Change how data_frame_tool handles categorical columns

src/python/tests_extended/data_frame_tool.py

@@ -111,6 +111,8 @@ def _process_input_list(self, df, input_metas, require):
                 self._validate_type(input_meta, df[input_meta.name].dtype)
                 if (df[input_meta.name].dtype) == 'datetime64[ns]':
                     input_array = np.array([dt.timestamp() for dt in df[input_meta.name]]).astype(np.int64)
+                elif (str(df[input_meta.name].dtype)) == 'category':
+                    input_array = np.array([dt + 1 for dt in df[input_meta.name]]).astype(np.uint32) # in ONNX models trained in ML.NET "categorical columns" are 1 based, not 0 based                    
                 else:
                     # With strings we must cast first to np.object then then reshape
                     # so we do it for everything