Is it possible to convert lines from a text file into columns to get a dataframe? - r

Question

I have a text file containing information on book title, author name, and country of birth which appear in seperate lines as shown below:
Oscar Wilde
De Profundis
Ireland
Nathaniel Hawthorn
Birthmark
USA
James Joyce
Ulysses
Ireland
Walt Whitman
Leaves of Grass
USA
Is there any way to convert the text to a dataframe with these three items appearing as different columns:
ID Author Book Country
1 "Oscar Wilde" "De Profundis" "Ireland"
2 "Nathaniel Hawthorn" "Birthmark" "USA"

Answer 1

There are built-in functions for dealing with this kind of data:
data.frame(scan(text=xx, multi.line=TRUE,
what=list(Author="", Book="", Country=""), sep="\n"))
# Author Book Country
#1 Oscar Wilde De Profundis Ireland
#2 Nathaniel Hawthorn Birthmark USA
#3 James Joyce Ulysses Ireland
#4 Walt Whitman Leaves of Grass USA

Answer 2

You can create a 3-column matrix from one column of data.
dat <- read.table('data.txt', sep = ',')
result <- matrix(dat$V1, ncol = 3, byrow = TRUE) |>
data.frame() |>
setNames(c('Author', 'Book', 'Country'))
result <- cbind(ID = 1:nrow(result), result)
result
# ID Author Book Country
#1 1 Oscar Wilde De Profundis Ireland
#2 2 Nathaniel Hawthorn Birthmark USA
#3 3 James Joyce Ulysses Ireland
#4 4 Walt Whitman Leaves of Grass USA

Answer 3

There aren't any built in functions that handle data like this. But you can reshape your data after importing.
#Test data
xx <- "Oscar Wilde
De Profundis
Ireland
Nathaniel Hawthorn
Birthmark
USA
James Joyce
Ulysses
Ireland
Walt Whitman
Leaves of Grass
USA"
writeLines(xx, "test.txt")
And then the code
library(dplyr)
library(tidyr)
lines <- read.csv("test.txt", header=FALSE)
lines %>%
mutate(
rid = ((row_number()-1) %% 3)+1,
pid = (row_number()-1) %/%3 + 1) %>%
mutate(col=case_when(rid==1~"Author",rid==2~"Book", rid==3~"Country")) %>%
select(-rid) %>%
pivot_wider(names_from=col, values_from=V1)
Which returns
# A tibble: 4 x 4
pid Author Book Country
<dbl> <chr> <chr> <chr>
1 1 Oscar Wilde De Profundis Ireland
2 2 Nathaniel Hawthorn Birthmark USA
3 3 James Joyce Ulysses Ireland
4 4 Walt Whitman Leaves of Grass USA