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移除书签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. |
