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## ----include = FALSE----------------------------------------------------------
knitr::opts_chunk$set(collapse = T, comment = "#>")
options(tibble.print_min = 4L, tibble.print_max = 4L)
set.seed(1014)
## ----eval = FALSE-------------------------------------------------------------
# df %>%
# group_by(g1, g2) %>%
# summarise(a = mean(a), b = mean(b), c = mean(c), d = mean(d))
## ----eval = FALSE-------------------------------------------------------------
# df %>%
# group_by(g1, g2) %>%
# summarise(across(a:d, mean))
## ----setup--------------------------------------------------------------------
library(dplyr, warn.conflicts = FALSE)
## -----------------------------------------------------------------------------
starwars %>%
summarise(across(where(is.character), n_distinct))
starwars %>%
group_by(species) %>%
filter(n() > 1) %>%
summarise(across(c(sex, gender, homeworld), n_distinct))
starwars %>%
group_by(homeworld) %>%
filter(n() > 1) %>%
summarise(across(where(is.numeric), ~ mean(.x, na.rm = TRUE)))
## -----------------------------------------------------------------------------
df <- data.frame(g = c(1, 1, 2), x = c(-1, 1, 3), y = c(-1, -4, -9))
df %>%
group_by(g) %>%
summarise(across(where(is.numeric), sum))
## -----------------------------------------------------------------------------
min_max <- list(
min = ~min(.x, na.rm = TRUE),
max = ~max(.x, na.rm = TRUE)
)
starwars %>% summarise(across(where(is.numeric), min_max))
starwars %>% summarise(across(c(height, mass, birth_year), min_max))
## -----------------------------------------------------------------------------
starwars %>% summarise(across(where(is.numeric), min_max, .names = "{.fn}.{.col}"))
starwars %>% summarise(across(c(height, mass, birth_year), min_max, .names = "{.fn}.{.col}"))
## -----------------------------------------------------------------------------
starwars %>% summarise(
across(c(height, mass, birth_year), ~min(.x, na.rm = TRUE), .names = "min_{.col}"),
across(c(height, mass, birth_year), ~max(.x, na.rm = TRUE), .names = "max_{.col}")
)
## -----------------------------------------------------------------------------
starwars %>% summarise(
tibble(
across(where(is.numeric), ~min(.x, na.rm = TRUE), .names = "min_{.col}"),
across(where(is.numeric), ~max(.x, na.rm = TRUE), .names = "max_{.col}")
)
)
## -----------------------------------------------------------------------------
starwars %>%
summarise(across(where(is.numeric), min_max, .names = "{.fn}.{.col}")) %>%
relocate(starts_with("min"))
## -----------------------------------------------------------------------------
df <- tibble(x = 1:3, y = 3:5, z = 5:7)
mult <- list(x = 1, y = 10, z = 100)
df %>% mutate(across(all_of(names(mult)), ~ .x * mult[[cur_column()]]))
## -----------------------------------------------------------------------------
df <- data.frame(x = c(1, 2, 3), y = c(1, 4, 9))
df %>%
summarise(n = n(), across(where(is.numeric), sd))
## -----------------------------------------------------------------------------
df %>%
summarise(across(where(is.numeric), sd), n = n())
## -----------------------------------------------------------------------------
df %>%
summarise(n = n(), across(where(is.numeric) & !n, sd))
## -----------------------------------------------------------------------------
df %>%
summarise(
tibble(n = n(), across(where(is.numeric), sd))
)
## -----------------------------------------------------------------------------
rescale01 <- function(x) {
rng <- range(x, na.rm = TRUE)
(x - rng[1]) / (rng[2] - rng[1])
}
df <- tibble(x = 1:4, y = rnorm(4))
df %>% mutate(across(where(is.numeric), rescale01))
## -----------------------------------------------------------------------------
starwars %>% distinct(pick(contains("color")))
## -----------------------------------------------------------------------------
starwars %>% count(pick(contains("color")), sort = TRUE)
## -----------------------------------------------------------------------------
starwars %>%
filter(if_any(everything(), ~ !is.na(.x)))
## -----------------------------------------------------------------------------
starwars %>%
filter(if_all(everything(), ~ !is.na(.x)))
## ----eval = FALSE-------------------------------------------------------------
# df %>%
# group_by(g1, g2) %>%
# summarise(
# across(where(is.numeric), mean),
# across(where(is.factor), nlevels),
# n = n(),
# )
## ----results = FALSE----------------------------------------------------------
df %>% mutate_if(is.numeric, ~mean(.x, na.rm = TRUE))
# ->
df %>% mutate(across(where(is.numeric), ~mean(.x, na.rm = TRUE)))
df %>% mutate_at(vars(c(x, starts_with("y"))), mean)
# ->
df %>% mutate(across(c(x, starts_with("y")), mean))
df %>% mutate_all(mean)
# ->
df %>% mutate(across(everything(), mean))
## -----------------------------------------------------------------------------
df <- tibble(x = c("a", "b"), y = c(1, 1), z = c(-1, 1))
# Find all rows where EVERY numeric variable is greater than zero
df %>% filter(if_all(where(is.numeric), ~ .x > 0))
# Find all rows where ANY numeric variable is greater than zero
df %>% filter(if_any(where(is.numeric), ~ .x > 0))
## -----------------------------------------------------------------------------
df <- tibble(x = 2, y = 4, z = 8)
df %>% mutate_all(~ .x / y)
df %>% mutate(across(everything(), ~ .x / y))
|
