Separate a string of multiple dates and names in R - r

Question

I have a dataframe with 2 columns, where the first column lists companies and the second column are strings of multiple dates and company names as follows:
data=data.frame('Company'=(c("A","B","C")),
'Bank'=c("1/13/2020 Bank A 5/12/2020 Bank H C 11/9/2020 HelloBank",
"2/14/2020 HopeBank 1/9/2020 Liberty Bank SA",
"10/18/2020 Securities"))
I would like to separate column "Bank" into multiple columns of Dates and Bank Names, such that:
data=data.frame('Company'=(c("A","B","C")),
"Date1"=(c("1/13/2020","2/14/2020","10/18/2020")),
'Bank1'=c("Bank A", "HopeBank","Securities"),
"Date2"=(c("5/12/2020","1/9/2020",NA)),
'Bank2'=c("Bank H C", "Liberty Bank SA",NA),
"Date3"=(c("11/9/2020 ",NA,NA)),
'Bank3'=c("HelloBank", NA,NA))
I have tried using library(stringr) but the formats of the dates are not consistent. Also, I do not know how many variables I will need in the final dataframe, and some of the strings in the "Bank" column are very long (up to 824 nchar).
I have also tried using separate from tidyr but without success.

Answer 1

Here is a base R option using strsplit to make it
v <- strsplit(data$Bank, "\\s(?=(\\d+\\/))|(?<=\\d)\\s", perl = TRUE)
data <- cbind(
data[1],
`colnames<-`(
do.call(rbind, lapply(v, `length<-`, max(lengths(v)))),
paste0(c("Date", "Bank"), rep(1:(max(lengths(v)) / 2), each = 2))
)
)
which gives
> data
Company Date1 Bank1 Date2 Bank2 Date3 Bank3
1 A 1/13/2020 Bank A 5/12/2020 Bank H C 11/9/2020 HelloBank
2 B 2/14/2020 HopeBank 1/9/2020 Liberty Bank SA <NA> <NA>
3 C 10/18/2020 Securities <NA> <NA> <NA> <NA>

Answer 2

If you don't know how many banks there might be in each row, you are better off creating a dataframe in long format. Something like this will do it, using the tidyverse...
library(tidyverse)
data_long <- data %>%
mutate(Bank = str_replace_all(Bank, "( \\d+/)", "#\\1"), #add markers between banks
Bank = str_split(Bank, "#")) %>% #split at markers
unnest(Bank) %>% #convert to one row per entry
mutate(Bank = str_squish(Bank)) %>% #trim white space
separate(Bank, into = c("Date", "BankName"), sep = " ", extra = "merge")
data_long
Company Date BankName
<chr> <chr> <chr>
1 A 1/13/2020 Bank A
2 A 5/12/2020 Bank H C
3 A 11/9/2020 HelloBank
4 B 2/14/2020 HopeBank
5 B 1/9/2020 Liberty Bank SA
6 C 10/18/2020 Securities
You might then want to convert Date into date format.
If you really want it in wide format, use pivot_wider.