Remove consecutive duplicates from dataframe

问题:

I have a data frame that I want to remove duplicates that are consecutive (in base). I know rle may be helpful here but can't think of how to use it. The example output will help to illuminate what I'm asking for.

Generate sample data:

set.seed(12)
samps <- sample(1:5, 20, T)
dat <- data.frame(v1=LETTERS[samps], v2=month.abb[samps])
dat[10, 2] <- "Mar"

Sample data:

   v1  v2
1   A Jan
2   E May
3   E May
4   B Feb
5   A Jan
6   A Jan
7   A Jan
8   D Apr
9   A Jan
10  A Mar
11  B Feb
12  E May
13  B Feb
14  B Feb
15  B Feb
16  C Mar
17  C Mar
18  C Mar
19  D Apr
20  A Jan

Desired outcome:

   v1  v2
1   A Jan
3   E May
4   B Feb
7   A Jan
8   D Apr
10  A Mar
11  B Feb
12  E May
15  B Feb
18  C Mar
19  D Apr
20  A Jan

回答1:

Here's a way, not with rle, but a way none-the-less:

dat[with(dat, c(TRUE, diff(as.numeric(interaction(v1, v2))) != 0)), ]

This assumes you're using factor columns, as your sample data implies.

回答2:

Here a fast solution using filter

dat[(filter(dat,c(-1,1))!= 0)[,1],]
     v1   v2
1     A  Jan
3     E  May
4     B  Feb
7     A  Jan
8     D  Apr
10    A  Mar
11    B  Feb
12    E  May
15    B  Feb
18    C  Mar
19    D  Apr
NA <NA> <NA>

You need to add the last value of the original data to the result.

回答3:

Using rle I came up with this

ind <- cumsum(rle(as.character(dat$v1))$length)
dat[ind, ]

ind indicates either the first or the last of consecutive entries.

EDIT:

A simple solution to Matthews comment would be

dat[15, 2] <- "May"
dat[cumsum(rle(paste0(dat$v1, dat$v2))$length), ]