inst/doc/grouping.R

In dplyr: A Grammar of Data Manipulation

## ----echo = FALSE, message = FALSE, warning = FALSE---------------------------
knitr::opts_chunk$set(collapse = T, comment = "#>")
options(tibble.print_min = 4L, tibble.print_max = 4L)

## ----message = FALSE----------------------------------------------------------
library(dplyr)

## -----------------------------------------------------------------------------
by_species <- starwars |> group_by(species)
by_sex_gender <- starwars |> group_by(sex, gender)

## -----------------------------------------------------------------------------
by_species
by_sex_gender

## -----------------------------------------------------------------------------
by_species |> tally()

by_sex_gender |> tally(sort = TRUE)

## ----group_by_with_expression-------------------------------------------------
bmi_breaks <- c(0, 18.5, 25, 30, Inf)

starwars |>
  group_by(bmi_cat = cut(mass/(height/100)^2, breaks=bmi_breaks)) |>
  tally()

## ----group_vars---------------------------------------------------------------
by_species |> group_keys()

by_sex_gender |> group_keys()

## -----------------------------------------------------------------------------
by_species |> group_indices()

## -----------------------------------------------------------------------------
by_species |> group_rows() |> head()

## -----------------------------------------------------------------------------
by_species |> group_vars()
by_sex_gender |> group_vars()

## -----------------------------------------------------------------------------
by_species |>
  group_by(homeworld) |>
  tally()

## -----------------------------------------------------------------------------
by_species |>
  group_by(homeworld, .add = TRUE) |>
  tally()

## -----------------------------------------------------------------------------
by_species |>
  ungroup() |>
  tally()

## -----------------------------------------------------------------------------
by_sex_gender |>
  ungroup(sex) |>
  tally()

## ----summarise----------------------------------------------------------------
by_species |>
  summarise(
    n = n(),
    height = mean(height, na.rm = TRUE)
  )

## -----------------------------------------------------------------------------
by_sex_gender |>
  summarise(n = n()) |>
  group_vars()

by_sex_gender |>
  summarise(n = n(), .groups = "drop_last") |>
  group_vars()

## -----------------------------------------------------------------------------
by_sex_gender |>
  summarise(n = n(), .groups = "keep") |>
  group_vars()

by_sex_gender |>
  summarise(n = n(), .groups = "drop") |>
  group_vars()

## ----select-------------------------------------------------------------------
by_species |> select(mass)

## -----------------------------------------------------------------------------
by_species |>
  arrange(desc(mass)) |>
  relocate(species, mass)

by_species |>
  arrange(desc(mass), .by_group = TRUE) |>
  relocate(species, mass)

## ----by_homeworld-------------------------------------------------------------
# Subtract off global mean
starwars |>
  select(name, homeworld, mass) |>
  mutate(standard_mass = mass - mean(mass, na.rm = TRUE))

# Subtract off homeworld mean
starwars |>
  select(name, homeworld, mass) |>
  group_by(homeworld) |>
  mutate(standard_mass = mass - mean(mass, na.rm = TRUE))

## -----------------------------------------------------------------------------
# Overall rank
starwars |>
  select(name, homeworld, height) |>
  mutate(rank = min_rank(height))

# Rank per homeworld
starwars |>
  select(name, homeworld, height) |>
  group_by(homeworld) |>
  mutate(rank = min_rank(height))

## ----filter-------------------------------------------------------------------
by_species |>
  select(name, species, height) |>
  filter(height == max(height))

## ----filter_group-------------------------------------------------------------
by_species |>
  filter_out(n() == 1) |>
  tally()

## ----slice--------------------------------------------------------------------
by_species |>
  relocate(species) |>
  slice(1)

## ----slice_min----------------------------------------------------------------
by_species |>
  filter_out(is.na(height)) |>
  slice_min(height, n = 2)