add_headline_column: Add column of headlines

In rjake/headliner: Compose Sentences to Describe Comparisons

Add column of headlines

Description

This works similar to headline() but acts on and returns a data frame.

Usage

add_headline_column(
  df,
  x,
  y,
  headline = "{trend} of {delta} ({orig_values})",
  ...,
  .name = "headline",
  if_match = "There was no difference",
  trend_phrases = headliner::trend_terms(),
  plural_phrases = NULL,
  orig_values = "{x} vs. {y}",
  n_decimal = 1,
  round_all = TRUE,
  multiplier = 1,
  return_cols = .name
)

Arguments

df	data frame, must be a single row
x	a numeric value to compare to the reference value of 'y'
y	a numeric value to act as a control for the 'x' value
headline	a string to format the final output. Uses glue syntax
...	arguments passed to glue_data
.name	string value for the name of the new column to create
if_match	string to display if numbers match, uses glue syntax
trend_phrases	list of values to use for when x is more than y or x is less than y. You can pass it just trend_terms (the default) and call the result with "...{trend}..." or pass is a named list (see examples)
plural_phrases	named list of values to use when difference (delta) is singular (delta = 1) or plural (delta != 1)
orig_values	a string using glue syntax. example: ({x} vs {y})
n_decimal	numeric value to limit the number of decimal places in the returned values.
round_all	logical value to indicate if all values should be rounded. When FALSE, the values will return with no modification. When TRUE (default) all values will be round to the length specified by 'n_decimal'.
multiplier	number indicating the scaling factor. When multiplier = 1 (default), 0.25 will return 0.25. When multiplier = 100, 0.25 will return 25.
return_cols	arguments that can be passed to select, ex: c("a", "b"), starts_with, etc.

Details

What is nice about this function is you can return some of the "talking points" used in the headline calculation. For example, if you want to find the most extreme headlines, you can use add_headline_column(..., return_cols = delta) This will bring back a headline column as well as the delta talking point (the absolute difference between x and y). With this result, you can sort in descending order and filter for the biggest difference.

Value

Returns the original data frame with columns appended.

Examples

# You can use 'add_headline_column()' to reference values in an existing data set.
# Here is an example comparing the box office sales of different Pixar films
head(pixar_films) |>
  dplyr::select(film, bo_domestic, bo_intl) |>
  add_headline_column(
    x = bo_domestic,
    y = bo_intl,
    headline = "{film} was ${delta}M higher {trend} (${x}M vs ${y}M)",
    trend_phrases = trend_terms(more = "domestically", less = "internationally")
  ) |>
  knitr::kable("pandoc")

# You can also use 'return_cols' to return any and all "talking points".
# You can use tidyselect helpers like 'starts_with("delta")' or
# 'everything()'. In this example, I returned the 'raw_delta' & 'trend' columns
# and then identified the records at the extremes
pixar_films |>
  dplyr::select(film, bo_domestic, bo_intl) |>
  add_headline_column(
    x = bo_domestic,
    y = bo_intl,
    headline = "${delta}M {trend} (${x}M vs ${y}M)",
    trend_phrases = trend_terms(more = "higher", less = "lower"),
    return_cols = c(raw_delta, trend)
  ) |>
  dplyr::filter(raw_delta %in% range(raw_delta)) |>
  knitr::kable("pandoc")

rjake/headliner documentation built on Jan. 5, 2023, 10:41 a.m.