Summarize continuous variables

Summarize continuous data and handle output format.

Usage

desc_cont(
  .data,
  vc,
  format = "median (q1-q3) [min-max]",
  digits = 1,
  export_raw_values = FALSE
)

Arguments

.data

A data.frame, where vc are column names of continuous variables

vc

A character vector, list of column names. Should only contain continuous variables

format

A character string. How would you like the output? See details.

digits

A numeric. How many digits? This argument calls internal formatting function

export_raw_values

A logical. Should the raw values be exported?

Value

A data.frame with columns

• var the variable name

• level NA, it is provided to have a consistent output with desc_facvar()

• value the formatted value with possibly the median, interquartile range, and range (see details)

• n_avail the number of cases with available data for this variable.

Details

Many other packages provide tools to summarize data. This one is just the package author's favorite. This makes it much easier to map to nice labeling thereafter. The format argument shows the output of the function. You can change square and round brackets, spaces, separators... Important format inputs are

• median the median value

• q1 the first quartile

• q3 the third quartile

• min the minimum value

• max the maximum value

The analogous for categorical variables is desc_facvar().

See also

desc_facvar()

Examples

df <-
  data.frame(
    smoke_status = c("smoker", "non-smoker",
           "smoker", "smoker",
           "smoker", "smoker",
           "non-smoker"
           ),
    age = c(60, 50, 56, 49, 75, 69, 85),
    bmi = c(18, 30, 25, 22, 23, 21, 22)
  )

# Use default formatting

desc_cont(.data = df, vc = c("age", "bmi"))
#>   var level                        value n_avail
#> 1 age  <NA> 60.0 (53.0-72.0) [49.0-85.0]       7
#> 2 bmi  <NA> 22.0 (21.5-24.0) [18.0-30.0]       7

# Use custom formatting

desc_cont(.data = df,
          vc = c("age", "bmi"),
          format = "median (q1;q3)"
          )
#>   var level            value n_avail
#> 1 age  <NA> 60.0 (53.0;72.0)       7
#> 2 bmi  <NA> 22.0 (21.5;24.0)       7

# You might want to export raw values, to run plotting or
# other formatting functions

desc_cont(.data = df, vc = c("age", "bmi"),
          export_raw_values = TRUE)
#>   var level                        value n_avail median   q1 q3 min max
#> 1 age  <NA> 60.0 (53.0-72.0) [49.0-85.0]       7     60 53.0 72  49  85
#> 2 bmi  <NA> 22.0 (21.5-24.0) [18.0-30.0]       7     22 21.5 24  18  30