title: how to fill missing dates group by in pandas DataFrame
body: <p>my initial dataframe is</p>
  
  <pre><code>df = pd.DataFrame({"a":["2020-01-01", "2020-01-06", "2020-01-04", "2020-01-07"],
                     "b":["a", "a", "b", "b"],
                     "c":[1, 2, 3,4]})
  print(df)
              a  b  c
  0  2020-01-01  a  1
  1  2020-01-06  a  2
  2  2020-01-04  b  3
  3  2020-01-07  b  4
  </code></pre>
  
  <p>I want my dataset to be like this</p>
  
  <pre><code>            a  b  c
  0  2020-01-01  a  1
  1  2020-01-02  a  NaN
  2  2020-01-03  a  NaN
  3  2020-01-04  a  NaN
  4  2020-01-05  a  NaN
  5  2020-01-06  a  2
  6  2020-01-04  b  3
  7  2020-01-05  b  NaN
  8  2020-01-06  b  NaN
  3  2020-01-07  b  4
  </code></pre>
  
  <p>I tried</p>
  
  <pre><code>d.set_index([d.a, d.b], inplace=True)
  d.asfreq("D")
  
  d.set_index([d.a, d.b], inplace=True)
  d.resample("D")
  </code></pre>
  
  <p>but I encountered</p>
  
  <pre><code>TypeError: Only valid with DatetimeIndex, TimedeltaIndex or PeriodIndex, but got an instance of 'MultiIndex'
  enter code here
  </code></pre>
  
  <p>My real DataFrame's column ('b' column in this example) has many unique values.</p>