b5034279b48ae96ffdd4714f96e0f62b0f4807fc,category_encoders/ordinal.py,OrdinalEncoder,ordinal_encoding,#Any#Any#Any#Any#Any#,239

Before Change

            for switch in mapping:
                categories_dict = dict(switch.get("mapping"))
                column = switch.get("col")
                transformed_column = X[column].map(lambda x: categories_dict.get(x, np.nan))

                try:
                    transformed_column = transformed_column.astype(int)
                except ValueError as e:
                    transformed_column = transformed_column.astype(float)

                if impute_missing:

After Change

                    categories = [x for x in pd.unique(X[col].values) if x is not None]

                index = []
                values = []

                for i in range(len(categories)):
                    index.append(categories[i])
                    values.append(i + 1)

                mapping = pd.Series(data=values, index=index)

                mapping_out.append({"col": col, "mapping": mapping, "data_type": X[col].dtype}, )

        return X, mapping_out

Instances