reaggregate_counts: Reaggregate age counts

In ageutils: Collection of Functions for Working with Age Intervals

Reaggregate age counts

Description

reaggregate_counts() converts counts over one interval range to another with optional weighting by a known population.

Usage

reaggregate_counts(
  bounds,
  counts,
  new_bounds,
  ...,
  population_bounds = NULL,
  population_weights = NULL
)

Arguments

bounds	⁠[numeric]⁠ The current boundaries in (strictly) increasing order. These correspond to the left hand side of the intervals (e.g. the closed side of [x, y). Double values are coerced to integer prior to categorisation.
counts	⁠[numeric]⁠ Vector of counts corresponding to the intervals defined by bounds.
new_bounds	⁠[numeric]⁠ The desired boundaries in (strictly) increasing order.
...	Further arguments passed to or from other methods.
population_bounds	⁠[numeric]⁠ Interval boundaries for a known population weighting given by the population_weights argument.
population_weights	⁠[numeric]⁠ Population weightings corresponding to population_bounds. Used to weight the output across the desired intervals. If NULL (default), counts are divided proportional to the interval sizes.

Value

A data frame with 4 entries; interval, lower, upper and a corresponding count.

Examples

# Reaggregating some data obtained from the 2021 UK census
head(pop_dat)

# Each row of the data is for the same region so we can drop some columns
# `age_category` and `value` columns
dat <- subset(pop_dat, select = c(age_category, value))

# Add the lower bounds to the data
dat <- transform(
    dat,
    lower_bound = as.integer(sub("\\[([0-9]+), .+)", "\\1", age_category))
)

# Now recategorise to the desired age intervals
with(
    dat,
    reaggregate_counts(
        bounds = lower_bound,
        counts = value,
        new_bounds = c(0, 1, 5, 15, 25, 45, 65)
    )
)

ageutils documentation built on Aug. 8, 2025, 6:06 p.m.