Github user holdenk commented on a diff in the pull request:
https://github.com/apache/spark/pull/16792#discussion_r99470045
--- 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
+ replacements are not supported.
- :param to_replace: int, long, float, string, or list.
+ :param to_replace: int, long, float, string, list or dict.
Value to be replaced.
If the value is a dict, then `value` is ignored and
`to_replace` must be a
- mapping from column name (string) to replacement value. The
value to be
- replaced must be an int, long, float, or string.
+ mapping between a value and a replacement.
:param value: int, long, float, string, or list.
- Value to use to replace holes.
The replacement value must be an int, long, float, or string.
If `value` is a
- list or tuple, `value` should be of the same length with
`to_replace`.
+ list, `value` should be of the same length and type as
`to_replace`.
+ If `value` is a scalar and `to_replace` is a sequence, then
`value` is replicated
--- End diff --
This is true, but perhaps it would be clearer to say if value is a scalar
and to_replace is a sequence then value is used as the replacement for every
instance in to_replace. (Since that is the effect the user sees - they don't
really need to know that we are copying it internally in a list).
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