desctable (version 0.1.0)

desctable: Generate a statistics table


Generate a statistics table with the chosen statistical functions, and tests if given a "grouped" dataframe.


desctable(data, stats, tests, labels)

# S3 method for default desctable(data, stats = stats_auto, tests, labels = NULL)

# S3 method for grouped_df desctable(data, stats = stats_auto, tests = tests_auto, labels = NULL)


The dataframe to analyze
A list of named statistics to apply to each element of the dataframe, or a function returning a list of named statistics
A list of statistical tests to use when calling desctable with a grouped_df
A named character vector of labels to use instead of variable names


A desctable object, which prints to a table of statistics for all variables


labels is an option named character vector used to make the table prettier.

If given, the variable names for which there is a label will be replaced by their corresponding label.

Not all variables need to have a label, and labels for non-existing variables are ignored.

labels must be given in the form c(unquoted_variable_name = "label")


The stats can be a function which takes a dataframe and returns a list of statistical functions to use.

stats can also be a named list of statistical functions, or formulas.

The names will be used as column names in the resulting table. If an element of the list is a function, it will be used as-is for the stats. If an element of the list is a formula, it can be used to conditionally use stats depending on the variable.

The general form is condition ~ T | F, and can be nested, such as is.factor ~ percent | (is.normal ~ mean | median), for example.


The tests can be a function which takes a variable and a grouping variable, and returns an appropriate statistical test to use in that case.

tests can also be a named list of statistical test functions, associating the name of a variable in the data, and a test to use specifically for that variable.

That test name must be expressed as a single-term formula (e.g. ~t.test). You don't have to specify tests for all the variables: a default test for all other variables can be defined with the name .default, and an automatic test can be defined with the name .auto.

If data is a grouped dataframe (using group_by), subtables are created and statistic tests are performed over each sub-group.


The output is a desctable object, which is a list of named dataframes that can be further manipulated. Methods for printing, using in pander and DT are present. Printing reduces the object to a dataframe.

See Also







iris %>%

# Does the same as stats_auto here
iris %>% 
  desctable(stats = list("N"      = length,
                         "%/Mean" = is.factor ~ percent | (is.normal ~ mean),
                         "sd"     = is.normal ~ sd,
                         "Med"    = is.normal ~ NA | median,
                         "IQR"    = is.normal ~ NA | IQR))

# With labels
mtcars %>% desctable(labels = c(hp  = "Horse Power",
                                cyl = "Cylinders",
                                mpg = "Miles per gallon"))

# With grouping on a factor
iris %>%
  group_by(Species) %>%
  desctable(stats = stats_default)

# With nested grouping, on arbitrary variables
mtcars %>%
  group_by(vs, cyl) %>%

# With grouping on a condition, and choice of tests
iris %>%
  group_by(Petal.Length > 5) %>%
  desctable(tests = list(.auto = tests_auto, Species = ~chisq.test))