Calculate percentiles for a numeric variable — summarise

Summarises a numeric variable by calculating specified percentiles, optionally grouped by period and other grouping variables. Useful for creating percentile distributions over time or across different measures.

Usage

summarise_percentiles(
  df,
  period_col,
  value_col,
  percentiles = seq(0.1, 0.9, 0.1),
  group_by = NULL
)

Arguments

df: Data frame or tibble containing the data to summarise
period_col: Column name for the period variable, used for ordering results. Typically a date column e.g., end_date
value_col: Column name for the numeric variable to calculate percentiles
percentiles: Numeric vector of percentiles to calculate, specified as proportions between 0 and 1. Default is seq(0.1, 0.9, 0.1) (10th to 90th percentiles by 10s)
group_by: Optional grouping variables. Can be a single column name or a vector of column names using c(). Default is NULL.

Value

A tibble with columns for the period, percentile values, calculated values, and any grouping variables.

Examples

if (FALSE) { # \dontrun{
# Calculate percentiles by period
data |>
  summarise_percentiles(
    period_col = end_date,
    value_col = recovery_rate
  )

# Calculate quartiles grouped by measure
data |>
  summarise_percentiles(
    period_col = end_date,
    value_col = value,
    percentiles = c(0.25, 0.5, 0.75),
    group_by = measure_id
  )

# Multiple grouping variables
data |>
  summarise_percentiles(
    period_col = end_date,
    value_col = value,
    group_by = c(measure_id, region_name)
  )
} # }