stabilize_df() validates the structure and contents of a data frame. It can
check that specific named columns are present and valid, that extra columns
conform to a shared rule, that required column names are present, and that
the row count is within specified bounds. stabilise_df(),
stabilize_data_frame(), and stabilise_data_frame() are synonyms of
stabilize_df().
Usage
stabilize_df(
.x,
...,
.extra_cols = NULL,
.col_names = NULL,
.min_rows = NULL,
.max_rows = NULL,
.allow_null = TRUE,
.x_arg = caller_arg(.x),
.call = caller_env(),
.x_class = object_type(.x)
)
stabilise_df(
.x,
...,
.extra_cols = NULL,
.col_names = NULL,
.min_rows = NULL,
.max_rows = NULL,
.allow_null = TRUE,
.x_arg = caller_arg(.x),
.call = caller_env(),
.x_class = object_type(.x)
)
stabilize_data_frame(
.x,
...,
.extra_cols = NULL,
.col_names = NULL,
.min_rows = NULL,
.max_rows = NULL,
.allow_null = TRUE,
.x_arg = caller_arg(.x),
.call = caller_env(),
.x_class = object_type(.x)
)
stabilise_data_frame(
.x,
...,
.extra_cols = NULL,
.col_names = NULL,
.min_rows = NULL,
.max_rows = NULL,
.allow_null = TRUE,
.x_arg = caller_arg(.x),
.call = caller_env(),
.x_class = object_type(.x)
)Arguments
- .x
The argument to stabilize.
- ...
Named stabilizer functions, such as
stabilize_*functions (stabilize_chr(), etc) or functions produced byspecify_*()functions (specify_chr(), etc). Each name corresponds to a required column in.x, and the function is used to validate that column.- .extra_cols
A single stabilizer function, such as a
stabilize_*function (stabilize_chr(), etc) or a function produced by aspecify_*()function (specify_chr(), etc). This function is used to validate all columns of.xthat are not explicitly listed in.... IfNULL(default), any extra columns will cause an error.- .col_names
(character)A character vector of column names that must be present in.x. Any columns listed here that are absent from.xwill cause an error. Unlike..., this does not validate the column contents.- .min_rows
(length-1 integer)The minimum number of rows allowed in.x. IfNULL(default), the row count is not checked.- .max_rows
(length-1 integer)The maximum number of rows allowed in.x. IfNULL(default), the row count is not checked.- .allow_null
(length-1 logical)Is NULL an acceptable value?- .x_arg
(length-1 character)The name of the argument being stabilized to use in error messages. The automatic value will work in most cases, or pass it through from higher-level functions to make error messages clearer in unexported functions.- .call
(environment)The execution environment to mention as the source of error messages.- .x_class
(length-1 character)The class name of the argument being stabilized to use in error messages. Use this if you remove a special class from the object before checking its coercion, but want the error message to match the original class.
See also
Other data frame functions:
specify_df(),
to_df()
Other stabilization functions:
stabilize_arg(),
stabilize_chr(),
stabilize_dbl(),
stabilize_fct(),
stabilize_int(),
stabilize_lgl(),
stabilize_lst(),
stabilize_present()
Examples
# Basic validation: required columns with type specs
stabilize_df(
