skimrObjects within skimr are identified by a class, but they require additional
attributes and data columns for all operations to succeed. These checks help
ensure this. While they have some application externally, they are mostly
used internally.
has_type_column(object)has_variable_column(object)
has_skimr_attributes(object)
has_skim_type_attribute(object)
is_data_frame(object)
is_skim_df(object)
is_one_skim_df(object)
is_skim_list(object)
could_be_skim_df(object)
assert_is_skim_df(object)
assert_is_skim_list(object)
assert_is_one_skim_df(object)
Any R object.
has_type_column: Does the object have the skim_type column?
has_variable_column: Does the object have the skim_variable column?
has_skimr_attributes: Does the object have the appropriate skimr attributes?
has_skim_type_attribute: Does the object have a skim_type attribute? This makes
it a one_skim_df.
is_data_frame: Is the object a data frame?
is_skim_df: Is the object a skim_df?
is_one_skim_df: Is the object a one_skim_df? This is similar to a
skim_df, but does not have the type column. That is stored as an
attribute instead.
is_skim_list: Is the object a skim_list?
could_be_skim_df: Is this a data frame with skim_variable and
skim_type columns?
assert_is_skim_df: Stop if the object is not a skim_df.
assert_is_skim_list: Stop if the object is not a skim_list.
assert_is_one_skim_df: Stop if the object is not a one_skim_df.
Most notably, a skim_df has columns skim_type and skim_variable. And
has the following special attributes
data_rows: n rows in the original data
data_cols: original number of columns
df_name: name of the original data frame
dt_key: name of the key if original is a data.table
groups: if there were group variables
base_skimmers: names of functions applied to all skim types
skimmers_used: names of functions used to skim each type
The functions in these checks work like all.equal(). The return TRUE if
the check passes, or otherwise notifies why the check failed. This makes them
more useful when throwing errors.