testdat (version 0.4.2)

value-expectations: Expectations: values

Description

Test whether variables in a data frame contain only certain values.

Usage

expect_values(
  vars,
  ...,
  miss = getOption("testdat.miss"),
  flt = TRUE,
  data = get_testdata()
)
expect_range(vars, min, max, ..., flt = TRUE, data = get_testdata())

Value

expect_*() functions are mainly called for their side effects. The expectation signals its result (e.g. "success", "failure"), which is logged by the current test reporter. In a non-testing context the expectation will raise an error with class expectation_failure if it fails.

Arguments

vars

<tidy-select> A set of columns to test.

...

Vectors of valid values.

miss

A vector of values to be treated as missing. The testdat.miss or testdat.miss_text option is used by default.

flt

<data-masking> A filter specifying a subset of the data frame to test.

data

A data frame to test. The global test data is used by default.

min

Minimum value for range check.

max

Maximum value for range check.

See Also

Checks: values

Other data expectations: conditional-expectations, datacomp-expectations, date-expectations, exclusivity-expectations, expect_depends(), generic-expectations, label-expectations, pattern-expectations, proportion-expectations, text-expectations, uniqueness-expectations

Examples

sales <- data.frame(
  sale_id = 1:5,
  date = c("20200101", "20200101", "20200102", "20200103", "20220101"),
  sale_price = c(10, 20, 30, 40, -1)
)

try(expect_values(date, 20000000:20210000, data = sales)) # Dates between 2000 and 2021
try(expect_range(sale_price, min = 0, max = Inf, data = sales)) # Prices non-negative