Transurgeon commented on code in PR #37444:
URL: https://github.com/apache/spark/pull/37444#discussion_r953047129
##########
python/pyspark/sql/dataframe.py:
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@@ -3356,11 +3476,29 @@ def drop(self, *cols: "ColumnOrName") -> "DataFrame":
# type: ignore[misc]
Examples
--------
+ >>> df = spark.createDataFrame([(14, "Tom"), (23, "Alice"), (16,
"Bob")], ["age", "name"])
+ >>> df.show()
+ +---+-----+
+ |age| name|
+ +---+-----+
+ | 14| Tom|
+ | 23|Alice|
+ | 16| Bob|
+ +---+-----+
>>> df.drop('age').collect()
- [Row(name='Alice'), Row(name='Bob')]
+ [Row(name='Tom'), Row(name='Alice'), Row(name='Bob')]
+ >>> df = spark.createDataFrame([(14, "Tom"), (23, "Alice"), (16,
"Bob")], ["age", "name"])
+ >>> df.show()
+ +---+-----+
+ |age| name|
+ +---+-----+
+ | 14| Tom|
+ | 23|Alice|
+ | 16| Bob|
+ +---+-----+
>>> df.drop(df.age).collect()
- [Row(name='Alice'), Row(name='Bob')]
+ [Row(name='Tom'), Row(name='Alice'), Row(name='Bob')]
>>> df.join(df2, df.name == df2.name, 'inner').drop(df.name).collect()
Review Comment:
I am not sure what these 3 inner joins do exactly. I dont see anywhere an
instantiation of df2..
What should I do with these 3 examples?
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