Python 熊猫无法推断时间序列频率，尽管格式正确？

我有以下数据帧：

[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)

当我尝试将频率设置为每日时：

[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):
--> 893                 raise ValueError
    894         except ValueError as e:

ValueError: 

During handling of the above exception, another exception occurred:

ValueError                                Traceback (most recent call last)
<ipython-input-23-4e9469ef0e46> in <module>
----> 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
--> 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)
--> 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(
--> 907                     infer=inferred, passed=freq.freqstr
    908                 )
    909             )

ValueError: Inferred frequency None from passed values does not conform to passed frequency D

---

您的索引中可能没有连续的天数，但您有连续的月份：

ix = pd.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'],
                        dtype='datetime64[ns]', name='Date', freq=None)

ix.freq = 'D'

按预期工作，因为日期是连续的，因此您可以将频率设置为天；但是，如果我们将最后一个日期更改为非连续日期：

'1981-01-09'

您会收到错误，因为日期不是连续的，因此无法设置为

freq='D'

：

ix = pd.DatetimeIndex(['1981-01-01', '1981-01-02', '1981-01-03', '1981-01-04',
                       '1981-01-05', '1981-01-06', '1981-01-07', '1981-01-09'],
                        dtype='datetime64[ns]', name='Date', freq=None)

ix.freq = 'D'  

ix = pd.DatetimeIndex(['1981-01-01', '1981-01-02', '1981-01-03', '1981-01-04',
                       '1981-01-05', '1981-01-06', '1981-01-07', '1981-01-09'],
                        dtype='datetime64[ns]', name='Date', freq=None)

ix.freq = 'D'