# 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.

## Exceptions and warnings

`errors.DtypeWarning` | Warning raised when reading different dtypes in a column from a file.
`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.OutOfBoundsDatetime` |
`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) | 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`(obj) | Check if the object is an iterator.

### Scalar introspection

`api.types.is_bool` |
`api.types.is_categorical`(arr) | Check whether an array-like is a Categorical instance.
`api.types.is_complex` |
`api.types.is_datetimetz`(arr) | (DEPRECATED) Check whether an array-like is a datetime array-like with a timezone component in its dtype.
`api.types.is_float` |
`api.types.is_hashable`(obj) | Return True if hash(obj) will succeed, False otherwise.
`api.types.is_integer` |
`api.types.is_interval` |
`api.types.is_number`(obj) | Check if the object is a number.
`api.types.is_period`(arr) | (DEPRECATED) Check whether an array-like is a periodical index.
`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 value is scalar.

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