fix

Author: jona-sassenhagen

category_encoders/basen.py

@@ -253,8 +253,7 @@ def transform(self, X, override_return_df=False):
         X_out = self.basen_encode(X_out, cols=self.cols)
 
         if self.drop_invariant:
-            for col in self.drop_cols:
-                X_out.drop(col, 1, inplace=True)
+            X_out = X_out.drop(columns=self.drop_cols)
 
         # impute missing values only in the generated columns
         # generated_cols = util.get_generated_cols(X, X_out, self.cols)

category_encoders/hashing.py

@@ -202,8 +202,7 @@ def require_data(self, data_lock, new_start, done_index, hashing_parts, cols, pr
                 # Always get df and check it after merge all data parts
                 data_part = self.hashing_trick(X_in=data_part, hashing_method=self.hash_method, N=self.n_components, cols=self.cols)
                 if self.drop_invariant:
-                    for col in self.drop_cols:
-                        data_part.drop(col, 1, inplace=True)
+                    data_part = data_part.drop(columns=self.drop_cols)
                 part_index = int(math.ceil(end_index / self.max_sample))
                 hashing_parts.put({part_index: data_part})
                 if self.verbose == 5:

category_encoders/ordinal.py

@@ -209,8 +209,7 @@ def transform(self, X, override_return_df=False):
         )
 
         if self.drop_invariant:
-            for col in self.drop_cols:
-                )
+            X = X.drop(columns=self.drop_cols)
 
         if self.return_df or override_return_df:
             return X