# desctable

##### Generate a statistics table

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

dataframe.

##### Usage

`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)

##### Arguments

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

##### Value

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

##### Labels

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")

##### Stats

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.

##### Tests

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.

##### Output

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

##### Examples

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

*Documentation reproduced from package desctable, version 0.1.0, License: GPL-3*