collapse consecutively repeated rows and group by other varibales

[veda]

Dear R experts,

I would like to collapse rows if a condition repeats in the following rows. For example, the original data is as follows
dataset <- data.frame(id = c("a",'a','a','a', "b", "b",'b','b'),
id2 = c("1","2","2","2", "1","1","2",'1'),
text = c("gi", "hi",'ed','ew', "ic",'ia',"ws",'er'),
stringsAsFactors = FALSE)
for id=='a', variable id2 repeats consecutively for three times (2,2,2);
for id=='b', variable id2 repeats consecutively for two times(1,1);
I would like to merge the text variable if id2 repeated in the following rows and results in dataset2.

dataset2 <- data.frame(id = c("a",'a', "b", "b",'b'),
id2 = c("1", "2", "1","2",'1'),
text = c("gi", "hi ed ew", "ic ia","ws",'er'),
stringsAsFactors = FALSE)

Do you have suggestion to achieve it? Thank you very much.

Best wishes,
Veda

[mishabalyasin]

Hi!

To help us help you, could you please prepare a reproducible example (reprex)? You are almost there with what you have right now, so please have a look at this guide, to see how to create one:

FAQ: How to do a minimal reproducible example ( reprex ) for beginners

A minimal reproducible example consists of the following items: A minimal dataset, necessary to reproduce the issue The minimal runnable code necessary to reproduce the issue, which can be run on the given dataset, and including the necessary information on the used packages. Let's quickly go over each one of these with examples: Minimal Dataset (Sample Data) You need to provide a data frame that is small enough to be (reasonably) pasted on a post, but big enough to reproduce your issue. Let's say, as an example, that you are working with the iris data frame head(iris) #> Sepal.Length Sepal.Width Petal.Length Petal.Width Species #> 1 5.1 3.5 1.4 0.…

Also, take a look at rle function. I think, it can help you in this case.

[Yarnabrina]

I think the following does what you want:

library(dplyr)
#> 
#> Attaching package: 'dplyr'
#> The following objects are masked from 'package:stats':
#> 
#>     filter, lag
#> The following objects are masked from 'package:base':
#> 
#>     intersect, setdiff, setequal, union

input_dataset <- data.frame(id = c("a",'a','a','a', "b", "b",'b','b'),
                            id2 = c("1","2","2","2", "1","1","2",'1'),
                            text = c("gi", "hi",'ed','ew', "ic",'ia',"ws",'er'),
                            stringsAsFactors = FALSE)

expected_dataset <- data.frame(id = c("a",'a', "b", "b",'b'),
                               id2 = c("1", "2", "1","2",'1'),
                               text = c("gi", "hi ed ew", "ic ia","ws",'er'),
                               stringsAsFactors = FALSE)

output_dataset <- input_dataset %>%
  mutate(ID = paste0(id, id2)) %>%
  transform(ID2 = rep.int(x = seq(length(x = rle(x = ID)$values)),
                          times = rle(x = ID)$lengths)) %>%
  group_by(ID2) %>%
  mutate(text = paste0(text, collapse = " ")) %>%
  ungroup() %>%
  distinct() %>%
  select(-ID, -ID2) %>%
  as.data.frame()

all.equal(target = expected_dataset,
          current = output_dataset)
#> [1] TRUE

^{Created on 2019-03-25 by the reprex package (v0.2.1)}

[veda]

It does wonders. Thank you so much.