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.AbstractMethodError(class_instance[, ...])	Raise this error instead of NotImplementedError for abstract methods while keeping compatibility with Python 2 and Python 3.
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.IntCastingNaNError	Raised when attempting an astype operation on an array with NaN to an integer dtype.
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.OptionError	Exception for pandas.options, backwards compatible with KeyError checks.
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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