General utility functions

Working with options

`describe_option`(pat[, _print_desc])	Prints the description for one or more registered options.
`reset_option`(pat)	Reset one or more options to their default value.
`get_option`(pat)	Retrieves the value of the specified option.
`set_option`(pat, value)	Sets the value of the specified option.
`option_context`(*args)	Context manager to temporarily set options in the with statement context.

Testing functions

`testing.assert_frame_equal`(left, right[, ...])	Check that left and right DataFrame are equal.
`testing.assert_series_equal`(left, right[, ...])	Check that left and right Series are equal.
`testing.assert_index_equal`(left, right[, ...])	Check that left and right Index are equal.
`testing.assert_extension_array_equal`(left, right)	Check that left and right ExtensionArrays are equal.

Exceptions and warnings

`errors.AccessorRegistrationWarning`	Warning for attribute conflicts in accessor registration.
`errors.DtypeWarning`	Warning raised when reading different dtypes in a column from a file.
`errors.DuplicateLabelError`	Error raised when an operation would introduce duplicate labels.
`errors.EmptyDataError`	Exception that is thrown in pd.read_csv (by both the C and Python engines) when empty data or header is encountered.
`errors.InvalidIndexError`	Exception raised when attempting to use an invalid index key.
`errors.MergeError`	Error raised when problems arise during merging due to problems with input data.
`errors.NullFrequencyError`	Error raised when a null freq attribute is used in an operation that needs a non-null frequency, particularly DatetimeIndex.shift, TimedeltaIndex.shift, PeriodIndex.shift.
`errors.NumbaUtilError`	Error raised for unsupported Numba engine routines.
`errors.OutOfBoundsDatetime`
`errors.OutOfBoundsTimedelta`	Raised when encountering a timedelta value that cannot be represented as a timedelta64[ns].
`errors.ParserError`	Exception that is raised by an error encountered in parsing file contents.
`errors.ParserWarning`	Warning raised when reading a file that doesn't use the default 'c' parser.
`errors.PerformanceWarning`	Warning raised when there is a possible performance impact.
`errors.UnsortedIndexError`	Error raised when attempting to get a slice of a MultiIndex, and the index has not been lexsorted.
`errors.UnsupportedFunctionCall`	Exception raised when attempting to call a numpy function on a pandas object, but that function is not supported by the object e.g.

Data types related functionality

`api.types.union_categoricals`(to_union[, ...])	Combine list-like of Categorical-like, unioning categories.
`api.types.infer_dtype`	Efficiently infer the type of a passed val, or list-like array of values.
`api.types.pandas_dtype`(dtype)	Convert input into a pandas only dtype object or a numpy dtype object.

Dtype introspection

`api.types.is_bool_dtype`(arr_or_dtype)	Check whether the provided array or dtype is of a boolean dtype.
`api.types.is_categorical_dtype`(arr_or_dtype)	Check whether an array-like or dtype is of the Categorical dtype.
`api.types.is_complex_dtype`(arr_or_dtype)	Check whether the provided array or dtype is of a complex dtype.
`api.types.is_datetime64_any_dtype`(arr_or_dtype)	Check whether the provided array or dtype is of the datetime64 dtype.
`api.types.is_datetime64_dtype`(arr_or_dtype)	Check whether an array-like or dtype is of the datetime64 dtype.
`api.types.is_datetime64_ns_dtype`(arr_or_dtype)	Check whether the provided array or dtype is of the datetime64[ns] dtype.
`api.types.is_datetime64tz_dtype`(arr_or_dtype)	Check whether an array-like or dtype is of a DatetimeTZDtype dtype.
`api.types.is_extension_type`(arr)	(DEPRECATED) Check whether an array-like is of a pandas extension class instance.
`api.types.is_extension_array_dtype`(arr_or_dtype)	Check if an object is a pandas extension array type.
`api.types.is_float_dtype`(arr_or_dtype)	Check whether the provided array or dtype is of a float dtype.
`api.types.is_int64_dtype`(arr_or_dtype)	Check whether the provided array or dtype is of the int64 dtype.
`api.types.is_integer_dtype`(arr_or_dtype)	Check whether the provided array or dtype is of an integer dtype.
`api.types.is_interval_dtype`(arr_or_dtype)	Check whether an array-like or dtype is of the Interval dtype.
`api.types.is_numeric_dtype`(arr_or_dtype)	Check whether the provided array or dtype is of a numeric dtype.
`api.types.is_object_dtype`(arr_or_dtype)	Check whether an array-like or dtype is of the object dtype.
`api.types.is_period_dtype`(arr_or_dtype)	Check whether an array-like or dtype is of the Period dtype.
`api.types.is_signed_integer_dtype`(arr_or_dtype)	Check whether the provided array or dtype is of a signed integer dtype.
`api.types.is_string_dtype`(arr_or_dtype)	Check whether the provided array or dtype is of the string dtype.
`api.types.is_timedelta64_dtype`(arr_or_dtype)	Check whether an array-like or dtype is of the timedelta64 dtype.
`api.types.is_timedelta64_ns_dtype`(arr_or_dtype)	Check whether the provided array or dtype is of the timedelta64[ns] dtype.
`api.types.is_unsigned_integer_dtype`(arr_or_dtype)	Check whether the provided array or dtype is of an unsigned integer dtype.
`api.types.is_sparse`(arr)	Check whether an array-like is a 1-D pandas sparse array.

Iterable introspection

`api.types.is_dict_like`(obj)	Check if the object is dict-like.
`api.types.is_file_like`(obj)	Check if the object is a file-like object.
`api.types.is_list_like`	Check if the object is list-like.
`api.types.is_named_tuple`(obj)	Check if the object is a named tuple.
`api.types.is_iterator`	Check if the object is an iterator.

Scalar introspection

`api.types.is_bool`	Return True if given object is boolean.
`api.types.is_categorical`(arr)	Check whether an array-like is a Categorical instance.
`api.types.is_complex`	Return True if given object is complex.
`api.types.is_float`	Return True if given object is float.
`api.types.is_hashable`(obj)	Return True if hash(obj) will succeed, False otherwise.
`api.types.is_integer`	Return True if given object is integer.
`api.types.is_interval`
`api.types.is_number`(obj)	Check if the object is a number.
`api.types.is_re`(obj)	Check if the object is a regex pattern instance.
`api.types.is_re_compilable`(obj)	Check if the object can be compiled into a regex pattern instance.
`api.types.is_scalar`	Return True if given object is scalar.

Bug report function

show_versions([as_json])

Provide useful information, important for bug reports.

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Licensed under the 3-clause BSD License.
https://pandas.pydata.org/pandas-docs/version/1.3.4/reference/general_utility_functions.html