splitting a column delimiter R - r

Question

I have a dataframe as below. I want to split the last column into 2. Splitting needs to be done based upon the only first : and rest of the columns dont matter.
In the new dataframe, there will be 4 columns. 3 rd column will be (a,b,d) while 4th column will be (1,2:3,3:4:4)
any suggestions? 4th line of my code doesnt work :(. I am okay with completely new solution or corrections to the line 4
employee <- c('John Doe','Peter Gynn','Jolie Hope')
salary <- c(3, 2, 1)
df <- data.frame(employee, salary, originalColumn = c("a :1", "b :2:3", "d: 3:4:4"))
as.data.frame(do.call(rbind, strsplit(df,":")))
--------------------update1
Below solutions work well. But i need a modified solution as I just realized that some of the cells in column 3 wont have ":". In such case i want text in that cell to appear in only 1st column after splitting that column
employee <- c('John Doe','Peter Gynn','Jolie Hope')
salary <- c(3, 2, 1)
df <- data.frame(employee, salary, originalColumn = c("a :1", "b", "d: 3:4:4"))

Answer 1

You could use cSplit. On your updated data frame,
library(splitstackshape)
cSplit(df, "originalColumn", sep = ":{1}")
# employee salary originalColumn_1 originalColumn_2
# 1: John Doe 3 a 1
# 2: Peter Gynn 2 b NA
# 3: Jolie Hope 1 d 3:4:4
And on your original data frame,
df1 <- data.frame(employee, salary,
originalColumn = c("a :1", "b :2:3", "d: 3:4:4"))
cSplit(df1, "originalColumn", sep = ":{1}")
# employee salary originalColumn_1 originalColumn_2
# 1: John Doe 3 a 1
# 2: Peter Gynn 2 b 2:3
# 3: Jolie Hope 1 d 3:4:4
Note: I'm using splitstackshape version 1.4.2. I believe the sep argument has been changed from version 1.4.0

Answer 2

You could use extract from tidyr to split the originalColumn in to two columns. In the below code, I am creating 3 columns and removing one of the unwanted columns from the result.
library(tidyr)
pat <- "([^ :])( ?:|: ?|)(.*)"
extract(df, originalColumn, c("Col1", "ColN", "Col2"), pat)[,-4]
# employee salary Col1 Col2
#1 John Doe 3 a 1
#2 Peter Gynn 2 b 2:3
#3 Jolie Hope 1 d 3:4:4
Using the updated df, (for better identification - df1)
extract(df1, originalColumn, c("Col1", "ColN", "Col2"), pat)[,-4]
# employee salary Col1 Col2
#1 John Doe 3 a 1
#2 Peter Gynn 2 b
#3 Jolie Hope 1 d 3:4:4
Or without creating a new column in df
extract(df, originalColumn, c("Col1", "Col2"), "(.)[ :](.*)") %>%
mutate(Col2= gsub("^\\:", "", Col2))
# employee salary Col1 Col2
#1 John Doe 3 a 1
#2 Peter Gynn 2 b 2:3
#3 Jolie Hope 1 d 3:4:4
Based on the pattern in df, the below code also works. Here, the regex used to extract the first column is (.). A dot is a single element at the beginning of the string inside the parentheses will be extracted for the Col1. Then .{2} two elements following the first are discarded and the rest within the parentheses (.*) forms the Col2.
extract(df, originalColumn, c("Col1", "Col2"), "(.).{2}(.*)")
# employee salary Col1 Col2
#1 John Doe 3 a 1
#2 Peter Gynn 2 b 2:3
#3 Jolie Hope 1 d 3:4:4
or using strsplit
as.data.frame(do.call(rbind, strsplit(as.character(df$originalColumn), " :|: ")))
# V1 V2
#1 a 1
#2 b 2:3
#3 d 3:4:4
For df1, here is a solution using strsplit
lst <- strsplit(as.character(df1$originalColumn), " :|: ")
as.data.frame(do.call(rbind,lapply(lst,
`length<-`, max(sapply(lst, length)))) )
# V1 V2
#1 a 1
#2 b <NA>
#3 d 3:4:4

Answer 3

You were close, here's a solution:
library(stringr)
df[, c('Col1','Col2')] <- do.call(rbind, str_split_fixed(df$originalColumn,":",n=2))
df$originalColumn <- NULL
employee salary Col1 Col2
1 John Doe 3 a 1
2 Peter Gynn 2 b 2:3
3 Jolie Hope 1 d 3:4:4
Notes:
stringr::str_split() is better than base::strsplit() because you don't have to do as.character(), also it has the n=2 argument you want to limit to only split on the first ':'