Make all operations on DataFrameMapper.transformed_names_ atomic. (#194)

Co-authored-by: Ritesh Agrawal <[email protected]>

Author: FlorisHoogenboom

sklearn_pandas/dataframe_mapper.py

@@ -304,7 +304,7 @@ def _transform(self, X, y=None, do_fit=False):
             self._build()
 
         extracted = []
-        self.transformed_names_ = []
+        transformed_names_ = []
         for columns, transformers, options in self.built_features:
             input_df = options.get('input_df', self.input_df)
 
@@ -333,10 +333,11 @@ def _transform(self, X, y=None, do_fit=False):
             extracted.append(_handle_feature(Xt))
 
             alias = options.get('alias')
+
             prefix = options.get('prefix', '')
             suffix = options.get('suffix', '')
 
-            self.transformed_names_ += self.get_names(
+            transformed_names_ += self.get_names(
                 columns, transformers, Xt, alias, prefix, suffix)
 
         # handle features not explicitly selected
@@ -351,15 +352,17 @@ def _transform(self, X, y=None, do_fit=False):
                         if do_fit:
                             _call_fit(self.built_default.fit, Xt, y)
                         Xt = self.built_default.transform(Xt)
-                self.transformed_names_ += self.get_names(
+                transformed_names_ += self.get_names(
                     unsel_cols, self.built_default, Xt)
             else:
                 # if not applying a default transformer,
                 # keep column names unmodified
-                self.transformed_names_ += unsel_cols
+                transformed_names_ += unsel_cols
 
             extracted.append(_handle_feature(Xt))
 
+        self.transformed_names_ = transformed_names_
+
         # combine the feature outputs into one array.
         # at this point we lose track of which features
         # were created from which input columns, so it's