Standard Frequency Tables in R

Usage

frequencies(
  x = NULL,
  weights = NULL,
  n.classes = NULL,
  lower.limit = NULL,
  upper.limit = NULL,
  time.breaks = NULL,
  svy.design = NULL,
  sort.decreasing = NULL,
  tidy.breaks = FALSE,
  na.count = TRUE,
  n.digits = 2,
  show.totals = TRUE,
  show.percent = TRUE,
  use.thousands.mark = FALSE,
  as.markdown = FALSE,
  as.categorical = FALSE,
  compare.valids = FALSE,
  show.relative = TRUE,
  show.cumulative = FALSE,
  show.rel.cumulative = FALSE,
  show.frequencies = TRUE
)

Arguments

x: Vector or data.frame. A numeric or categorical variable of any type.
weights: Numeric. Weights for aggregating the categories in x. It should have the same length of x.
n.classes: Integer or numeric. If a single integer, it represents the number of classes for the numeric variable. If a vector of numeric values, it will represent the desired break points for the classes. Defaults to the number of classes determined by the Herbert Sturges algorithm.
lower.limit: Numeric. Lower classes limit. Along with n.classes, it determines the bins of a distribution for continuous variables. Defaults to the minimum value of the numeric vector.
upper.limit: Numeric. Lower classes limit. Along with n.classes, it determines the bins of a distribution for continuous variables. Defaults to the maximum value of the numeric vector.
time.breaks: Character or integer. Specifies the aggregation class for date-time variables: "secs", "mins", "hours", "days", "weeks", "months","years", "DSTdays" or "quarters". If an integer it specifies an arbitrary number of classes for all the observations.
svy.design: survey.design object. A survey design object from survey::package.
sort.decreasing: NULL or logical. sort frequencies decreasingly, increasingly according to frequency counts. The default, NULL, sorts frequencies according with the classes.
tidy.breaks: Logical. Uses the default classes for histograms, allowing the frequency table of numeric values to match the default graphical bins for an histogram. It overrides the value for n.classes.
na.count: Logical. include NA values as part of the classes to be counted. If the vector has no missing values it will report 0 occurrences when TRUE is selected.
n.digits: Integer. number of decimal places to display for percentage frequencies. The number of decimals shown for relative frequencies is n.digits + 2.
show.totals: Logical. Show the sum of frequencies and relative/percentage frequencies.
show.percent: Logical. Show relative frequencies as percentage frequencies. Default is TRUE.
use.thousands.mark: Logical. Show the thousands mark for numeric columns. Warning: numeric variables will be stored as character.
as.markdown: Logical. Return the frequency table in RMarkdown format, uses the pander:: package.
as.categorical: Logical. If TRUE, it will display each integer value as a different category. If FALSE, it will aggregate integer values into classes for unique values greater than 15. Useful for displaying variables with several categories, such as Default is FALSE.
compare.valids: Logical. Show or hide an additional column for each column type to compare valid vs. NA values, default is FALSE. It overrides selected option for na.count argument.
show.relative: Logical. Show or hide the column for relative frequencies, default is TRUE.
show.cumulative: Logical. Show or hide the column for cumulative frequencies, default is FALSE
show.rel.cumulative: Logical. Show or hide the column for relative cumulative frequencies, default is FALSE.
show.frequencies: Logical. Show or hide the column for counts per class, default is TRUE.

Value

a data.frame with one character column and the rest as numeric values

Examples

frequencies(x = airquality$Ozone)
#>          classes freqs relative_freqs
#> 1  [  1.0, 21.9)    41          26.80
#> 2  [ 21.9, 42.8)    31          20.26
#> 3  [ 42.8, 63.6)    15           9.80
#> 4  [ 63.6, 84.5)    15           9.80
#> 5  [ 84.5,105.4)     7           4.58
#> 6  [105.4,126.2)     5           3.27
#> 7  [126.2,147.1)     1           0.65
#> 8  [147.1,168.0]     1           0.65
#> 9      NA VALUES    37          24.18
#> 10         TOTAL   153         100.00