describe_distribution  R Documentation 
Describe a distribution
Description
This function describes a distribution by a set of indices (e.g., measures of
centrality, dispersion, range, skewness, kurtosis).
Usage
describe_distribution(x, ...)
## S3 method for class 'numeric'
describe_distribution(
x,
centrality = "mean",
dispersion = TRUE,
iqr = TRUE,
range = TRUE,
quartiles = FALSE,
ci = NULL,
iterations = 100,
threshold = 0.1,
verbose = TRUE,
...
)
## S3 method for class 'factor'
describe_distribution(x, dispersion = TRUE, range = TRUE, verbose = TRUE, ...)
## S3 method for class 'data.frame'
describe_distribution(
x,
select = NULL,
exclude = NULL,
centrality = "mean",
dispersion = TRUE,
iqr = TRUE,
range = TRUE,
quartiles = FALSE,
include_factors = FALSE,
ci = NULL,
iterations = 100,
threshold = 0.1,
ignore_case = FALSE,
regex = FALSE,
verbose = TRUE,
...
)
Arguments
x 
A numeric vector, a character vector, a data frame, or a list. See
Details .

... 
Additional arguments to be passed to or from methods.

centrality 
The pointestimates (centrality indices) to compute. Character
(vector) or list with one or more of these options: "median" , "mean" , "MAP"
(see map_estimate() ), "trimmed" (which is just mean(x, trim = threshold) ),
"mode" or "all" .

dispersion 
Logical, if TRUE , computes indices of dispersion related
to the estimate(s) (SD and MAD for mean and median , respectively).
Dispersion is not available for "MAP" or "mode" centrality indices.

iqr 
Logical, if TRUE , the interquartile range is calculated
(based on stats::IQR() , using type = 6 ).

range 
Return the range (min and max).

quartiles 
Return the first and third quartiles (25th and 75pth
percentiles).

ci 
Confidence Interval (CI) level. Default is NULL , i.e. no
confidence intervals are computed. If not NULL , confidence intervals
are based on bootstrap replicates (see iterations ). If
centrality = "all" , the bootstrapped confidence interval refers to
the first centrality index (which is typically the median).

iterations 
The number of bootstrap replicates for computing confidence
intervals. Only applies when ci is not NULL .

threshold 
For centrality = "trimmed" (i.e. trimmed mean), indicates
the fraction (0 to 0.5) of observations to be trimmed from each end of the
vector before the mean is computed.

verbose 
Toggle warnings and messages.

select 
Variables that will be included when performing the required
tasks. Can be either
a variable specified as a literal variable name (e.g., column_name ),
a string with the variable name (e.g., "column_name" ), or a character
vector of variable names (e.g., c("col1", "col2", "col3") ),
a formula with variable names (e.g., ~column_1 + column_2 ),
a vector of positive integers, giving the positions counting from the left
(e.g. 1 or c(1, 3, 5) ),
a vector of negative integers, giving the positions counting from the
right (e.g., 1 or 1:3 ),
one of the following selecthelpers: starts_with() , ends_with() ,
contains() , a range using : or regex("") . starts_with() ,
ends_with() , and contains() accept several patterns, e.g
starts_with("Sep", "Petal") .
or a function testing for logical conditions, e.g. is.numeric() (or
is.numeric ), or any userdefined function that selects the variables
for which the function returns TRUE (like: foo < function(x) mean(x) > 3 ),
ranges specified via literal variable names, selecthelpers (except
regex() ) and (userdefined) functions can be negated, i.e. return
nonmatching elements, when prefixed with a  , e.g. ends_with("") ,
is.numeric or (Sepal.Width:Petal.Length) . Note: Negation means
that matches are excluded, and thus, the exclude argument can be
used alternatively. For instance, select=ends_with("Length") (with
 ) is equivalent to exclude=ends_with("Length") (no  ). In case
negation should not work as expected, use the exclude argument instead.
If NULL , selects all columns. Patterns that found no matches are silently
ignored, e.g. find_columns(iris, select = c("Species", "Test")) will just
return "Species" .

exclude 
See select , however, column names matched by the pattern
from exclude will be excluded instead of selected. If NULL (the default),
excludes no columns.

include_factors 
Logical, if TRUE , factors are included in the
output, however, only columns for range (first and last factor levels) as
well as n and missing will contain information.

ignore_case 
Logical, if TRUE and when one of the selecthelpers or
a regular expression is used in select , ignores lower/upper case in the
search pattern when matching against variable names.

regex 
Logical, if TRUE , the search pattern from select will be
treated as regular expression. When regex = TRUE , select must be a
character string (or a variable containing a character string) and is not
allowed to be one of the supported selecthelpers or a character vector
of length > 1. regex = TRUE is comparable to using one of the two
selecthelpers, select = contains("") or select = regex("") , however,
since the selecthelpers may not work when called from inside other
functions (see 'Details'), this argument may be used as workaround.

Details
If x
is a data frame, only numeric variables are kept and will be
displayed in the summary.
If x
is a list, the behavior is different whether x
is a stored list. If
x
is stored (for example, describe_distribution(mylist)
where mylist
was created before), artificial variable names are used in the summary
(Var_1
, Var_2
, etc.). If x
is an unstored list (for example,
describe_distribution(list(mtcars$mpg))
), then "mtcars$mpg"
is used as
variable name.
Value
A data frame with columns that describe the properties of the variables.
Note
There is also a
plot()
method
implemented in the
seepackage.
Examples
describe_distribution(rnorm(100))
data(iris)
describe_distribution(iris)
describe_distribution(iris, include_factors = TRUE, quartiles = TRUE)
describe_distribution(list(mtcars$mpg, mtcars$cyl))