Nothing
## -----------------------------------------------------------------------------
library(skimr)
## -----------------------------------------------------------------------------
results <- lm(weight ~ feed, data = chickwts)
class(results)
attributes(results)
## ---- eval = FALSE------------------------------------------------------------
# as.data.frame(results)
# #> Error in as.data.frame.default(results) :
# #> cannot coerce class ‘"lm"’ to a data.frame
## -----------------------------------------------------------------------------
skim(results$model)
## -----------------------------------------------------------------------------
skim_lm <- function(.data) {
.data <- .data$model
skimr::skim(.data)
}
lm(weight ~ feed, data = chickwts) %>% skim_lm()
## -----------------------------------------------------------------------------
skim_lm <- function(.data, fit = FALSE) {
.data <- .data$model
if (fit) {
.data <- .data %>%
dplyr::bind_cols(
fitted = data.frame(results$fitted.values),
residuals = data.frame(results$residuals)
)
}
skimr::skim(.data)
}
## -----------------------------------------------------------------------------
skim_lm(results, fit = TRUE)
## -----------------------------------------------------------------------------
class(UScitiesD)
UScitiesD
## -----------------------------------------------------------------------------
skim_dist <- function(.data) {
.data <- data.frame(as.matrix(.data))
skimr::skim(.data)
}
## -----------------------------------------------------------------------------
as.data.frame.dist <- function(.data) {
.data <- data.frame(as.matrix(.data))
.data[] <- lapply(.data, structure, class = "distance", nms = names(.data))
.data
}
as.data.frame(UScitiesD)
## -----------------------------------------------------------------------------
skim(UScitiesD)
## -----------------------------------------------------------------------------
get_nearest <- function(column) {
closest <- which.min(column[column != 0])
cities <- attr(column, "nms")[column != 0]
toString(cities[closest])
}
get_furthest <- function(column) {
furthest <- which.max(column[column != 0])
cities <- attr(column, "nms")[column != 0]
toString(cities[furthest])
}
## -----------------------------------------------------------------------------
skim_with_dist <- skim_with(
distance = sfl(
nearest = get_nearest,
furthest = get_furthest
)
)
skim_with_dist(UScitiesD)
## -----------------------------------------------------------------------------
#' @importFrom skimr get_skimmers
#' @export
get_skimmers.distance <- function(column) {
sfl(
skim_type = "distance",
nearest = get_nearest,
furthest = get_furthest
)
}
## -----------------------------------------------------------------------------
get_default_skimmer_names()
## -----------------------------------------------------------------------------
skim(UScitiesD)
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