data.frame(name = "Alice", age = 30L),
name = specify_chr_scalar(),
age = specify_int_scalar()
)
#> name age
#> 1 Alice 30
# Allow extra columns with .extra_cols
stabilize_df(
data.frame(name = "Alice", age = 30L, score = 99.5),
name = specify_chr_scalar(),
age = specify_int_scalar(),
.extra_cols = stabilize_present
)
#> name age score
#> 1 Alice 30 99.5
# Check required column names without validating contents
stabilize_df(
mtcars,
.col_names = c("mpg", "cyl"),
.extra_cols = stabilize_present
)
#> mpg cyl disp hp drat wt qsec vs am gear carb
#> Mazda RX4 21.0 6 160.0 110 3.90 2.620 16.46 0 1 4 4
#> Mazda RX4 Wag 21.0 6 160.0 110 3.90 2.875 17.02 0 1 4 4
#> Datsun 710 22.8 4 108.0 93 3.85 2.320 18.61 1 1 4 1
#> Hornet 4 Drive 21.4 6 258.0 110 3.08 3.215 19.44 1 0 3 1
#> Hornet Sportabout 18.7 8 360.0 175 3.15 3.440 17.02 0 0 3 2
#> Valiant 18.1 6 225.0 105 2.76 3.460 20.22 1 0 3 1
#> Duster 360 14.3 8 360.0 245 3.21 3.570 15.84 0 0 3 4
#> Merc 240D 24.4 4 146.7 62 3.69 3.190 20.00 1 0 4 2
#> Merc 230 22.8 4 140.8 95 3.92 3.150 22.90 1 0 4 2
#> Merc 280 19.2 6 167.6 123 3.92 3.440 18.30 1 0 4 4
#> Merc 280C 17.8 6 167.6 123 3.92 3.440 18.90 1 0 4 4
#> Merc 450SE 16.4 8 275.8 180 3.07 4.070 17.40 0 0 3 3
#> Merc 450SL 17.3 8 275.8 180 3.07 3.730 17.60 0 0 3 3
#> Merc 450SLC 15.2 8 275.8 180 3.07 3.780 18.00 0 0 3 3
#> Cadillac Fleetwood 10.4 8 472.0 205 2.93 5.250 17.98 0 0 3 4
#> Lincoln Continental 10.4 8 460.0 215 3.00 5.424 17.82 0 0 3 4
#> Chrysler Imperial 14.7 8 440.0 230 3.23 5.345 17.42 0 0 3 4
#> Fiat 128 32.4 4 78.7 66 4.08 2.200 19.47 1 1 4 1
#> Honda Civic 30.4 4 75.7 52 4.93 1.615 18.52 1 1 4 2
#> Toyota Corolla 33.9 4 71.1 65 4.22 1.835 19.90 1 1 4 1
#> Toyota Corona 21.5 4 120.1 97 3.70 2.465 20.01 1 0 3 1
#> Dodge Challenger 15.5 8 318.0 150 2.76 3.520 16.87 0 0 3 2
#> AMC Javelin 15.2 8 304.0 150 3.15 3.435 17.30 0 0 3 2
#> Camaro Z28 13.3 8 350.0 245 3.73 3.840 15.41 0 0 3 4
#> Pontiac Firebird 19.2 8 400.0 175 3.08 3.845 17.05 0 0 3 2
#> Fiat X1-9 27.3 4 79.0 66 4.08 1.935 18.90 1 1 4 1
#> Porsche 914-2 26.0 4 120.3 91 4.43 2.140 16.70 0 1 5 2
#> Lotus Europa 30.4 4 95.1 113 3.77 1.513 16.90 1 1 5 2
#> Ford Pantera L 15.8 8 351.0 264 4.22 3.170 14.50 0 1 5 4
#> Ferrari Dino 19.7 6 145.0 175 3.62 2.770 15.50 0 1 5 6
#> Maserati Bora 15.0 8 301.0 335 3.54 3.570 14.60 0 1 5 8
#> Volvo 142E 21.4 4 121.0 109 4.11 2.780 18.60 1 1 4 2
# Enforce row count constraints
try(stabilize_df(mtcars[0, ], .min_rows = 1, .extra_cols = stabilize_present))
#> Error in eval(expr, envir) :
#> `mtcars[0, ]` must have at least 1 row.
#> ✖ 0 is too few.
# NULL is allowed by default
stabilize_df(NULL)
#> NULL
try(stabilize_df(NULL, .allow_null = FALSE))
#> Error in eval(expr, envir) : `NULL` must not be <NULL>.
# Coercible inputs such as named lists are accepted
stabilize_df(
list(name = "Alice", age = 30L),
name = specify_chr_scalar(),
age = specify_int_scalar()
)
#> name age
#> 1 Alice 30
# Non-coercible inputs are rejected
try(stabilize_df("not a data frame"))
#> Error in eval(expr, envir) :
#> Can't coerce `"not a data frame"` <character> to <data.frame>.