xarray_beam.Mean

class xarray_beam.Mean(dim, skipna=True, dtype=None, fanout=None)

Calculate the mean over one or more distributed dataset dimensions.

Parameters:

dim (Union[str, Sequence[str]]) –
skipna (bool) –
dtype (Union[dtype[Any], None, Type[Any], _SupportsDType[dtype[Any]], str, Tuple[Any, int], Tuple[Any, Union[SupportsIndex, Sequence[SupportsIndex]]], List[Any], _DTypeDict, Tuple[Any, Any]]) –
fanout (Optional[int]) –

__init__(dim, skipna=True, dtype=None, fanout=None)

Parameters:

dim (Union[str, Sequence[str]]) –
skipna (bool) –
dtype (Union[dtype[Any], None, Type[Any], _SupportsDType[dtype[Any]], str, Tuple[Any, int], Tuple[Any, Union[SupportsIndex, Sequence[SupportsIndex]]], List[Any], _DTypeDict, Tuple[Any, Any]]) –
fanout (Optional[int]) –

Return type:

None

Methods

`__init__`(dim[, skipna, dtype, fanout])
`annotations`()
`default_label`()
`default_type_hints`()
`display_data`()	Returns the display data associated to a pipeline component.
`expand`(pcoll)
`from_runner_api`(proto, context)
`get_resource_hints`()
`get_type_hints`()	Gets and/or initializes type hints for this object.
`get_windowing`(inputs)	Returns the window function to be associated with transform's output.
`infer_output_type`(unused_input_type)
`register_urn`(urn, parameter_type[, constructor])
`runner_api_requires_keyed_input`()
`to_runner_api`(context[, has_parts])
`to_runner_api_parameter`(unused_context)
`to_runner_api_pickled`(unused_context)
`type_check_inputs`(pvalueish)
`type_check_inputs_or_outputs`(pvalueish, ...)
`type_check_outputs`(pvalueish)
`with_input_types`(input_type_hint)	Annotates the input type of a `PTransform` with a type-hint.
`with_output_types`(type_hint)	Annotates the output type of a `PTransform` with a type-hint.
`with_resource_hints`(**kwargs)	Adds resource hints to the `PTransform`.

Attributes