DataFrame.replace with dict doesn't work when value=None

pandas/core/shared_docs.py

@@ -482,8 +482,8 @@
             - Dicts can be used to specify different replacement values
               for different existing values. For example,
               ``{{'a': 'b', 'y': 'z'}}`` replaces the value 'a' with 'b' and
-              'y' with 'z'. To use a dict in this way the `value`
-              parameter should be `None`.
+              'y' with 'z'. To use a dict in this way, the optional `value`
+              parameter should not be given.
             - For a DataFrame a dict can specify that different values
               should be replaced in different columns. For example,
               ``{{'a': 1, 'b': 'z'}}`` looks for the value 1 in column 'a'
@@ -494,8 +494,8 @@
               specifying the column to search in.
             - For a DataFrame nested dictionaries, e.g.,
               ``{{'a': {{'b': np.nan}}}}``, are read as follows: look in column
-              'a' for the value 'b' and replace it with NaN. The `value`
-              parameter should be ``None`` to use a nested dict in this
+              'a' for the value 'b' and replace it with NaN. The optional `value`
+              parameter should not be specified to use a nested dict in this
               way. You can nest regular expressions as well. Note that
               column names (the top-level dictionary keys in a nested
               dictionary) **cannot** be regular expressions.