Github user zero323 commented on a diff in the pull request:
https://github.com/apache/spark/pull/16792#discussion_r99465189
--- 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 --
@holdenk I am not convinced. I am intentionally trying to be a bit vague to
avoid suggestion that we support only `int` -> `int`or `float` -> `float`. We
cannot use abstract base class (`numbers.Real`?) because we depend on types,
not interfaces.
But if you feel strongly about it I'll trust your judgment. I would
probably write `TypeVar('T', str, Union[float, int])` but I am pretty sure it
wouldn't be welcome :) and I hope the other PR will make the requirements
explicit.
---
If your project is set up for it, you can reply to this email and have your
reply appear on GitHub as well. If your project does not have this feature
enabled and wishes so, or if the feature is enabled but not working, please
contact infrastructure at [email protected] or file a JIRA ticket
with INFRA.
---
---------------------------------------------------------------------
To unsubscribe, e-mail: [email protected]
For additional commands, e-mail: [email protected]
