Nothing
## -----------------------------------------------------------------------------
summary(iris)
## -----------------------------------------------------------------------------
summary(iris$Sepal.Length)
## -----------------------------------------------------------------------------
fivenum(iris$Sepal.Length)
## -----------------------------------------------------------------------------
summary(iris$Species)
## ---- render = knitr::normal_print--------------------------------------------
library(skimr)
skim(iris)
## -----------------------------------------------------------------------------
skim(iris) %>% is_skim_df()
## ---- render = knitr::normal_print--------------------------------------------
skim(iris) %>%
dplyr::select(-skim_type, -skim_variable) %>% is_skim_df()
## ---- render = knitr::normal_print--------------------------------------------
skim(iris) %>%
dplyr::select(-n_missing) %>% is_skim_df()
## ---- render = knitr::normal_print--------------------------------------------
skim(iris) %>%
tibble::as_tibble()
## ---- render = knitr::normal_print--------------------------------------------
skim(iris) %>%
dplyr::filter(skim_variable == "Petal.Length")
## ---- render = knitr::normal_print--------------------------------------------
skim(iris) %>%
dplyr::select(skim_type, skim_variable, n_missing)
## ---- render = knitr::normal_print--------------------------------------------
skim(iris) %>%
dplyr::select(skim_type, skim_variable, numeric.mean)
## ---- render = knitr::normal_print--------------------------------------------
iris %>%
dplyr::group_by(Species) %>%
skim()
## ---- render = knitr::normal_print--------------------------------------------
skim(iris, Sepal.Length, Species)
## ---- render = knitr::normal_print--------------------------------------------
skim(iris, starts_with("Sepal"))
## ---- render = knitr::normal_print--------------------------------------------
skim(lynx)
## -----------------------------------------------------------------------------
all.equal(skim(lynx), skim(as.data.frame(lynx)))
## ---- render = knitr::normal_print--------------------------------------------
m <- matrix(c(1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12), nrow = 4, ncol = 3)
m
## ---- render = knitr::normal_print--------------------------------------------
colMeans(m)
skim(m) # Similar to summary.matrix and colMeans()
## ---- render = knitr::normal_print--------------------------------------------
rowMeans(m)
skim(t(m))
## ---- render = knitr::normal_print--------------------------------------------
skim(c(m))
mean(m)
## ---- render = knitr::normal_print--------------------------------------------
iris_setosa <- iris %>%
skim_tee() %>%
dplyr::filter(Species == "setosa")
head(iris_setosa)
## ---- render = knitr::normal_print--------------------------------------------
iris %>%
skim() %>%
partition()
## ---- render = knitr::normal_print--------------------------------------------
iris %>%
skim() %>%
yank("numeric")
## ---- render = knitr::normal_print--------------------------------------------
iris %>%
skim() %>%
to_long() %>%
head()
## ---- render = knitr::normal_print--------------------------------------------
iris %>%
skim() %>%
focus(n_missing, numeric.mean)
## -----------------------------------------------------------------------------
skim(Orange)
## -----------------------------------------------------------------------------
skim(Orange) %>%
yank("numeric")
## -----------------------------------------------------------------------------
my_skim <- skim_with(numeric = sfl(new_mad = mad))
my_skim(faithful)
## -----------------------------------------------------------------------------
my_skim <- skim_with(numeric = sfl(new_mad = mad), append = FALSE)
my_skim(faithful)
## -----------------------------------------------------------------------------
no_hist <- skim_with(ts = sfl(line_graph = NULL))
no_hist(Nile)
## -----------------------------------------------------------------------------
my_skim <- skim_with(
numeric = sfl(total = ~ sum(., na.rm = TRUE)),
factor = sfl(missing = ~ sum(is.na(.))),
append = FALSE
)
my_skim(iris)
## -----------------------------------------------------------------------------
my_skim <- skim_with(base = sfl(length = length))
my_skim(faithful)
## -----------------------------------------------------------------------------
#' @export
my_package_skim <- skim_with()
## -----------------------------------------------------------------------------
get_skimmers.my_type <- function(column) {
sfl(
skim_type = "my_type",
total = sum
)
}
my_data <- data.frame(
my_type = structure(1:3, class = c("my_type", "integer"))
)
skim(my_data)
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