Report the number of distinct values in a column across data frames

This function is intended to mimic dplyr::n_distinct() for multiple inputs. It is useful to report the number of clients throughout a series of inclusion or exclusion steps. A use case could be getting the Ns for the sample definition flowchart in an epidemiological study. It is also useful for inline reporting of Ns in an R Markdown document.

Usage

report_n(..., on, force_proceed = getOption("healthdb.force_proceed"))

Arguments

...

Data frames or remote tables (e.g., from 'dbplyr')

on

The column to report on. It must be present in all data sources.

force_proceed

A logical for whether to ask for user input in order to proceed when the data is not local data.frames, and a query needs to be executed before reporting. The default is fetching from options (FALSE). Use options(healthdb.force_proceed = TRUE) to suppress the prompt once and for all. In non-interactive sessions (e.g., scripts run via Rscript, knitr), the confirmation prompt cannot be displayed, and the function stops with an error unless force_proceed = TRUE.

Value

A sequence of the number of distinct on values, one for each input

Examples

# some exclusions
iris_1 <- subset(iris, Petal.Length > 1)
iris_2 <- subset(iris, Petal.Length > 2)

# get n at each operation
n <- report_n(iris, iris_1, iris_2, on = Species)
n
#> [1] 3 3 2

# get the difference at each step
diff(n)
#> [1]  0 -1
# data in a list
iris_list <- list(iris_1, iris_2)
report_n(rlang::splice(iris_list), on = Species)
#> [1] 3 2
# if you loaded tidyverse, this will also work
# report_n(!!!iris_list, on = Species)