prepare release 2.6.3

scikit-learn-contrib · Oct 29, 2023 · 26ef261 · 26ef261
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diff --git a/CHANGELOG.md b/CHANGELOG.md
@@ -1,6 +1,12 @@
 unreleased
 ==========
 
+v2.6.3
+======
+* fixed: issue 424 - pandas NaNs
+* fixed: pandas deprecations and ruff linter suggestions
+* fixed: issue 421 - detect pandas categorical type as categorical column
+
 v2.6.2
 ======
 * fixed: issue 414 - broken link

diff --git a/category_encoders/__init__.py b/category_encoders/__init__.py
@@ -28,7 +28,7 @@
 from category_encoders.quantile_encoder import QuantileEncoder, SummaryEncoder
 
 
-__version__ = '2.6.2'
+__version__ = '2.6.3'
 
 __author__ = "willmcginnis", "cmougan", "paulwestenthanner"
 

diff --git a/docs/source/index.rst b/docs/source/index.rst
@@ -75,7 +75,7 @@ All of these are fully compatible sklearn transformers, so they can be used in p
 the cols parameter isn't passed, every non-numeric column will be converted. See below for detailed documentation
 
 Known issues:
-----
+-------------
 
 `CategoryEncoders` internally works with `pandas DataFrames` as apposed to `sklearn` which works with `numpy arrays`. This can cause problems in `sklearn` versions prior to 1.2.0. In order to ensure full compatibility with `sklearn` set `sklearn` to also output `DataFrames`. This can be done by
 
@@ -97,7 +97,7 @@ for a whole project or just for a single pipeline using
 If you experience another bug, feel free to report it on [github](https://github.com/scikit-learn-contrib/category_encoders/issues)
 
 Contents:
-----
+---------
 
 .. toctree::
    :maxdepth: 3