dplyr.R
In dplyr: A Grammar of Data Manipulation

## ----echo = FALSE, message = FALSE--------------------------------------------
knitr::opts_chunk$set(collapse = T, comment = "#>")
options(tibble.print_min = 4L, tibble.print_max = 4L)
library(dplyr)
set.seed(1014)

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dim(starwars)
starwars

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starwars |> filter(skin_color == "light", eye_color == "brown")

## ----eval = FALSE-------------------------------------------------------------
# starwars[starwars$skin_color == "light" & starwars$eye_color == "brown", ]

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starwars |> arrange(height, mass)

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starwars |> arrange(desc(height))

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starwars |> slice(5:10)

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starwars |> slice_head(n = 3)

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starwars |> slice_sample(n = 5)
starwars |> slice_sample(prop = 0.1)

## -----------------------------------------------------------------------------
starwars |> slice_max(height, n = 3)

## -----------------------------------------------------------------------------
# Select columns by name
starwars |> select(hair_color, skin_color, eye_color)
# Select all columns between hair_color and eye_color (inclusive)
starwars |> select(hair_color:eye_color)
# Select all columns except those from hair_color to eye_color (inclusive)
starwars |> select(!(hair_color:eye_color))
# Select all columns ending with color
starwars |> select(ends_with("color"))

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starwars |> select(home_world = homeworld)

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starwars |> rename(home_world = homeworld)

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starwars |> mutate(height_m = height / 100)

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starwars |>
  mutate(height_m = height / 100) |>
  select(height_m, height, everything())

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starwars |>
  mutate(
    height_m = height / 100,
    BMI = mass / (height_m^2)
  ) |>
  select(BMI, everything())

## -----------------------------------------------------------------------------
starwars |>
  mutate(
    height_m = height / 100,
    BMI = mass / (height_m^2),
    .keep = "none"
  )

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starwars |> relocate(sex:homeworld, .before = height)

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starwars |> summarise(height = mean(height, na.rm = TRUE))

## ----eval = FALSE-------------------------------------------------------------
# a1 <- group_by(starwars, species, sex)
# a2 <- select(a1, height, mass)
# a3 <- summarise(a2,
#   height = mean(height, na.rm = TRUE),
#   mass = mean(mass, na.rm = TRUE)
# )

## -----------------------------------------------------------------------------
summarise(
  select(
    group_by(starwars, species, sex),
    height, mass
  ),
  height = mean(height, na.rm = TRUE),
  mass = mean(mass, na.rm = TRUE)
)

## ----eval = FALSE-------------------------------------------------------------
# starwars |>
#   group_by(species, sex) |>
#   select(height, mass) |>
#   summarise(
#     height = mean(height, na.rm = TRUE),
#     mass = mean(mass, na.rm = TRUE)
#   )

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# `name` represents the integer 1
select(starwars, name)
select(starwars, 1)

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height <- 5
select(starwars, height)

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name <- "color"
select(starwars, ends_with(name))

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name <- 5
select(starwars, name, identity(name))

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vars <- c("name", "height")
select(starwars, all_of(vars), "mass")

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df <- starwars |> select(name, height, mass)

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mutate(df, "height", 2)

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mutate(df, height + 10)

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var <- seq(1, nrow(df))
mutate(df, new = var)

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group_by(starwars, sex)
group_by(starwars, sex = as.factor(sex))
group_by(starwars, height_binned = cut(height, 3))

## -----------------------------------------------------------------------------
group_by(df, "month")