title: Add/fill pandas column based on range in rows from another dataframe
body: <p>Working with pandas, I have df1 indexed by time samples:</p>
  
  <pre><code>data = '''\
  time       flags    input                  
  8228835.0  53153.0  32768.0
  8228837.0  53153.0  32768.0
  8228839.0  53153.0  32768.0
  8228841.0  53153.0  32768.0
  8228843.0  61345.0  32768.0'''
  
  fileobj = pd.compat.StringIO(data)
  df1 = pd.read_csv(fileobj, sep='\s+', index_col='time')
  </code></pre>
  
  <p>df2 indicates time ranges with start and end to define ranges where the state of 'check' is True:</p>
  
  <pre><code>data = '''\
          check     start       end
  20536   True   8228837   8228993
  20576   True   8232747   8232869
  20554   True   8230621   8230761
  20520   True   8227351   8227507
  20480   True   8223549   8223669
  20471   True   8221391   8221553'''
  
  fileobj = pd.compat.StringIO(data)
  df2 = pd.read_csv(fileobj, sep='\s+')
  </code></pre>
  
  <p>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:</p>
  
  <pre><code>             flags    input    check
  time                       
  8228835.0  53153.0  32768.0    False
  8228837.0  53153.0  32768.0    True
  8228839.0  53153.0  32768.0    True
  8228841.0  53153.0  32768.0    True
  8228843.0  61345.0  32768.0    True
  ....
  8228994.0. 12424.0. 32768.0.   False
  </code></pre>