CODEWITHSUNDEEP
rstringrdplyr
feder80
feder80

Reputation: 1361

Extract strings from filename and create new columns using mutate

I have a data.frame with two columns. In the second column are filenames.

df  <- data.frame(paragraph = "Lorem ipsum dolor sit amet, consetetur sadipscing elitr, sed diam nonumy eirmod tempor invidunt ut labore et dolore magna aliquyam erat, sed diam voluptua.",
             filename = "./data/RevCon_2015_C1_Austria_05_06.txt", stringsAsFactors = FALSE)

How can I extract certain strings (using stringr) from this second column and add them (using dplyr::mutate) as additional variables (conference, year, country, etc.) so that I get the following result:

df2  <- data.frame(paragraph = "Lorem ipsum dolor sit amet, consetetur sadipscing elitr, sed diam nonumy eirmod tempor invidunt ut labore et dolore magna aliquyam erat, sed diam voluptua.",
              filename = "./data/RevCon_2015_C1_Austria_05_06.txt", conference = "RevCon", year = "2015", country= "Austria", date = "06.05.2015", stringsAsFactors = FALSE)

Upvotes: 2

Views: 1103

Answers (2)

acylam
acylam

Reputation: 18681

Here are two different approaches using separate and extract from tidyr:

library(dplyr)
library(tidyr)

df %>%
  mutate(filename2 = gsub("^(\\w+)_(\\d+)_.+?_(\\w+)_(\\d{2})_(\\d{2}).+$", 
                          "\\1_\\2_\\3_\\5.\\4.\\2", basename(filename))) %>%
  separate(filename2, c("conference", "year", "country", "date"), sep = "_")

or with extract:

df %>%
  extract(filename, c("conference", "year", "country", "day", "month"),
          "^.+/(\\w+)_(\\d+)_.+?_(\\w+)_(\\d{2})_(\\d{2}).+$",
          remove = FALSE) %>%
  unite(date, month, day, year, sep = ".", remove = FALSE) %>%
  select(paragraph, filename, conference, year, country, date)

Result:

                                                                   paragraph
1 Lorem ipsum dolor sit amet, consetetur sadipscing elitr, sed diam nonumy eirmod tempor invidunt ut labore et dolore magna aliquyam erat, sed diam voluptua.
                                 filename conference year country       date
1 ./data/RevCon_2015_C1_Austria_05_06.txt     RevCon 2015 Austria 06.05.2015

Notes:

  1. The first approach uses gsub to match each "column" we want using capture groups, and re-order as desired. Notice that _ is added in to distinguish between columns
    • I used the basename function to extract everything after the last /
    • separate is then used to split the elements into actual columns with _ being the separator
  2. The second approach uses the same regex but instead of rearranging, extract treats each capture group as a separate column
    • unite binds month, day and year together without removing the original columns
    • Finally select removes day and month and rearranges the column order

Upvotes: 0

Maurits Evers
Maurits Evers

Reputation: 50718

We can do the following using tidyr::separate:

library(tidyverse);
df %>%
    mutate(tmp = gsub("(\\./data/|\\.txt)", "", filename)) %>%
    separate(
        tmp,
        into = c("conference", "year", "ignored", "country", "month", "day")) %>%
    mutate(date = paste(day, month, year, sep = "/")) %>%
    select(-ignored, -month, -day)
#          paragraph                                filename conference year
#1 Lorem ipsum [...] ./data/RevCon_2015_C1_Austria_05_06.txt     RevCon 2015
#  country        date
#1 Austria  06/05/2015

Note this assumes that filenames adhere to the following pattern: ./data/{conference}_{year}_{ignored}_{country}_{month}_{day}.txt

Sample data

df  <- data.frame(
    paragraph = "Lorem ipsum [...]",
    filename = "./data/RevCon_2015_C1_Austria_05_06.txt",
    stringsAsFactors = FALSE)

Upvotes: 2

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