parsing list string vector to multiple column data.table - r

Question

I am trying to convert data of form:
dt <- data.table(foo = c(c('a=a1|b=b1'),c('a=a2|b=b2|c=c2'),c('a=a3|d=d3')))
to form:
data.table(a=c('a1','a2','a3'),b=c('b1','b2',NA),c=c(NA,'c2',NA),d=c(NA,NA,'d3'))
I tried to parse first step using:
lapply(dt$foo, function(x) unlist(strsplit(x, split = '|', fixed = T)))
but couldn't proceed further. Any pointers?

Answer 1

Will update if more cases are provided. This is not a data.table because I don't use it, but afaik it should still work? Maybe if coerced to data.frame first.
library(tidyverse)
dt <- tibble(foo = c(c('a=a1|b=b1'),c('a=a2|b=b2|c=c2'),c('a=a3|d=d3')))
tibble(a=c('a1','a2','a3'),b=c('b1','b2',NA),c=c(NA,'c2',NA),d=c(NA,NA,'d3'))
#> # A tibble: 3 x 4
#> a b c d
#> <chr> <chr> <chr> <chr>
#> 1 a1 b1 <NA> <NA>
#> 2 a2 b2 c2 <NA>
#> 3 a3 <NA> <NA> d3
dt %>%
mutate(foo = str_split(foo, pattern = "\\|")) %>%
rowid_to_column() %>%
unnest() %>%
separate(foo, into = c("col", "val"), sep = "=") %>%
spread(col, val)
#> # A tibble: 3 x 5
#> rowid a b c d
#> <int> <chr> <chr> <chr> <chr>
#> 1 1 a1 b1 <NA> <NA>
#> 2 2 a2 b2 c2 <NA>
#> 3 3 a3 <NA> <NA> d3
Created on 2018-04-12 by the reprex package (v0.2.0).

Answer 2

Converting my comment to an answer, you can try:
library(splitstackshape)
cSplit(dt[, row := .I], "foo", "|", "long")[
, cSplit(.SD, "foo", "=")][
, dcast(.SD, row ~ foo_1, value.var = "foo_2")]
# row a b c d
# 1: 1 a1 b1 <NA> <NA>
# 2: 2 a2 b2 c2 <NA>
# 3: 3 a3 <NA> <NA> d3
You can, of course, also just use a combination of strsplit, tstrsplit, and dcast as well.
dt[, unlist(strsplit(foo, "|", TRUE)), 1:nrow(dt)][
, c("col", "val") := tstrsplit(V1, "=", fixed = TRUE)][
, dcast(.SD, nrow ~ col, value.var = "val")]
# nrow a b c d
# 1: 1 a1 b1 <NA> <NA>
# 2: 2 a2 b2 c2 <NA>
# 3: 3 a3 <NA> <NA> d3

Answer 3

An option is to use read.table function to read values as key-value pair and then finally convert into data.frame. The dplyr::bind_rows can help to join different rows.
dt <- data.table(foo = c(c('a=a1|b=b1'),c('a=a2|b=b2|c=c2'),c('a=a3|d=d3')))
library(dplyr)
bind_rows(mapply(function(x){
t <- read.table(text = gsub("\\|","\n",x), sep=c("="), stringsAsFactors=FALSE)
t <- as.data.frame(t(t), stringsAsFactors = FALSE)
colnames(t) <- t[1,]
t <- t[-1,]
}, dt$foo))
# a b c d
# 1 a1 b1 <NA> <NA>
# 2 a2 b2 c2 <NA>
# 3 a3 <NA> <NA> d3
UPDATED: data.table based solution as suggested by #abhiieor will be as:
library(data.table)
rbindlist(mapply(function(x){
t <- read.table(text = gsub("\\|","\n",x), sep=c("="), stringsAsFactors=FALSE)
t <- as.data.frame(t(t), stringsAsFactors = FALSE)
colnames(t) <- t[1,]
t <- t[-1,]
}, dt$foo), use.names = T, fill = T)