Github user HyukjinKwon commented on a diff in the pull request:
https://github.com/apache/spark/pull/17737#discussion_r114049248
--- Diff: python/pyspark/sql/column.py ---
@@ -185,17 +185,51 @@ def __contains__(self, item):
"in a string column or 'array_contains' function
for an array column.")
# bitwise operators
- bitwiseOR = _bin_op("bitwiseOR")
- bitwiseAND = _bin_op("bitwiseAND")
- bitwiseXOR = _bin_op("bitwiseXOR")
+ _bitwiseOR_doc = """
+ Compute bitwise OR of this expression with another expression.
+
+ :param other: a value or :class:`Column` to calculate bitwise or(|)
against
+ this :class:`Column`.
+
+ >>> from pyspark.sql import Row
+ >>> df3 = spark.createDataFrame([Row(a=170, b=75)])
--- End diff --
I think there is a global `df` variable when running doctests and I guess
it was avoided to shadow the same name from the outer scope in some doctests
whereas other doctests just use it. I get your point. In documentation, we will
only see only the code block and I guess using `df` might be slightly better.
AFAIK, usually, Python documentation have self-contained doctests so I
don't know which case is better and correct. If you could confirm this, I can
sweep it.
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