Updated for style

Signed off by: Michael Erickson <[email protected]>

Author: Michael Erickson

swat/cas/table.py

@@ -5823,8 +5823,8 @@ def drop(self, labels, axis=0, level=None, inplace=False, errors='raise'):
 
     def drop_duplicates(self, casout, subset=[]):
         '''
-        Remove duplicate rows from a CASTable. Optionally, consider only a subset of columns
-        when checking for duplicate rows.
+        Remove duplicate rows from a CASTable. Optionally, consider only
+        a subset of columns when checking for duplicate rows.
 
         Parameters
         --------
@@ -5857,10 +5857,10 @@ def drop_duplicates(self, casout, subset=[]):
 
         # We run this aciton to drop duplicates from the original table
         # It is not returned -> we have to manually grab results from casout
-        self.groupby(subset)._retrieve('deduplication.deduplicate', casout=casout, noDuplicateKeys=True)
+        self.groupby(subset)._retrieve('deduplication.deduplicate',
+                                       casout=casout, noDuplicateKeys=True)
 
         # Fetch the output table
-        # out = self._retrieve('table.fetch', table={'name': casout.get('name'), 'caslib': casout.get('caslib')})['Fetch']
         if isinstance(casout, CASTable):
             out = casout
         elif isinstance(casout, dict):

swat/tests/cas/test_table.py

@@ -872,7 +872,9 @@ def test_drop_duplicates(self):
         tbl = self.table
         df = self.get_cars_df()
         # drop duplicates for single subset
-        tbl_dropped = tbl.drop_duplicates(casout={'replace': True, 'name':'drop-test-1'}, subset='Make')
+        tbl_dropped = tbl.drop_duplicates(casout={'replace': True,
+                                                  'name': 'drop-test-1'},
+                                          subset='Make')
         df_dropped = df.drop_duplicates(subset='Make')
 
         # Equivalent to pandas in size
@@ -882,7 +884,8 @@ def test_drop_duplicates(self):
         self.assertEquals(tbl_dropped['Make'].nunique(), len(tbl_dropped))
 
         # drop duplicates for multi-element subset
-        tbl_dropped_multi = tbl.drop_duplicates(casout={'replace': True, 'name':'drop-test-2'},
+        tbl_dropped_multi = tbl.drop_duplicates(casout={'replace': True,
+                                                         'name': 'drop-test-2'},
                                                 subset=['Origin', 'Type'])
         df_dropped_multi = df.drop_duplicates(subset=['Origin', 'Type'])
 
@@ -900,14 +903,16 @@ def test_drop_duplicates(self):
                                   {'name': 'Origin', 'type': 'CHAR', 'length': 6},
                                   {'name': 'DriveTrain', 'type': 'CHAR', 'length': 5}
                                   ]}
-        subset = self.s.upload_frame(fetchTable, casout={'replace': True, 'name':'drop-test-3'},
+        subset = self.s.upload_frame(fetchTable, casout={'replace': True,
+                                                         'name': 'drop-test-3'},
                                      importOptions=importOptions)
 
         # This table is like tbl, but with nDuplicate fully duplicate rows
         duplicate_table = tbl.append(subset)
 
         # Drop duplicates without subset (checks all cols)
-        tbl_dropped_all = duplicate_table.drop_duplicates(casout={'replace': True, 'name':'drop-test-4'})
+        tbl_dropped_all = duplicate_table.drop_duplicates(casout={'replace': True,
+                                                                  'name': 'drop-test-4'})
 
         # Make sure that the correct amount of rows were dropped
         self.assertEquals(len(tbl), len(tbl_dropped_all))