verbaliseR

Make your text mighty fine!

Cara Thompson
2022-10-04

Make your text mighty fine

{verbaliseR} is a collection of functions that make it easier to turn R analysis outputs into sentences. Here’s a quick example:

library(dplyr)

unique_species <- palmerpenguins::penguins %>%
  pull(species) %>%
  unique()

paste0("There are ", 
       verbaliseR::pluralise(word = "species", 
                             count = length(unique_species), 
                             plural = "species", 
                             add_or_swap = "swap"), 
       " of penguins in this dataset: ",
       verbaliseR::listify(unique_species, 
                           linking_word = "and"),
       ".")
[1] "There are three species of penguins in this dataset: Adelie, Gentoo and Chinstrap."

Installation

Install from GitHub:

# From CRAN
install.packages("verbaliseR")

# From Github...
# ... if you don't already have the {remotes} package installed:
install.packages("remotes")

# ... then:
remotes::install_github("cararthompson/verbaliseR")

Main functions

listify()

Takes a vector and returns a string where the items in the vector are listed in prose. The link word can be anything you like, and there is an option to add an Oxford comma if desired. Here are a few examples:

# The default returns a list with "and" ...
verbaliseR::listify(c("a", "b", "c"))
[1] "a, b and c"
# to which you can choose add an Oxford comma
verbaliseR::listify(c("a", "b", "c"),
                    oxford_comma = TRUE)
[1] "a, b, and c"
# You can modify the linking word...
verbaliseR::listify(c("a", "b", "c"), 
                    linking_word = "or")
[1] "a, b or c"
# ... and get quite creative with it ...
verbaliseR::listify(c(verbaliseR::listify(c("a", "b", "c"), 
                                          linking_word = "or"),
                      "d"),
                    linking_word = "but most certainly not",
                    oxford_comma = TRUE)
[1] "a, b or c, but most certainly not d"
# ... in whatever language you choose
verbaliseR::listify(c(verbaliseR::listify(c("a", "b", "c"), 
                                          linking_word = "ou"),
                      "d"),
                    linking_word = "mais jamais au grand jamais",
                    oxford_comma = TRUE)
[1] "a, b ou c, mais jamais au grand jamais d"

prettify_date()

Takes a date or string formatted as “YYYY_MM_DD” or “YYYY/MM/DD” and returns a string which is the date formatted in prose. Options include UK/US style and formal/informal (without / with the ordinals)

# Defaults to UK style, informal
verbaliseR::prettify_date(Sys.Date())
[1] "4th October 2022"
# Can also do US style
verbaliseR::prettify_date("2022/09/15", 
                          uk_or_us = "US")
[1] "September 15th, 2022"
# To remove the ordinals, select formal_or_informal = "formal"
verbaliseR::prettify_date("2022-09-15", 
                          uk_or_us = "US", 
                          formal_or_informal = "formal")
[1] "September 15, 2022"

num_to_text()

Used within pluralise() this function can also be useful on its own. It takes a number (whole number as numeric or integer) and writes it out in full, applying the following rules:

The big mark can be modified.

verbaliseR::num_to_text(3)
[1] "three"
# 0 defaults to "no", but can be changed to anything
verbaliseR::num_to_text(0)
[1] "no"
verbaliseR::num_to_text(0, zero_or_no = "none")
[1] "none"
verbaliseR::num_to_text(3, 
                        sentence_start = TRUE)
[1] "Three"
# Only whole numbers are returned as text; a warning is issued accordingly
verbaliseR::num_to_text(1.25, 
                        sentence_start = TRUE)
[1] "1.25"
# Numbers greater than 1000 are not returned as text even if they are at the start of a sentence; 
# a warning is issued accordingly
# They are however formatted for readability
verbaliseR::num_to_text(3333, 
                        sentence_start = TRUE)
[1] "3,333"
# To change the default formatting, specify a custom big_mark
verbaliseR::num_to_text(3333, 
                        sentence_start = TRUE, 
                        big_mark = " ")
[1] "3 333"

pluralise()

Takes a string and turns it into its plural, based on user input. It also retains the number, applying the rules of num_to_text() to it, unless specified otherwise. The flexibility of this function means it can be used in any language, but since numbers are currently returned only in English, users of other languages will need to specify include_number = FALSE for now if the number is between 1 and 10 or if sentence_start is TRUE.

# The default plural is an s tagged onto the end of the word ...
verbaliseR::pluralise("penguin", 3)
[1] "three penguins"
# ... but this can be changed ...
verbaliseR::pluralise("bateau", 3, 
                      plural = "x", 
                      include_number = FALSE)
[1] "bateaux"
# ... or a new word can be substituted
verbaliseR::pluralise("sheep", 3, 
                      plural = "sheep", 
                      add_or_swap = "swap")
[1] "three sheep"
# Numbers below 1001 are written out in full at the start of sentences ...
verbaliseR::pluralise("penguin", 333,
                      sentence_start = TRUE)
[1] "Three hundred and thirty-three penguins"
# ... but not in the middle of sentences
verbaliseR::pluralise("penguin", 333)
[1] "333 penguins"
# Numbers above 1000 are never written out in full but are formatted for readability ...
verbaliseR::pluralise("penguin", 33333,
                      sentence_start = TRUE)
[1] "33,333 penguins"
# ... with a customisable big mark to allow for different conventions
verbaliseR::pluralise("penguin", 33333,
                      big_mark = " ")
[1] "33 333 penguins"
# Numbers with decimals are always left as numerals and aren't formatted
verbaliseR::pluralise("unit", 12345.67)
[1] "12345.67 units"

restore_capitals()

Takes a string in which some or all capitalisation has been lost, and restores capitals in the specified items.

x <- "Should i tell c-3po the french call him z-6po?"

verbaliseR::restore_capitals(x, c("I", "C-3PO", "French", "Z-6PO"))
[1] "Should I tell C-3PO the French call him Z-6PO?"

Further information

Citation

For attribution, please cite this work as

Thompson (2022, Oct. 4). Building stories with data: verbaliseR. Retrieved from https://www.cararthompson.com/shinyApps/2022-10-05-verbaliser/

BibTeX citation

@misc{thompson2022verbaliser,
  author = {Thompson, Cara},
  title = {Building stories with data: verbaliseR},
  url = {https://www.cararthompson.com/shinyApps/2022-10-05-verbaliser/},
  year = {2022}
}