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Posted to reviews@spark.apache.org by GitBox <gi...@apache.org> on 2022/11/25 17:05:28 UTC
[GitHub] [spark] zero323 commented on a diff in pull request #38020: [SPARK-39877][FOLLOW-UP] PySpark DataFrame.unpivot allows for column names only
zero323 commented on code in PR #38020:
URL: https://github.com/apache/spark/pull/38020#discussion_r1032609227
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python/pyspark/sql/dataframe.py:
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@@ -3175,12 +3177,12 @@ def melt(
Parameters
----------
- ids : str, Column, tuple, list, optional
- Column(s) to use as identifiers. Can be a single column or column name,
- or a list or tuple for multiple columns.
- values : str, Column, tuple, list, optional
- Column(s) to unpivot. Can be a single column or column name, or a list or tuple
- for multiple columns. If not specified or empty, uses all columns that
+ ids : str, list, tuple, optional
+ Column name(s) to use as identifiers. Can be a single column name,
+ or a list or tuple for multiple column names.
+ values : str, list, tuple, optional
Review Comment:
Seems like `values` shouldn't be described as an optional, as it is a required argument. How about something like this?
```python
values : str, Column, tuple, list or None
Column(s) to unpivot. Can be a single column or column name, or a list or tuple
for multiple columns. If specified, and not `None` must not be empty. If `None` uses all
columns that are not set as `ids`.
```
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