diff --git a/optimus/dataframe/columns.py b/optimus/dataframe/columns.py
index 63b470a1..649d938f 100644
--- a/optimus/dataframe/columns.py
+++ b/optimus/dataframe/columns.py
@@ -1462,7 +1462,7 @@ def nest(input_cols, shape="string", separator="", output_col=None):
 
         if shape is "vector":
             input_cols = parse_columns(self, input_cols, filter_by_column_dtypes=PYSPARK_NUMERIC_TYPES)
-
+            output_col = one_list_to_val(output_col)
             vector_assembler = VectorAssembler(
                 inputCols=input_cols,
                 outputCol=output_col)
diff --git a/optimus/ml/feature.py b/optimus/ml/feature.py
index 481da052..c8586867 100644
--- a/optimus/ml/feature.py
+++ b/optimus/ml/feature.py
@@ -38,18 +38,16 @@ def string_to_index(df, input_cols, output_cols=None, **kargs):
     :return: Dataframe with indexed columns.
     """
 
-    # input_cols = parse_columns(df, input_cols)
+    input_cols = parse_columns(df, input_cols)
     if output_cols is None:
-
         output_cols = [name_col(input_col, "index_to_string") for input_col in input_cols]
-    print(output_cols)
 
     indexers = [StringIndexer(inputCol=input_col, outputCol=output_col, **kargs).fit(df) for input_col, output_col
                 in zip(list(set(input_cols)), list(set(output_cols)))]
 
     pipeline = Pipeline(stages=indexers)
     df = pipeline.fit(df).transform(df)
-    # df.show()
+    
     return df