How to strsplit data frame column and replicate rows accordingly? [duplicate]

Question

I have a data frame like this:

> df <- data.frame(Column1=c("id1", "id2", "id3"), Column2=c("text1,text2,text3", "text4", "text5,text6"), Column3=c("text7", "text8,text9,text10,text11", "text12,text13"))

> df
  Column1           Column2                   Column3
1     id1 text1,text2,text3                     text7
2     id2             text4 text8,text9,text10,text11
3     id3       text5,text6             text12,text13

How do I transform it in this format?

  Column1 variable                     value
1     id1  Column2                     text1
2     id1  Column2                     text2
3     id1  Column2                     text3
4     id2  Column2                     text4
5     id3  Column2                     text5
6     id3  Column2                     text6
7     id1  Column3                     text7
8     id2  Column3                     text8
9     id2  Column3                     text9
10    id2  Column3                    text10
11    id2  Column3                    text11
12    id3  Column3                    text12
13    id3  Column3                    text13

---

I guess the first step is to melt() the data frame (btw, should I worry about that warning?):

> library(reshape2)    
> mdf <- melt(df, id.vars="Column1", measure.vars=c("Column2", "Column3"))
> mdf
  Column1 variable                     value
1     id1  Column2         text1,text2,text3
2     id2  Column2                     text4
3     id3  Column2               text5,text6
4     id1  Column3                     text7
5     id2  Column3 text8,text9,text10,text11
6     id3  Column3             text12,text13
Warning message:
attributes are not identical across measure variables; they will be dropped

Then I would basically need to ``strsplit()` the 'value' column and replicate the rows accordingly, but I can't think of a way to do it.

> strsplit(mdf$value, ",")
[[1]]
[1] "text1" "text2" "text3"

[[2]]
[1] "text4"

[[3]]
[1] "text5" "text6"

[[4]]
[1] "text7"

[[5]]
[1] "text8"  "text9"  "text10" "text11"

[[6]]
[1] "text12" "text13"

Any help is appreciated! Thanks.

Answer 1

A data.table solution:

library(data.table)
mdt <- melt(setDT(df), id.vars="Column1")[,strsplit(as.character(value),",",fixed=TRUE),
                                          by=list(Column1,variable)]

the result:

> mdt
    Column1 variable     V1
 1:     id1  Column2  text1
 2:     id1  Column2  text2
 3:     id1  Column2  text3
....

You can also use the tstrsplit function from the latest version of data.table (v1.9.5+) which keeps the name for the value column instead of renaming it to V1:

mdt <- melt(setDT(df), id.vars="Column1")[,lapply(.SD, function(x) tstrsplit(x, ",", fixed=TRUE)),
                                          by=list(Column1,variable)]

the result:

> mdt
    Column1 variable  value
 1:     id1  Column2  text1
 2:     id1  Column2  text2
 3:     id1  Column2  text3
....

---

An alternative solution with dplyr & tidyr:

library(dplyr)
library(tidyr)
mdf <- df %>% gather(variable, value, -Column1) %>% 
  transform(value = strsplit(as.character(value),",")) %>%
  unnest(value)

the result:

> mdf
   Column1 variable  value
1      id1  Column2  text1
2      id1  Column2  text2
3      id1  Column2  text3
....

With the latest version of tidyr, you can also use the separate_rows-function:

mdf <- df %>% 
  gather(variable, value, -Column1) %>% 
  separate_rows(value)