flake8 errors

Author: samuelsinayoko

pandas/core/frame.py

@@ -1211,7 +1211,8 @@ def to_records(self, index=True, convert_datetime64=True):
         """
         Convert DataFrame to record array.
 
-        Index will be put in the 'index' field of the record array if requested.
+        Index will be put in the 'index' field of the record array if
+        requested.
 
         Parameters
         ----------
@@ -1227,44 +1228,50 @@ def to_records(self, index=True, convert_datetime64=True):
 
         See Also
         --------
-        DataFrame.from_records: convert structured or record ndarray to DataFrame.
+        DataFrame.from_records: convert structured or record ndarray
+            to DataFrame.
+        numpy.recarray: ndarray that allows field access using
+            attributes, analogous to typed (typed) columns in a
+            spreadsheet.
 
         Examples
         --------
 
-        >>> df = pd.DataFrame({'col1': [1, 2], 'col2': [0.5, 0.75]}, index=['a', 'b'])
+        >>> df = pd.DataFrame({'A': [1, 2], 'B': [0.5, 0.75]},
+        ...                   index=['a', 'b'])
         >>> df
-           col1  col2
+           A  B
         a     1  0.50
         b     2  0.75
         >>> df.to_records()
         rec.array([('a', 1, 0.5 ), ('b', 2, 0.75)],
-                  dtype=[('index', 'O'), ('col1', '<i8'), ('col2', '<f8')])
+                  dtype=[('index', 'O'), ('A', '<i8'), ('B', '<f8')])
 
         The index can be excluded from the record array:
 
         >>> df.to_records(index=False)
         rec.array([(1, 0.5 ), (2, 0.75)],
-                  dtype=[('col1', '<i8'), ('col2', '<f8')])
+                  dtype=[('A', '<i8'), ('B', '<f8')])
 
         By default, timestamps are converted to `datetime.datetime`:
 
         >>> df.index = pd.date_range('2018-01-01 09:00', periods=2, freq='min')
         >>> df
-                             col1  col2
+                             A  B
         2018-01-01 09:00:00     1  0.50
         2018-01-01 09:01:00     2  0.75
         >>> df.to_records()
         rec.array([(datetime.datetime(2018, 1, 1, 9, 0), 1, 0.5 ),
                    (datetime.datetime(2018, 1, 1, 9, 1), 2, 0.75)],
-                  dtype=[('index', 'O'), ('col1', '<i8'), ('col2', '<f8')])
+                  dtype=[('index', 'O'), ('A', '<i8'), ('B', '<f8')])
 
-        The timestamp conversion can be disabled so NumPy's datetime64 data type is used instead:
+        The timestamp conversion can be disabled so NumPy's datetime64
+        data type is used instead:
 
         >>> df.to_records(convert_datetime64=False)
         rec.array([('2018-01-01T09:00:00.000000000', 1, 0.5 ),
                    ('2018-01-01T09:01:00.000000000', 2, 0.75)],
-                  dtype=[('index', '<M8[ns]'), ('col1', '<i8'), ('col2', '<f8')])
+                  dtype=[('index', '<M8[ns]'), ('A', '<i8'), ('B', '<f8')])
         """
         if index:
             if is_datetime64_any_dtype(self.index) and convert_datetime64: