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Posted to reviews@spark.apache.org by GitBox <gi...@apache.org> on 2022/03/21 08:25:52 UTC
[GitHub] [spark] Yikun commented on a change in pull request #35868: [SPARK-38576][PYTHON] Implement `numeric_only` parameter for `DataFrame/Series.rank` to rank numeric columns only
Yikun commented on a change in pull request #35868:
URL: https://github.com/apache/spark/pull/35868#discussion_r830850186
##########
File path: python/pyspark/pandas/series.py
##########
@@ -3540,8 +3540,10 @@ def quantile(psser: Series) -> Column:
return self._reduce_for_stat_function(quantile, name="quantile")
- # TODO: add axis, numeric_only, pct, na_option parameter
- def rank(self, method: str = "average", ascending: bool = True) -> "Series":
+ # TODO: add axis, pct, na_option parameter
+ def rank(
+ self, method: str = "average", ascending: bool = True, numeric_only: Optional[bool] = None
Review comment:
same test on None explictly
##########
File path: python/pyspark/pandas/tests/test_series.py
##########
@@ -1333,6 +1333,17 @@ def test_rank(self):
self.assert_eq(pser.rank(method="first"), psser.rank(method="first").sort_index())
self.assert_eq(pser.rank(method="dense"), psser.rank(method="dense").sort_index())
+ non_numeric_pser = pd.Series(["a", "c", "b", "d"], name="x", index=[10, 11, 12, 13])
+ non_numeric_psser = ps.from_pandas(non_numeric_pser)
+ self.assert_eq(
+ non_numeric_pser.rank(numeric_only=True).sort_index(),
+ non_numeric_psser.rank(numeric_only=True).sort_index(),
+ )
+ self.assert_eq(
+ (non_numeric_pser + "x").rank(numeric_only=True).sort_index(),
+ (non_numeric_psser + "x").rank(numeric_only=True).sort_index(),
+ )
Review comment:
```suggestion
self.assert_eq(
non_numeric_pser.rank(numeric_only=True),
non_numeric_psser.rank(numeric_only=True),
)
self.assert_eq(
(non_numeric_pser + "x").rank(numeric_only=True),
(non_numeric_psser + "x").rank(numeric_only=True),
)
```
I guess `sort.index` is useless in here, because we will get a empty series
##########
File path: python/pyspark/pandas/frame.py
##########
@@ -10239,8 +10239,10 @@ def any(self, axis: Axis = 0) -> "Series":
return first_series(DataFrame(internal))
- # TODO: add axis, numeric_only, pct, na_option parameter
- def rank(self, method: str = "average", ascending: bool = True) -> "DataFrame":
+ # TODO: add axis, pct, na_option parameter
+ def rank(
+ self, method: str = "average", ascending: bool = True, numeric_only: Optional[bool] = None
Review comment:
https://github.com/pandas-dev/pandas/blob/6033ed4b3383d874ee4a8a461724c0b8c2ca968d/pandas/core/generic.py#L8651-L8660
Consider rank=`None` would be deprecated in future in pandas, we might want to add a test on this (set `rank=None` expilictly), to make sure protect some behavior in future.
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