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[MINOR][DOCS][PYTHON] Adding missing boolean type for replacement value in fillna #17688

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[MINOR][DOCS][PYTHON] Adding missing boolean type for replacement value in fillna #17688

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2 changes: 1 addition & 1 deletion python/pyspark/sql/dataframe.py
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Original file line number Diff line number Diff line change
Expand Up @@ -1238,7 +1238,7 @@ def fillna(self, value, subset=None):
Value to replace null values with.
If the value is a dict, then `subset` is ignored and `value` must be a mapping
from column name (string) to replacement value. The replacement value must be
an int, long, float, or string.
an int, long, float, boolean, or string.
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@HyukjinKwon HyukjinKwon Apr 23, 2017 •
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I think this indicates the replacement If the value is a dict whereas param value can't be a bool as below:

>>> from pyspark.sql import Row
>>> spark.createDataFrame([Row(a=None), Row(a=True)]).fillna({"a": True}).first()
Row(a=True)
>>> spark.createDataFrame([Row(a=None), Row(a=True)]).fillna(True).first()
Row(a=None)

I can't find def fill(value: Boolean) in functions.scala. Namely, (I guess) this will call it with int (a parent type). So,

>>> spark.createDataFrame([Row(a=None), Row(a=0)]).fillna(True).first()
Row(a=1)
>>> spark.createDataFrame([Row(a=None), Row(a=0)]).fillna(False).first()
Row(a=0)

So, the current status looks correct to me.

BTW, probably, we should throw an exception in

if not isinstance(value, (float, int, long, basestring, dict)):
    raise ValueError("value should be a float, int, long, string, or dict")

in Python boolean is a int - https://www.python.org/dev/peps/pep-0285/

  1. Should bool inherit from int?

=> Yes.

>>> isinstance(True, int)
True

However, this looks just a documentation fix and I guess there are many instances similar with it. I think it is fine with not fixing it here.

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That makes sense, I'd say that the eventual improvement would maybe be offering fill for bool for symetry with the rest of the types but its not necessary here rather than type checking for bool on the input.

:param subset: optional list of column names to consider.
Columns specified in subset that do not have matching data type are ignored.
For example, if `value` is a string, and subset contains a non-string column,
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4 changes: 4 additions & 0 deletions python/pyspark/sql/tests.py
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Expand Up @@ -1711,6 +1711,10 @@ def test_fillna(self):
self.assertEqual(row.age, None)
self.assertEqual(row.height, None)

# fillna with dictionary for boolean types
row = self.spark.createDataFrame([Row(a=None), Row(a=True)]).fillna({"a": True}).first()
self.assertEqual(row.a, True)

def test_bitwise_operations(self):
from pyspark.sql import functions
row = Row(a=170, b=75)
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