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Posted to reviews@spark.apache.org by GitBox <gi...@apache.org> on 2022/03/17 00:02:38 UTC
[GitHub] [spark] xinrong-databricks commented on a change in pull request #35868: Implement `numeric_only` parameter for `DataFrame/Series.rank` to rank numeric columns only
xinrong-databricks commented on a change in pull request #35868:
URL: https://github.com/apache/spark/pull/35868#discussion_r828546722
##########
File path: python/pyspark/pandas/series.py
##########
@@ -3618,8 +3622,25 @@ def rank(self, method: str = "average", ascending: bool = True) -> "Series":
2 2.0
3 3.0
Name: A, dtype: float64
+
+ If numeric_only is set to 'True', rank only numeric Series,
+ return an empty Series otherwise.
+
+ >>> s = ps.Series(['a', 'b', 'c'], name='A', index=['x', 'y', 'z'])
+ >>> s
+ x a
+ y b
+ z c
+ Name: A, dtype: object
+
+ >>> s.rank(numeric_only=True)
+ Series([], Name: A, dtype: float64)
"""
- return self._rank(method, ascending).spark.analyzed
+ is_numeric = isinstance(self.spark.data_type, (NumericType, BooleanType))
+ if numeric_only and not is_numeric:
+ return ps.Series([], dtype="float64", name=self.name)
Review comment:
Following pandas' behavior.
##########
File path: python/pyspark/pandas/series.py
##########
@@ -3618,8 +3622,25 @@ def rank(self, method: str = "average", ascending: bool = True) -> "Series":
2 2.0
3 3.0
Name: A, dtype: float64
+
+ If numeric_only is set to 'True', rank only numeric Series,
+ return an empty Series otherwise.
+
+ >>> s = ps.Series(['a', 'b', 'c'], name='A', index=['x', 'y', 'z'])
+ >>> s
+ x a
+ y b
+ z c
+ Name: A, dtype: object
+
+ >>> s.rank(numeric_only=True)
+ Series([], Name: A, dtype: float64)
"""
- return self._rank(method, ascending).spark.analyzed
+ is_numeric = isinstance(self.spark.data_type, (NumericType, BooleanType))
+ if numeric_only and not is_numeric:
+ return ps.Series([], dtype="float64", name=self.name)
Review comment:
Following pandas' behavior.
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