title: Pandas not able to infer time series frequency, despite proper formatting?
body: <p>I have the following dataframe:</p>
  
  <pre><code>[1] df.index 
  [1] DatetimeIndex(['1981-01-01', '1981-01-02', '1981-01-03', '1981-01-04',
                 '1981-01-05', '1981-01-06', '1981-01-07', '1981-01-08',
                 '1981-01-09', '1981-01-10',
                 ...
                 '1990-12-22', '1990-12-23', '1990-12-24', '1990-12-25',
                 '1990-12-26', '1990-12-27', '1990-12-28', '1990-12-29',
                 '1990-12-30', '1990-12-31'],
                dtype='datetime64[ns]', name='Date', length=3650, freq=None)
  </code></pre>
  
  <p>When I try to set the frequency to daily: </p>
  
  <pre><code>[2] df.index
  ---------------------------------------------------------------------------
  ValueError                                Traceback (most recent call last)
  /usr/local/lib/python3.5/dist-packages/pandas/core/arrays/datetimelike.py in _validate_frequency(cls, index, freq, **kwargs)
      892             if not np.array_equal(index.asi8, on_freq.asi8):
  --&gt; 893                 raise ValueError
      894         except ValueError as e:
  
  ValueError: 
  
  During handling of the above exception, another exception occurred:
  
  ValueError                                Traceback (most recent call last)
  &lt;ipython-input-23-4e9469ef0e46&gt; in &lt;module&gt;
  ----&gt; 1 df.index.freq = 'D'
  
  /usr/local/lib/python3.5/dist-packages/pandas/core/indexes/datetimelike.py in freq(self, value)
       98     def freq(self, value):
       99         # validation is handled by _data setter
  --&gt; 100         self._data.freq = value
      101 
      102     @property
  
  /usr/local/lib/python3.5/dist-packages/pandas/core/arrays/datetimelike.py in freq(self, value)
      829         if value is not None:
      830             value = frequencies.to_offset(value)
  --&gt; 831             self._validate_frequency(self, value)
      832 
      833         self._freq = value
  
  /usr/local/lib/python3.5/dist-packages/pandas/core/arrays/datetimelike.py in _validate_frequency(cls, index, freq, **kwargs)
      905                 "Inferred frequency {infer} from passed values "
      906                 "does not conform to passed frequency {passed}".format(
  --&gt; 907                     infer=inferred, passed=freq.freqstr
      908                 )
      909             )
  
  ValueError: Inferred frequency None from passed values does not conform to passed frequency D
  </code></pre>
  
  <p>Note that when I do the same thing for a monthly data set, it works fine:</p>
  
  <pre><code>[1] df.index
  [1] DatetimeIndex(['1985-01-01', '1985-02-01', '1985-03-01', '1985-04-01',
                 '1985-05-01', '1985-06-01', '1985-07-01', '1985-08-01',
                 '1985-09-01', '1985-10-01',
                 ...
                 '2017-04-01', '2017-05-01', '2017-06-01', '2017-07-01',
                 '2017-08-01', '2017-09-01', '2017-10-01', '2017-11-01',
                 '2017-12-01', '2018-01-01'],
                dtype='datetime64[ns]', name='DATE', length=397, freq=None)
  [2] df.index.freq = 'MS'
  [2] DatetimeIndex(['1985-01-01', '1985-02-01', '1985-03-01', '1985-04-01',
                 '1985-05-01', '1985-06-01', '1985-07-01', '1985-08-01',
                 '1985-09-01', '1985-10-01',
                 ...
                 '2017-04-01', '2017-05-01', '2017-06-01', '2017-07-01',
                 '2017-08-01', '2017-09-01', '2017-10-01', '2017-11-01',
                 '2017-12-01', '2018-01-01'],
                dtype='datetime64[ns]', name='DATE', length=397, freq='MS')
  </code></pre>