Check that the rows and columns of two tables are the same

Checks for differences between object and expected in the following order:

Check table class with tbl_check_class()
Check column names with tbl_check_names()
Check number of rows and columns with tbl_check_dimensions()
Check groups with tbl_check_groups()
Check that each column is the same with tbl_check_column()

If the tables differ

tbl_check() returns a list describing the problem
tbl_grade() returns a failing grade and informative message with gradethis::fail()

Usage

tbl_check(
  object = .result,
  expected = .solution,
  cols = NULL,
  check_class = TRUE,
  check_names = TRUE,
  check_column_order = FALSE,
  check_dimensions = TRUE,
  check_groups = TRUE,
  check_columns = TRUE,
  check_column_class = check_columns,
  check_column_values = check_columns,
  env = parent.frame()
)

tbl_grade(
  object = .result,
  expected = .solution,
  cols = NULL,
  max_diffs = 3,
  check_class = TRUE,
  check_names = TRUE,
  check_column_order = FALSE,
  check_dimensions = TRUE,
  check_groups = TRUE,
  check_columns = TRUE,
  check_column_class = check_columns,
  check_column_values = check_columns,
  env = parent.frame(),
  ...
)

Arguments

object

A data frame to be compared to expected.

expected

A data frame containing the expected result.

cols

[tidy-select]
A selection of columns to compare between object and expected. Differences in other columns will be ignored. If NULL, the default, all columns will be checked.

check_class

[logical(1)]
Whether to check that object and expected have the same classes with tbl_check_class().

check_names

[logical(1)]
Whether to check that object and expected have the same column names with tbl_check_names().

check_column_order

[logical(1)]
Whether to check that the columns of object are in the same order as expected with tbl_check_names(). Defaults to FALSE.

check_dimensions

[logical(1)]
Whether to check that object and expected have the same number of rows and columns with tbl_check_dimensions().

check_groups

[logical(1)]
Whether to check that object and expected have the same groups with dplyr::group_vars().

check_columns

[logical(1)]
Whether to check that all columns have the same contents with tbl_check_column().

check_column_class

[logical(1)]
Whether to check that each columns has the same class in object and expected.

check_column_values

[logical(1)]
Whether to check that each column has the same values in object and expected.

env

The environment in which to find .result and .solution.

max_diffs

[numeric(1)]
The maximum number of mismatched values to display in an informative failure message. Passed to tbl_check_names() to determine the number of mismatched column names to display and the n_values argument of tbl_check_column() to determine the number of mismatched column values to display. Defaults to 3.

...

Arguments passed on to gradethis::fail

hint: Include a code feedback hint with the failing message? This argument only applies to fail() and fail_if_equal() and the message is added using the default options of give_code_feedback() and maybe_code_feedback(). The default value of hint can be set using gradethis_setup() or the gradethis.fail.hint option.
encourage: Incude a random encouraging phrase with random_encouragement()? The default value of encourage can be set using gradethis_setup() or the gradethis.fail.encourage option.

Value

If there are any issues, a list from tbl_check() or a gradethis::fail() message from tbl_grade(). Otherwise, invisibly returns NULL.

Problems

class: The table does not have the expected classes.
not_table: object does not inherit the data.frame class.
names: The table has column names that are not expected, or is missing names that are expected.
names_order: The table has the same column names as expected, but in a different order.
ncol: The table doesn't have the expected number of columns.
nrow: The table doesn't have the expected number of rows.
groups: The table has groups that are not expected, or is missing groups that are expected.

Additional problems may be produced by tbl_check_column().

Examples

.result <- data.frame(a = 1:10, b = 11:20)
.solution <- tibble::tibble(a = 1:10, b = 11:20)
tbl_check()
#> <tblcheck problem>
#> Your table should be a tibble (class `tbl_df`), but it is a data frame (class `data.frame`).
#> $ type           : chr "class"
#> $ expected       : chr [1:3] "tbl_df" "tbl" "data.frame"
#> $ actual         : chr "data.frame"
#> $ expected_length: int 2
#> $ actual_length  : int 2
#> $ location       : chr "table"
tbl_grade()
#> <gradethis_graded: [Incorrect]
#>   Your table should be a tibble (class `tbl_df`), but it is a
#>   data frame (class `data.frame`).
#> >

