获取GroupBy的Pandas的平均值-获取数据错误：aggreg没有数字类型

Question

我知道有很多问题，比如Getting daily averages with pandas 还有How get monthly mean in pandas using groupby但是我有个奇怪的错误。

简单数据集，有一个索引列（类型timestamp）和一个值列。 想得到数据的月平均值。

In [76]: df.head()
Out[76]: 
                          A
2008-01-02                1
2008-01-03                2
2008-01-04                3
2008-01-07                4
2008-01-08                5

然而，当我分组时，我只得到索引的组而不是值的组

In [74]: df.head().groupby(lambda x: x.month).groups
Out[74]: 
{1: [Timestamp('2008-01-02 00:00:00'),
  Timestamp('2008-01-03 00:00:00'),
  Timestamp('2008-01-04 00:00:00'),
  Timestamp('2008-01-07 00:00:00'),
  Timestamp('2008-01-08 00:00:00')]}

尝试使用means（）会导致错误：

尝试过df.head().resample("M", how='mean')和df.head().groupby(lambda x: x.month).mean()

并获取错误：DataError: No numeric types to aggregate

In [75]: df.resample("M", how='mean')
---------------------------------------------------------------------------
DataError                                 Traceback (most recent call last)
<ipython-input-75-79dc1a060ba4> in <module>()
----> 1 df.resample("M", how='mean')

/usr/local/lib/python2.7/site-packages/pandas/core/generic.pyc in resample(self, rule, how, axis, fill_method, closed, label, convention, kind, loffset, limit, base)
   2878                               fill_method=fill_method, convention=convention,
   2879                               limit=limit, base=base)
-> 2880         return sampler.resample(self).__finalize__(self)
   2881 
   2882     def first(self, offset):

/usr/local/lib/python2.7/site-packages/pandas/tseries/resample.pyc in resample(self, obj)
     82 
     83         if isinstance(ax, DatetimeIndex):
---> 84             rs = self._resample_timestamps()
     85         elif isinstance(ax, PeriodIndex):
     86             offset = to_offset(self.freq)

/usr/local/lib/python2.7/site-packages/pandas/tseries/resample.pyc in _resample_timestamps(self)
    286             # Irregular data, have to use groupby
    287             grouped = obj.groupby(grouper, axis=self.axis)
--> 288             result = grouped.aggregate(self._agg_method)
    289 
    290             if self.fill_method is not None:

/usr/local/lib/python2.7/site-packages/pandas/core/groupby.pyc in aggregate(self, arg, *args, **kwargs)
   2436     def aggregate(self, arg, *args, **kwargs):
   2437         if isinstance(arg, compat.string_types):
-> 2438             return getattr(self, arg)(*args, **kwargs)
   2439 
   2440         result = OrderedDict()

/usr/local/lib/python2.7/site-packages/pandas/core/groupby.pyc in mean(self)
    664         """
    665         try:
--> 666             return self._cython_agg_general('mean')
    667         except GroupByError:
    668             raise

/usr/local/lib/python2.7/site-packages/pandas/core/groupby.pyc in _cython_agg_general(self, how, numeric_only)
   2356 
   2357     def _cython_agg_general(self, how, numeric_only=True):
-> 2358         new_items, new_blocks = self._cython_agg_blocks(how, numeric_only=numeric_only)
   2359         return self._wrap_agged_blocks(new_items, new_blocks)
   2360 

/usr/local/lib/python2.7/site-packages/pandas/core/groupby.pyc in _cython_agg_blocks(self, how, numeric_only)
   2406 
   2407         if len(new_blocks) == 0:
-> 2408             raise DataError('No numeric types to aggregate')
   2409 
   2410         return data.items, new_blocks

DataError: No numeric types to aggregate

Answer 1

是的，您应该尝试将A强制为类似df['A'] = df['A'].astype(int)的数值。可能值得检查的是，在读取的初始数据中是否有任何东西导致它成为对象，而不是数字。