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https://issues.apache.org/jira/browse/BEAM-13966?focusedWorklogId=745035&page=com.atlassian.jira.plugin.system.issuetabpanels:worklog-tabpanel#worklog-745035
]
ASF GitHub Bot logged work on BEAM-13966:
-----------------------------------------
Author: ASF GitHub Bot
Created on: 21/Mar/22 13:06
Start Date: 21/Mar/22 13:06
Worklog Time Spent: 10m
Work Description: yeandy commented on a change in pull request #17043:
URL: https://github.com/apache/beam/pull/17043#discussion_r831083595
##########
File path: sdks/python/apache_beam/dataframe/frames_test.py
##########
@@ -2209,6 +2209,112 @@ def test_nlargest_any(self):
# but not necessarily with the same index
self.assert_frame_data_equivalent(result, df.population.nlargest(3))
+ def test_pivot_non_categorical(self):
+ df = pd.DataFrame({
+ 'foo': ['one', 'one', 'one', 'two', 'two', 'two'],
+ 'bar': ['A', 'B', 'C', 'A', 'B', 'C'],
+ 'baz': [1, 2, 3, 4, 5, 6],
+ 'zoo': ['x', 'y', 'z', 'q', 'w', 't']
+ })
+ with self.assertRaisesRegex(
+ frame_base.WontImplementError,
+ r"pivot\(\) of non-categorical type is not supported"):
+ self._evaluate(
+ lambda df: df.pivot(index='foo', columns='bar', values='baz'), df)
+
+ def test_pivot_pandas_example1(self):
+ # Simple test 1
+ df = pd.DataFrame({
+ 'foo': ['one', 'one', 'one', 'two', 'two', 'two'],
+ 'bar': ['A', 'B', 'C', 'A', 'B', 'C'],
+ 'baz': [1, 2, 3, 4, 5, 6],
+ 'zoo': ['x', 'y', 'z', 'q', 'w', 't']
+ })
+ df['bar'] = df['bar'].astype(
+ pd.CategoricalDtype(categories=['A', 'B', 'C']))
+ result = self._evaluate(
+ lambda df: df.pivot(index='foo', columns='bar', values='baz'), df)
+ self.assert_frame_data_equivalent(
+ result, df.pivot(index='foo', columns='bar', values='baz'))
+
+ def test_pivot_pandas_example2(self):
+ # Simple test 2
+ df = pd.DataFrame({
+ 'foo': ['one', 'one', 'one', 'two', 'two', 'two'],
+ 'bar': ['A', 'B', 'C', 'A', 'B', 'C'],
+ 'baz': [1, 2, 3, 4, 5, 6],
+ 'zoo': ['x', 'y', 'z', 'q', 'w', 't']
+ })
+ df['bar'] = df['bar'].astype(
+ pd.CategoricalDtype(categories=['A', 'B', 'C']))
+ result = self._evaluate(lambda df: df.pivot(index='foo', columns='bar'),
df)
+ self.assert_frame_data_equivalent(
+ result['baz'], df.pivot(index='foo', columns='bar')['baz'])
Review comment:
This test just selects the `baz` column, and the rest of `result` are
non-zero, non-nans found in the `zoo` column. So there's no good verification
to test. (unless we want to check that they are non-zero, non-nans?)
##########
File path: sdks/python/apache_beam/dataframe/frames_test.py
##########
@@ -2209,6 +2209,112 @@ def test_nlargest_any(self):
# but not necessarily with the same index
self.assert_frame_data_equivalent(result, df.population.nlargest(3))
+ def test_pivot_non_categorical(self):
+ df = pd.DataFrame({
+ 'foo': ['one', 'one', 'one', 'two', 'two', 'two'],
+ 'bar': ['A', 'B', 'C', 'A', 'B', 'C'],
+ 'baz': [1, 2, 3, 4, 5, 6],
+ 'zoo': ['x', 'y', 'z', 'q', 'w', 't']
+ })
+ with self.assertRaisesRegex(
+ frame_base.WontImplementError,
+ r"pivot\(\) of non-categorical type is not supported"):
+ self._evaluate(
+ lambda df: df.pivot(index='foo', columns='bar', values='baz'), df)
+
+ def test_pivot_pandas_example1(self):
+ # Simple test 1
+ df = pd.DataFrame({
+ 'foo': ['one', 'one', 'one', 'two', 'two', 'two'],
+ 'bar': ['A', 'B', 'C', 'A', 'B', 'C'],
+ 'baz': [1, 2, 3, 4, 5, 6],
+ 'zoo': ['x', 'y', 'z', 'q', 'w', 't']
+ })
+ df['bar'] = df['bar'].astype(
+ pd.CategoricalDtype(categories=['A', 'B', 'C']))
+ result = self._evaluate(
+ lambda df: df.pivot(index='foo', columns='bar', values='baz'), df)
+ self.assert_frame_data_equivalent(
+ result, df.pivot(index='foo', columns='bar', values='baz'))
Review comment:
SG, moved!
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Issue Time Tracking
-------------------
Worklog Id: (was: 745035)
Time Spent: 1h 10m (was: 1h)
> Implement DataFrame.pivot() for DataFrame API
> ---------------------------------------------
>
> Key: BEAM-13966
> URL: https://issues.apache.org/jira/browse/BEAM-13966
> Project: Beam
> Issue Type: Sub-task
> Components: dsl-dataframe, sdk-py-core
> Reporter: Andy Ye
> Assignee: Andy Ye
> Priority: P3
> Labels: dataframe-api
> Time Spent: 1h 10m
> Remaining Estimate: 0h
>
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