TheNeuralBit commented on a change in pull request #15773:
URL: https://github.com/apache/beam/pull/15773#discussion_r741336462
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File path: sdks/python/apache_beam/dataframe/frames.py
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@@ -1500,6 +1500,23 @@ def dropna(self, **kwargs):
preserves_partition_by=partitionings.Arbitrary(),
requires_partition_by=partitionings.Arbitrary()))
+ @frame_base.with_docs_from(pd.Series)
+ @frame_base.args_to_kwargs(pd.Series)
+ @frame_base.populate_defaults(pd.Series)
+ @frame_base.maybe_inplace
+ def set_axis(self, labels, **kwargs):
+ index = pd.Index([], dtype=np.asarray(labels).dtype)
+ proxy = self._expr.proxy().copy()
+ proxy.index = index
+ with expressions.allow_non_parallel_operations(True):
+ return frame_base.DeferredFrame.wrap(
+ expressions.ComputedExpression(
+ 'set_axis',
+ lambda s: s.set_axis(labels, **kwargs), [self._expr],
+ proxy=proxy,
+ requires_partition_by=partitionings.Singleton(),
+ preserves_partition_by=partitionings.Singleton()))
Review comment:
`Series.set_axis` is the same as `DataFrame.set_axis` with `axis=index`
(since there are no column names to assign). So this method should always raise
like the latter.
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