Add/fill pandas column based on range in rows from another dataframe

Working with pandas, I have df1 indexed by time samples:

data = '''\time       flags    input                  8228835.0  53153.0  32768.08228837.0  53153.0  32768.08228839.0  53153.0  32768.08228841.0  53153.0  32768.08228843.0  61345.0  32768.0'''fileobj = pd.compat.StringIO(data)df1 = pd.read_csv(fileobj, sep='\s+', index_col='time')

df2 indicates time ranges with start and end to define ranges where the state of 'check' is True:

data = '''\        check     start       end20536   True   8228837   822899320576   True   8232747   823286920554   True   8230621   823076120520   True   8227351   822750720480   True   8223549   822366920471   True   8221391   8221553'''fileobj = pd.compat.StringIO(data)df2 = pd.read_csv(fileobj, sep='\s+')

What I need to do is add a column for 'check' to df1 and fill out the actual time ranges defined in df2 with the value of True. All others should be False. An example result would be:

             flags    input    checktime                       8228835.0  53153.0  32768.0    False8228837.0  53153.0  32768.0    True8228839.0  53153.0  32768.0    True8228841.0  53153.0  32768.0    True8228843.0  61345.0  32768.0    True....8228994.0. 12424.0. 32768.0.   False