fixing some over-indentation

Author: reidy-p

pandas/io/stata.py

@@ -1571,7 +1571,8 @@ def read(self, nrows=None, convert_dates=None,
                 else:
                     data_formatted.append((col, data[col]))
         if requires_type_conversion:
-            data = DataFrame(dict(data_formatted), columns=dict(data_formatted).keys())
+            data = DataFrame(dict(data_formatted),
+                             columns=dict(data_formatted).keys())
         del data_formatted
 
         self._do_convert_missing(data, convert_missing)
@@ -1609,7 +1610,8 @@ def read(self, nrows=None, convert_dates=None,
                     convert = True
                 retyped_data.append((col, data[col].astype(dtype)))
             if convert:
-                data = DataFrame(dict(retyped_data), columns=dict(retyped_data).keys())
+                data = DataFrame(dict(retyped_data),
+                                 columns=dict(retyped_data).keys())
 
         if index_col is not None:
             data = data.set_index(data.pop(index_col))
@@ -1722,7 +1724,8 @@ def _do_convert_categoricals(self, data, value_label_dict, lbllist,
                 cat_converted_data.append((col, cat_data))
             else:
                 cat_converted_data.append((col, data[col]))
-        data = DataFrame(dict(cat_converted_data), columns=dict(cat_converted_data).keys())
+        data = DataFrame(dict(cat_converted_data),
+                         columns=dict(cat_converted_data).keys())
         return data
 
     def data_label(self):
@@ -1997,7 +2000,8 @@ def _prepare_categoricals(self, data):
                 data_formatted.append((col, values))
             else:
                 data_formatted.append((col, data[col]))
-        return DataFrame(dict(data_formatted), columns=dict(data_formatted).keys())
+        return DataFrame(dict(data_formatted),
+                         columns=dict(data_formatted).keys())
 
     def _replace_nans(self, data):
         # return data

pandas/tests/frame/test_nonunique_indexes.py

@@ -217,7 +217,7 @@ def check(result, expected=None):
             expected_df = DataFrame({'A': expected_ser,
                                      'B': this_df['B'],
                                      'A': expected_ser},
-                                     columns=['A', 'B', 'A'])
+                                    columns=['A', 'B', 'A'])
             this_df['A'] = index
             check(this_df, expected_df)
 
@@ -328,8 +328,8 @@ def check(result, expected=None):
 
         df1r = df1.reindex_like(df2)
         result = df1r == df2
-        expected = DataFrame([[False, True], [True, False], [False, False], [
-                             True, False]], columns=['A', 'A'])
+        expected = DataFrame([[False, True], [True, False], [False, False],
+                             [True, False]], columns=['A', 'A'])
         assert_frame_equal(result, expected)
 
         # mixed column selection

pandas/tests/io/test_excel.py

@@ -328,9 +328,10 @@ def test_reader_special_dtypes(self):
             # GH5394 - this is why convert_float isn't vectorized
             "Str2Col": ["a", 3, "c", "d", "e"],
             "DateCol": [datetime(2013, 10, 30), datetime(2013, 10, 31),
-                         datetime(1905, 1, 1), datetime(2013, 12, 14),
-                         datetime(2015, 3, 14)]
-        }, columns=["IntCol", "FloatCol", "BoolCol", "StrCol", "Str2Col", "DateCol"])
+                        datetime(1905, 1, 1), datetime(2013, 12, 14),
+                        datetime(2015, 3, 14)]
+        }, columns=["IntCol", "FloatCol", "BoolCol",
+                    "StrCol", "Str2Col", "DateCol"])
 
         basename = 'test_types'