enhanced description of cat features param (#2627)

docs/Parameters.rst

@@ -659,7 +659,7 @@ IO Parameters
 
    -  add a prefix ``name:`` for column name, e.g. ``categorical_feature=name:c1,c2,c3`` means c1, c2 and c3 are categorical features
 
-   -  **Note**: only supports categorical with ``int`` type
+   -  **Note**: only supports categorical with ``int`` type (not applicable for data represented as pandas DataFrame in Python-package)
 
    -  **Note**: index starts from ``0`` and it doesn't count the label column when passing type is ``int``
 

include/LightGBM/config.h

@@ -613,7 +613,7 @@ struct Config {
   // desc = used to specify categorical features
   // desc = use number for index, e.g. ``categorical_feature=0,1,2`` means column\_0, column\_1 and column\_2 are categorical features
   // desc = add a prefix ``name:`` for column name, e.g. ``categorical_feature=name:c1,c2,c3`` means c1, c2 and c3 are categorical features
-  // desc = **Note**: only supports categorical with ``int`` type
+  // desc = **Note**: only supports categorical with ``int`` type (not applicable for data represented as pandas DataFrame in Python-package)
   // desc = **Note**: index starts from ``0`` and it doesn't count the label column when passing type is ``int``
   // desc = **Note**: all values should be less than ``Int32.MaxValue`` (2147483647)
   // desc = **Note**: using large values could be memory consuming. Tree decision rule works best when categorical features are presented by consecutive integers starting from zero