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.2EventValue1 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)