表,而不是一个数据框,尽管输入了两个明显相同的数据帧。推测与group_by操作后dplyr返回的dataframe对象有关,请问如何解决?
目的是删除 EventCode = X 的重复项(在 EventValue1 和 EventValue2 列上),但保留 EventCode = Y 的重复项。
df <- data.frame(EventID = c("1", "2", "3", "4", "5", "6", "7", "8", "9"),
EventValue1 = c("A", "A", "B", "C", "D", "E", "E", "F", "F"),
EventValue2 = c("AA", "AA", "BB", "CC", "DD", "EE", "FF", "FF", "FF"),
EventCode = c("X", "X", "X", "X", "X", "X", "X", "Y", "Y"))
# split df by event code
df.x <- subset(df, EventCode == "X")
df.y <- subset(df, EventCode == "Y")
# remove duplicates in df.x by EventValue1 and EventValue2
df.x.2 <- df.x %>%
group_by(EventValue1, EventValue2) %>%
slice(which.min(EventID))
# recombine dfs
df <- rbind(df.x.2, df.y) # this returns a list, should be a data frame
# desired outcome
# EventID EventValue1 EventValue2 EventCode
# 1 A AA X
# 3 B AA X
# 4 C AA X
# 5 D AA X
# 6 E AA X
# 7 E AA X
# 8 F FF Y
# 9 F FF Y
使用bind_rows
代替rbind
:
df <- bind_rows(df.x.2, df.y)
df
# A tibble: 8 x 4
# Groups: EventValue1, EventValue2 [7]
EventID EventValue1 EventValue2 EventCode
<fct> <fct> <fct> <fct>
1 1 A AA X
2 3 B BB X
3 4 C CC X
4 5 D DD X
5 6 E EE X
6 7 E FF X
7 8 F FF Y
8 9 F FF Y
由于您的 df.x.2
按 EventValue1
分组并且 EventValue2
rbind
失败。如果您 ungroup
数据
它会起作用
library(dplyr)
rbind(df.x.2 %>% ungroup(), df.y)
# EventID EventValue1 EventValue2 EventCode
#* <fct> <fct> <fct> <fct>
#1 1 A AA X
#2 3 B BB X
#3 4 C CC X
#4 5 D DD X
#5 6 E EE X
#6 7 E FF X
#7 8 F FF Y
#8 9 F FF Y
或者使用 dplyr
特定的 bind_rows
仍然会保持分组
bind_rows(df.x.2, df.y)
我知道这里有其他方法可以得到结果,但我试图理解为什么在下面的代码中使用 rbind 会产生一个列表,而不是一个数据框,尽管输入了两个明显相同的数据帧。推测与group_by操作后dplyr返回的dataframe对象有关,请问如何解决?
目的是删除 EventCode = X 的重复项(在 EventValue1 和 EventValue2 列上),但保留 EventCode = Y 的重复项。
df <- data.frame(EventID = c("1", "2", "3", "4", "5", "6", "7", "8", "9"),
EventValue1 = c("A", "A", "B", "C", "D", "E", "E", "F", "F"),
EventValue2 = c("AA", "AA", "BB", "CC", "DD", "EE", "FF", "FF", "FF"),
EventCode = c("X", "X", "X", "X", "X", "X", "X", "Y", "Y"))
# split df by event code
df.x <- subset(df, EventCode == "X")
df.y <- subset(df, EventCode == "Y")
# remove duplicates in df.x by EventValue1 and EventValue2
df.x.2 <- df.x %>%
group_by(EventValue1, EventValue2) %>%
slice(which.min(EventID))
# recombine dfs
df <- rbind(df.x.2, df.y) # this returns a list, should be a data frame
# desired outcome
# EventID EventValue1 EventValue2 EventCode
# 1 A AA X
# 3 B AA X
# 4 C AA X
# 5 D AA X
# 6 E AA X
# 7 E AA X
# 8 F FF Y
# 9 F FF Y
使用bind_rows
代替rbind
:
df <- bind_rows(df.x.2, df.y)
df
# A tibble: 8 x 4
# Groups: EventValue1, EventValue2 [7]
EventID EventValue1 EventValue2 EventCode
<fct> <fct> <fct> <fct>
1 1 A AA X
2 3 B BB X
3 4 C CC X
4 5 D DD X
5 6 E EE X
6 7 E FF X
7 8 F FF Y
8 9 F FF Y
由于您的 df.x.2
按 EventValue1
分组并且 EventValue2
rbind
失败。如果您 ungroup
数据
library(dplyr)
rbind(df.x.2 %>% ungroup(), df.y)
# EventID EventValue1 EventValue2 EventCode
#* <fct> <fct> <fct> <fct>
#1 1 A AA X
#2 3 B BB X
#3 4 C CC X
#4 5 D DD X
#5 6 E EE X
#6 7 E FF X
#7 8 F FF Y
#8 9 F FF Y
或者使用 dplyr
特定的 bind_rows
仍然会保持分组
bind_rows(df.x.2, df.y)