Find identical observations in a column´s data frame but different in another column

Question

In R, I have a data frame which includes a ID column. I need to find all the rows that have the same ID but are different in the X1 variable.

For example,

d

ID    X1     X2
a    19      F
b    19      F
c    16      T
a    16      T 
a    19      T
d    17      T 
b    15      F 
b    19      F
c    17      T
c    17      T
d    17      T
e    15      T
f    14      T
g    16      T

The result will be:

df1

ID    X1     X2
a    19      F
b    19      F
c    16      T
a    16      T 
b    15      F 
c    17      T

Answer 1

t      <- table(d$X1, d$ID)
t[t>1] <- 1
t      <- apply(t,2,sum)
t      <- t[t>1]

d1 <- data.frame(ID = names(t))
d1 <- merge(d1, d, by = "ID", all.x=T,all.y=F)
d1 <- unique(d1[,1:2])
d1

 ID X1 1 a 19 2 a 16 4 b 15 5 b 19 7 c 16 8 c 17

We can include the 3rd column as well, but you'd need to give some logic to pick which value of it to retain. For instance, there were 2 values of a where X1 was 19, one with X2 T and one where it was F. To choose between the 2 you could keep the first matching row for X2 , the last, or choose T above F, etc.

Answer 2

We can remove the single ids first. Then get a count of the ids left. If there is a single id left we remove it:

newdf <- df1[duplicated(df1$ID, fromLast=TRUE),]
tbl <- table(newdf$ID)
newdf[!newdf$ID %in% names(tbl[tbl < 2]),]
#   ID X1    X2
# 1  a 19 FALSE
# 2  b 19 FALSE
# 3  c 16  TRUE
# 4  a 16  TRUE
# 7  b 15 FALSE
# 9  c 17  TRUE

Answer 3

这行得通吗？

df1[rownames(unique(df1[,c("ID","X1")])),]