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Compute Fast Summary Statistics by Group

compute_fastsummary.Rd

compute_fastsummary() computes summary statistics for selected columns of a dataset, optionally grouped by one or more variables. It allows the user to specify a set of functions to apply, either from a predefined set or custom formulas/functions.

Usage

compute_fastsummary(
  data,
  cols,
  fns = NULL,
  group_cols,
  output = c("long", "wide"),
  tbl = FALSE,
  groups = NULL
)

Arguments

data

A data.table, data.frame, or tibble. The dataset on which to compute the summaries. If not a data.table, it will be converted internally for computation. The result will be returned in the same class as the input (unless tbl = TRUE).

cols

A character vector. Names of the columns to summarize.

fns

Optional. Either:

  • NULL (default): use all default functions defined by define_fns().

  • A character vector of function names matching define_fns().

  • A list of functions or formulas, possibly mixed with character names referring to define_fns().

group_cols

A character vector. Column(s) by which to group the data before computing the summary statistics.

output

Character. Either "long" (default) or "wide" to specify the output format. "long" returns one row per group per summary statistic, "wide" returns one row per group with multiple columns for each summary statistic.

tbl

Logical. If TRUE, converts the result to a tibble (tibble::as_tibble()).

groups

Deprecated. Use group_cols instead.

Value

A dataset containing the summary statistics for the selected columns. The output will be either long or wide depending on the output argument. The returned object will match the class of the input data (unless tbl = TRUE).

Details

The function constructs the summary calls efficiently using bquote() and evaluates them within the data.table environment. This allows for fast computation even with large datasets. Custom functions can be supplied as formulas (e.g., ~ mean(.x, na.rm = TRUE)) or as pre-defined function names from define_fns().

Examples

if (FALSE) { # \dontrun{
library(data.table)
dt <- data.table(x = rnorm(100), y = rnorm(100), group = sample(1:2, 100, TRUE))
# Compute mean and sd by group
compute_fastsummary(dt, cols = c("x", "y"), fns = c("mean", "sd"), groups = "group")

# Use a custom function
compute_fastsummary(
  dt,
  cols = "x",
  fns = list(mean = ~mean(.x, na.rm = TRUE)),
  groups = "group",
  output = "long",
  tbl = TRUE
)
} # }