Github user zero323 commented on a diff in the pull request:
https://github.com/apache/spark/pull/16792#discussion_r99486909
--- Diff: python/pyspark/sql/dataframe.py ---
@@ -1272,16 +1272,18 @@ def replace(self, to_replace, value, subset=None):
"""Returns a new :class:`DataFrame` replacing a value with another
value.
:func:`DataFrame.replace` and :func:`DataFrameNaFunctions.replace`
are
aliases of each other.
+ Values `to_replace` and `value` should be homogeneous. Mixed
string and numeric
--- End diff --
Challenge accepted :)
This makes me think we should also document uniqueness requirements. User
might expect that:
```
df.replace([1, 1.0], [2, 3.0])
```
or
```
df.replace({1: 2, 1.0: 3.0})
```
when in fact there will be only one pair considered.
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