Function to get the number of rows with complete data for a given dataset and collection variables

Usage

getNcomplete(
  data = NULL,
  vars = NULL,
  name = NULL,
  returnType = c("named number", "raw number", "list")
)

Arguments

data: The data as a data frame or tibble.
vars: The variables to check, in tidyselect syntax
name: Optional name, if not supplied, vars will be used.
returnType: Character argument specifying the return type, see description.

Value

number of rows of complete data as a named number, an unnamed number or list.

Background

This function does a very simple thing: returns the number of rows of data in the dataset 'data' with non-missing values for all the variables in 'vars'.

Depending on the value of 'returnType' it returns a raw number, a named number or a list with members 'name' and 'nComplete'.

The 'name' can be supplied in the argument 'name' or, if nothing is specified there the character form of the variable selection is used as the name for the named number or the list return.

The nice thing is that you can use any tidyselect syntax to select the variables, see the examples.

The option to return a list makes it easy to write a sequence of dplyr summarise() statements to build a table of the numbers of complete data for various selections of variables. These can then, of course, be embedded in a dplyr group_by() specifications so the same counting can be done for subsets of the data.

I will expand the examples below and this probably needs a vignette to explain it more fully.

Acknowledgement: this wouldn't have happened had Maren Rogaski not been keen on getting these values!

Examples

if (FALSE) { # \dontrun{
valN <- 10

tibble(a = rnorm(valN),
       b = rnorm(valN),
       c = rnorm(valN),
       aChar = rep("a", valN),
       nums = 1:valN) %>%
  mutate(a = if_else(row_number() == 1,
                     NA_real_,
                     a),
         b = if_else(row_number() == 2,
                     NA_real_,
                     b),
         c = if_else(row_number() == 3,
                     NA_real_,
                     c),
         aChar = if_else(row_number() == 4,
                         NA_character_,
                         aChar),
         nums = if_else(row_number() == 5,
                        NA_integer_,
                        nums)) -> tmpTib

getNcomplete(tmpTib) # you can call the dataset by its object name
getNcomplete("tmpTib") # or supply that as a character variable
### but those will throw an error as the function wants you to be explicit:
### so use 'everything()' if you want all the variables in the dataset.
getNcomplete("tmpTib", everything())
getNcomplete(tmpTib, everything())
### but you can use any 'tidyselect' specification of the variables:
getNcomplete(tmpTib, a : nums)
getNcomplete(tmpTib, a : aChar)
getNcomplete(tmpTib, a)
getNcomplete(tmpTib, "a")
getNcomplete(tmpTib, where(is.integer))
getNcomplete(tmpTib, where(is.character))
getNcomplete(tmpTib, where(is.numeric))
getNcomplete(tmpTib, c("a", "c"))
### but this will throw a raw R error complaining there is no variable 'sausages'!
getNcomplete(tmpTib, sausages)
### you can specify three return types with returnType (imaginative names eh?)
### # 'named number'
### # 'raw number'
### # 'list'

} # }