zhengruifeng commented on code in PR #37569:
URL: https://github.com/apache/spark/pull/37569#discussion_r949049721
##########
python/pyspark/pandas/frame.py:
##########
@@ -12368,6 +12369,137 @@ def calculate_columns_axis(*cols: pd.Series) ->
pd.Series:
)
return first_series(DataFrame(internal))
+ def mode(self, axis: Axis = 0, numeric_only: bool = False, dropna: bool =
True) -> "DataFrame":
+ """
+ Get the mode(s) of each element along the selected axis.
+
+ The mode of a set of values is the value that appears most often.
+ It can be multiple values.
+
+ .. versionadded:: 3.4.0
+
+ Parameters
+ ----------
+ axis : {0 or 'index'}, default 0
+ Axis for the function to be applied on.
+ numeric_only : bool, default False
+ If True, only apply to numeric columns.
+ dropna : bool, default True
+ Don't consider counts of NaN/NaT.
+
+ Returns
+ -------
+ DataFrame
+ The modes of each column or row.
+
+ See Also
+ --------
+ Series.mode : Return the highest frequency value in a Series.
+ Series.value_counts : Return the counts of values in a Series.
+
+ Examples
+ --------
+ >>> df = ps.DataFrame([('bird', 2, 2),
+ ... ('mammal', 4, np.nan),
+ ... ('arthropod', 8, 0),
+ ... ('bird', 2, np.nan)],
+ ... index=('falcon', 'horse', 'spider', 'ostrich'),
+ ... columns=('species', 'legs', 'wings'))
+ >>> df
+ species legs wings
+ falcon bird 2 2.0
+ horse mammal 4 NaN
+ spider arthropod 8 0.0
+ ostrich bird 2 NaN
+
+ By default, missing values are not considered, and the mode of wings
+ are both 0 and 2. Because the resulting DataFrame has two rows,
+ the second row of ``species`` and ``legs`` contains ``NaN``.
+
+ >>> df.mode()
+ species legs wings
+ 0 bird 2.0 0.0
+ 1 None NaN 2.0
Review Comment:
Pandas use `NaN` instead of `None` to fill str column `species`, but I think
it's acceptable here.
```
>>> df.mode()
species legs wings
0 bird 2.0 0.0
1 NaN NaN 2.0
```
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