ReportSubtotal (version 0.1.2)

subtotal_section: Subtotal Section Addition Function

Description

Adds subtotal sections to a data report.

Usage

subtotal_section(
  report,
  frame,
  vars = "Population",
  aggregator = "sum",
  exclude = numeric(0),
  agg_parameter = character(0),
  subtotal_label = "All"
)

Value

The data report with subtotal sections included.

Arguments

report

A data report.

frame

Data frame summarised by the data report.

vars

Names of column(s) in the data frame aggregated in the data report.

aggregator

Function to aggregate the data with.

exclude

Vector of column indices determining which variables only require subtotal rows (as opposed to sections).

agg_parameter

Optional parameter for the aggregation function to use.

subtotal_label

Label to be used for subtotal rows.

Details

The dataset and report are factorized, and a series of reports with the same variables are then generated, but with some variables replaced by a subtotal label, which effectively concentrates all levels of those variables into one subtotal row for those variables - ultimately making up entire subtotal sections for some variables. The subtotal reports are all combined with the original report, and the combined report is sorted, sorting the subtotal label to the top for all variables.

Examples

library(dplyr)

group_by(iris, Species) %>%
summarise(sum(Petal.Length), .groups = "keep") %>%
subtotal_section(iris, vars = "Petal.Length")

group_by(mtcars, cyl, gear) %>%
summarise(mean(mpg), .groups = "keep") %>%
subtotal_section(mtcars, vars = "mpg", aggregator = "mean")

group_by(mtcars, cyl, gear) %>%
summarise(mean(mpg), mean(wt), .groups = "keep") %>%
subtotal_section(mtcars, vars = c("mpg", "wt"),
aggregator = "mean", exclude = 1:2)

group_by(iris, Species, Petal.Width) %>%
summarise(max(Sepal.Width), max(Sepal.Length), .groups = "keep") %>%
subtotal_section(iris, vars = c("Sepal.Width", "Sepal.Length"),
aggregator = "max", agg_parameter = "na.rm")

group_by(mtcars, qsec, carb, hp, gear) %>%
summarise(min(cyl), min(drat), min(wt), .groups = "keep") %>%
subtotal_section(mtcars, vars = c("cyl", "drat", "wt"),
aggregator = "min", agg_parameter = "na.rm",
subtotal_label = "Cars_Total", exclude = c(1, 4))