.result <- tibble::tibble(a = 1:10, b = a, c = a, d = a, e = a, f = a)
.solution <- tibble::tibble(z = 1:10, y = z, x = z, w = z, v = z, u = z)
tbl_check()
#> <tblcheck problem>
#> Your table should have columns named `z`, `y`, `x`, and 3 more. Your table should not have columns named `a`, `b`, `c`, or 3 more.
#> $ type      : chr "names"
#> $ missing   : chr [1:6] "z" "y" "x" "w" ...
#> $ unexpected: chr [1:6] "a" "b" "c" "d" ...
#> $ location  : chr "table"
tbl_grade()
#> <gradethis_graded: [Incorrect]
#>   Your table should have columns named `z`, `y`, `x`, and 3 more.
#>   Your table should not have columns named `a`, `b`, `c`, or 3
#>   more.
#> >
tbl_grade(max_diffs = 5)
#> <gradethis_graded: [Incorrect]
#>   Your table should have columns named `z`, `y`, `x`, `w`, `v`,
#>   and 1 more. Your table should not have columns named `a`, `b`,
#>   `c`, `d`, `e`, or 1 more.
#> >
tbl_grade(max_diffs = Inf)
#> <gradethis_graded: [Incorrect]
#>   Your table should have columns named `z`, `y`, `x`, `w`, `v`,
#>   and `u`. Your table should not have columns named `a`, `b`,
#>   `c`, `d`, `e`, or `f`.
#> >

.result <- tibble::tibble(a = 1:10, b = 11:20)
.solution <- tibble::tibble(a = 1:11, b = 12:22)
tbl_check()
#> <tblcheck problem>
#> Your table should have 11 rows, but it has 10 rows.
#> $ type    : chr "nrow"
#> $ expected: int 11
#> $ actual  : int 10
#> $ location: chr "table"
tbl_grade()
#> <gradethis_graded: [Incorrect]
#>   Your table should have 11 rows, but it has 10 rows.
#> >

.result <- tibble::tibble(a = 1:10, b = 11:20)
.solution <- tibble::tibble(a = letters[1:10], b = letters[11:20])
tbl_check()
#> <tblcheck problem>
#> Your `a` column should be a vector of text (class `character`), but it is a vector of integers (class `integer`).
#> $ type           : chr "class"
#> $ expected       : chr "character"
#> $ actual         : chr "integer"
#> $ expected_length: int 10
#> $ actual_length  : int 10
#> $ location       : chr "column"
#> $ column         : chr "a"
tbl_grade()
#> <gradethis_graded: [Incorrect]
#>   Your `a` column should be a vector of text (class `character`),
#>   but it is a vector of integers (class `integer`).
#> >

.result <- tibble::tibble(a = 1:10, intermediate = 6:15, b = 11:20)
.solution <- tibble::tibble(a = 1:10, b = 11:20)
tbl_check(cols = any_of(names(.solution)))
tbl_grade(cols = any_of(names(.solution)))

.result <- tibble::tibble(a = 1:10, b = 11:20)
.solution <- tibble::tibble(a = 11:20, b = 1:10)
tbl_check()
#> <tblcheck problem>
#> The first 3 values of your `a` column should be `11`, `12`, and `13`, not `1`, `2`, and `3`.
#> $ type    : chr "values"
#> $ expected: int [1:10] 11 12 13 14 15 16 17 18 19 20
#> $ actual  : int [1:10] 1 2 3 4 5 6 7 8 9 10
#> $ location: chr "column"
#> $ column  : chr "a"
tbl_grade()
#> <gradethis_graded: [Incorrect]
#>   The first 3 values of your `a` column should be `11`, `12`, and
#>   `13`, not `1`, `2`, and `3`.
#> >
tbl_grade(max_diffs = 5)
#> <gradethis_graded: [Incorrect]
#>   The first 5 values of your `a` column should be `11`, `12`,
#>   `13`, `14`, and `15`, not `1`, `2`, `3`, `4`, and `5`.
#> >
tbl_grade(max_diffs = Inf)
#> <gradethis_graded: [Incorrect]
#>   The first 10 values of your `a` column should be `11`, `12`,
#>   `13`, `14`, `15`, `16`, `17`, `18`, `19`, and `20`, not `1`,
#>   `2`, `3`, `4`, `5`, `6`, `7`, `8`, `9`, and `10`.
#> >