374ca541aaf62aba88a144acbbc7398ca3e995ef,category_encoders/ordinal.py,OrdinalEncoder,ordinal_encoding,#Any#Any#Any#Any#Any#,255

Before Change

                if util.is_category(X[col].dtype):
                    categories = X[col].cat.categories
                else:
                    categories = [x if x is not None else np.nan for x in pd.unique(X[col].values)]

                data = {}

After Change

                else:
                    categories = X[col].unique()

                index = pd.Series(categories).fillna(nan_identity).unique()

                data = pd.Series(index=index, data=range(1, len(index) + 1))

                if handle_missing == "value" and ~data.index.isnull().any():
                    data.loc[nan_identity] = -2
                elif handle_missing == "return_nan":
                    data.loc[nan_identity] = -2

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

        return X, mapping_out

Instances