skimr (version 2.0.2)

sfl: Create a skimr function list

Description

This constructor is used to create a named list of functions. It also you also pass NULL to identify a skimming function that you wish to remove. Only functions that return a single value, working with dplyr::summarize(), can be used within sfl.

Usage

sfl(..., skim_type = "")

Arguments

...

A list of functions specified by:

• Their name, "mean"

• The function itself, mean

• A call to the function with . as a dummy argument, mean(., na.rm = TRUE)

These arguments are automatically quoted. They support unquoting and splicing. See vignette("programming") for an introduction to these concepts.

The following notations are not supported, see examples:

• An anonymous function, function(x) mean(x, na.rm = TRUE)

• An anonymous function in purrr notation, ~mean(., na.rm = TRUE)

skim_type

A character scalar. This is used to match locally-provided skimmers with defaults. See get_skimmers() for more detail.

Value

A skimr_function_list, which contains a list of fun_calls, returned by dplyr::funs() and a list of skimming functions to drop.

Details

sfl() will automatically generate callables and names for a variety of inputs, including functions, formulas and strings. Nonetheless, we recommend providing names when reasonable to get better skim() output.

See Also

dplyr::funs(), skim_with() and get_skimmers().

Examples

# NOT RUN {
# sfl's can take a variety of input formats and will generate names
# if not provided.
sfl(mad, "var", ~ length(.)^2)

# But these can generate unpredictable names in your output.
# Better to set your own names.
sfl(mad = mad, variance = "var", length_sq = ~ length(.)^2)

# sfl's can remove individual skimmers from defaults by passing NULL.
sfl(hist = NULL)

# When working interactively, you don't need to set a type.
# But you should when defining new defaults with `get_skimmers()`.
get_skimmers.my_new_class <- function(column) {
  sfl(n_missing, skim_type = "my_new_class")
}
# }