Scale data relative to its value on a date — scale_to

Pick a date and provide some variables. Those variables will be adjusted to be relative to their value on that date. Usually used to calculate foot traffic growth relative to a certain date.

scale_to_date(
  data,
  adj_vars,
  date,
  date_var = "date",
  by = NULL,
  growth = TRUE,
  format_percent = FALSE,
  accuracy = 0.1
)

Arguments

data: Any type of data set that can be coerced to a data.table. Note that a data.table will be returned.
adj_vars: Character vector of the variable names you'd like adjusted to be relative to the date.
date: The date you'd like everything relative to, as a date object.
date_var: The name of the date variable, as a string.
by: Character vector of the variable names you'd like the operation to be performed by. There should only be one observation for which date_var == date within each combination of the by variables, or else your results will be arbitrary.
growth: Set to TRUE to get new/old - 1 (i.e. a percentage growth). Set to FALSE to get new/old (i.e. a relative value).
format_percent: Set to TRUE to get back a formatted percentage, i.e. "50%", instead of a number.
accuracy: If format_percent = TRUE, the number of digits after the decimal place to round to, as in scales::percent.

Examples


# Create some data to scale relative to
patterns <- data.table(date = c(lubridate::ymd('2020-01-15'),
                                lubridate::ymd('2020-01-16'),
                                lubridate::ymd('2020-01-17')),
                                visits_by_day = c(1,2,3))
#> Error in data.table(date = c(lubridate::ymd("2020-01-15"), lubridate::ymd("2020-01-16"),     lubridate::ymd("2020-01-17")), visits_by_day = c(1, 2, 3)): could not find function "data.table"

# Make everything relative to January 15!
scale_to_date(patterns, 'visits_by_day', lubridate::ymd('2020-01-15'))[]
#> Error in data.table::is.data.table(data): object 'patterns' not found