Split variable from comma into an ordered dataframe - r

Question

I have a dataframe like this, where the values are separated by comma.
# Events
# A,B,C
# C,D
# B,A
# D,B,A,E
# A,E,B
I would like to have the next data frame
# Event1 Event2 Event3 Event4 Event5
# A B C NA NA
# NA NA C NA NA
# A B NA NA NA
# A B NA D E
# A B NA NA E
I have tried with cSplit but I don't have the desired df. Is possible?
NOTE: The values doesn't appear in the same possition as the variable Event in the second dataframe.

Answer 1

1) Here is a base R solution. split each row giving list s and create cols which contains the possible values. Then iterate over s and convert that to a data frame.
Note that this does not hard code the column names and continues to work even if some column names are substrings of other column names.
s <- strsplit(DF$Events, ",")
cols <- unique(sort(unlist(s)))
data.frame(Event = t(sapply(s, function(x) ifelse(cols %in% x, cols, NA))))
giving:
Event.1 Event.2 Event.3 Event.4 Event.5
1 A B C <NA> <NA>
2 <NA> <NA> C D <NA>
3 A B <NA> <NA> <NA>
4 A B <NA> D E
5 A B <NA> <NA> E
2) This base R solution uses strsplit as above and then names the components since stack requires a named list and then invokes stack. Then we expand that into a wide form using tapply and convert it to a data frame and fix up the names.
s <- strsplit(DF$Events, ",")
names(s) <- seq_along(s)
stk <- stack(s)
mat <- t(tapply(stk$values, stk, c))
colnames(mat) <- NULL
data.frame(Event = mat)
giving:
Event.1 Event.2 Event.3 Event.4 Event.5
1 A B C <NA> <NA>
2 <NA> <NA> C D <NA>
3 A B <NA> <NA> <NA>
4 A B <NA> D E
5 A B <NA> <NA> E
This could also be represented as an R 4.2+ pipeline:
DF |>
with(setNames(Events, seq_along(Events))) |>
strsplit(",") |>
stack() |>
with(tapply(values, data.frame(ind, values), c)) |>
`colnames<-`(NULL) |>
data.frame(Event = _)
Note
The input in reproducible form:
Lines <- "Events
A,B,C
C,D
B,A
D,B,A,E
A,E,B"
DF <- read.table(text = Lines, header = TRUE, strip.white = TRUE)

Answer 2

Another approach using tidyverse:
library(dplyr)
library(purrr)
library(stringr)
Events = c("A,B,C", 'C,D', "B,A", "D,B,A,E", "A,E,B")
letters <- Events %>% str_split(",") %>% unlist() %>% unique()
df <- data.frame(Events)
df %>%
map2_dfc(.y = letters, ~ ifelse(str_detect(.x, .y), .y, NA)) %>%
set_names(nm = paste0("Events", 1:length(letters)))
#> # A tibble: 5 × 5
#> Events1 Events2 Events3 Events4 Events5
#> <chr> <chr> <chr> <chr> <chr>
#> 1 A B C <NA> <NA>
#> 2 <NA> <NA> C D <NA>
#> 3 A B <NA> <NA> <NA>
#> 4 A B <NA> D E
#> 5 A B <NA> <NA> E
Created on 2022-07-11 by the reprex package (v2.0.1)

Answer 3

This tidyverse solution is easily the most economical in terms of amount of code used:
library(tidyverse)
data.frame(Events) %>%
# split the strings by the comma:
mutate(Events = str_split(Events, ",")) %>%
# unnest splitted values wider into columns:
unnest_wider(Events, names_sep = "")
# A tibble: 5 × 4
Events1 Events2 Events3 Events4
<chr> <chr> <chr> <chr>
1 A B C NA
2 C D NA NA
3 B A NA NA
4 D B A E
5 A E B NA
Data:
Events = c("A,B,C", 'C,D', "B,A", "D,B,A,E", "A,E,B")

Answer 4

We can try the following base R code
> d <- t(table(stack(setNames(strsplit(df$Events, ","), 1:nrow(df)))))
> as.data.frame.matrix(`dim<-`(colnames(d)[ifelse(d > 0, d * col(d), NA)], dim(d)))
V1 V2 V3 V4 V5
1 A B C <NA> <NA>
2 <NA> <NA> C D <NA>
3 A B <NA> <NA> <NA>
4 A B <NA> D E
5 A B <NA> <NA> E