collapse (version 1.5.3)

fsummarise: Fast Summarise

Description

fsummarize is a much faster version of dplyr::summarise, when used together with the Fast Statistical Functions.

Usage

fsummarise(.data, ..., keep.group_vars = TRUE)
smr(.data, ..., keep.group_vars = TRUE)        # Shortcut

Arguments

.data

a (grouped) data frame or named list of columns. Grouped data can be created with fgroup_by or dplyr::group_by.

…

name-value pairs of summary functions. The name will be the name of the variable in the result. Functions when applied to a vector need to return a scalar. For fast performance and weighted aggregation use the Fast Statistical Functions.

keep.group_vars

logical. FALSE removes grouping variables after computation.

Value

If .data is grouped by fgroup_by or dplyr::group_by, the result is a data frame of the same class and attributes with rows reduced to the number of groups. If .data is not grouped, the result is a data frame of the same class and attributes with 1 row.

See Also

collap, Data Frame Manipulation, Fast Statistical Functions, Collapse Overview

Examples

# NOT RUN {
# Simple use
fsummarise(mtcars, mean_mpg = fmean(mpg),
                   sd_mpg = fsd(mpg))

# Using base functions (not a big difference without groups)
fsummarise(mtcars, mean_mpg = mean(mpg),
                   sd_mpg = sd(mpg))

# Grouped use
library(magrittr)
mtcars %>% fgroup_by(cyl) %>%
  fsummarise(mean_mpg = fmean(mpg),
             sd_mpg = fsd(mpg))

# This is still efficient but quite a bit slower on large data (many groups)
mtcars %>% fgroup_by(cyl) %>%
  fsummarise(mean_mpg = mean(mpg),
             sd_mpg = sd(mpg))

# Weighted aggregation
mtcars %>% fgroup_by(cyl) %>%
  fsummarise(w_mean_mpg = fmean(mpg, wt),
             w_sd_mpg = fsd(mpg, wt))

# }
# NOT RUN {
 <!-- % No code relying on suggested package -->
## Can also group with dplyr::group_by, but at a conversion cost, see ?GRP
library(dplyr)
mtcars %>% group_by(cyl) %>%
  fsummarise(mean_mpg = fmean(mpg),
             sd_mpg = fsd(mpg))

# Again less efficient...
mtcars %>% group_by(cyl) %>%
  fsummarise(mean_mpg = mean(mpg),
             sd_mpg = sd(mpg))

# }
# NOT RUN {

# }