patperu/example.csv

## example.csv

          
            ID
            TITLE
            PRODUCT
            COUNTRY
            DATE

            
              ABC123
              EVENT A
              PRODUCT A, PRODUCT B
              COUNTRY A, COUNTRY B
              GG-MM.YYYY

            
              ABC124
              EVENT A
              PRODUCT C, PRODUCT D, PRODUCT E
              COUNTRY C, COUNTRY D, COUNTRY E
              GG-MM.YYYY

            
              ABC125
              EVENT A
              PRODUCT F, PRODUCT G
              COUNTRY F, COUNTRY G, COUNTRY H
              GG-MM.YYYY

## example_tidy.csv

          
            ID
            TITLE
            DATE
            PRODUCT
            COUNTRY

            
              ABC123
              EVENT A
              GG-MM.YYYY
              PRODUCT A
              COUNTRY A

            
              ABC123
              EVENT A
              GG-MM.YYYY
              PRODUCT B
              COUNTRY B

            
              ABC124
              EVENT A
              GG-MM.YYYY
              PRODUCT C
              COUNTRY C

            
              ABC124
              EVENT A
              GG-MM.YYYY
              PRODUCT D
              COUNTRY D

            
              ABC124
              EVENT A
              GG-MM.YYYY
              PRODUCT E
              COUNTRY E

            
              ABC125
              EVENT A
              GG-MM.YYYY
              PRODUCT F
              COUNTRY F

            
              ABC125
              EVENT A
              GG-MM.YYYY
              PRODUCT G
              COUNTRY G

            
              ABC125
              EVENT A
              GG-MM.YYYY
              NA
              COUNTRY H

## map_split.R
library(stringr)
library(dplyr)
library(tidyr)
library(purrr)
library(readr)

x <- read_csv("example.csv")
x

vars <- c("PRODUCT", "COUNTRY")

xt <- x %>%
      map_at(vars, ~str_split(., ", ")) %>%
      as_data_frame()

(c1 <- xt %>% select(-PRODUCT) %>% unnest() %>% mutate(idd = 1:n()))
(p1 <- xt %>% select(-COUNTRY) %>% unnest() %>% mutate(idd = 1:n()))

fin <- full_join(p1, c1, by = c("ID", "TITLE", "DATE", "idd")) %>% select(-idd)
fin

write_csv(fin, "example_tidy.csv")
ID	TITLE	PRODUCT	COUNTRY	DATE
ABC123	EVENT A	PRODUCT A, PRODUCT B	COUNTRY A, COUNTRY B	GG-MM.YYYY
ABC124	EVENT A	PRODUCT C, PRODUCT D, PRODUCT E	COUNTRY C, COUNTRY D, COUNTRY E	GG-MM.YYYY
ABC125	EVENT A	PRODUCT F, PRODUCT G	COUNTRY F, COUNTRY G, COUNTRY H	GG-MM.YYYY
	library(stringr)
	library(dplyr)
	library(tidyr)
	library(purrr)
	library(readr)

	x <- read_csv("example.csv")
	x

	vars <- c("PRODUCT", "COUNTRY")

	xt <- x %>%
	map_at(vars, ~str_split(., ", ")) %>%
	as_data_frame()

	(c1 <- xt %>% select(-PRODUCT) %>% unnest() %>% mutate(idd = 1:n()))
	(p1 <- xt %>% select(-COUNTRY) %>% unnest() %>% mutate(idd = 1:n()))

	fin <- full_join(p1, c1, by = c("ID", "TITLE", "DATE", "idd")) %>% select(-idd)
	fin

	write_csv(fin, "example_tidy.csv")