简单数据集,带有一个索引列(类型时间戳)和一个值列.
想获得数据的月平均值.

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

但是,当我分组时,我只得到索引的组而不是值

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')]}

尝试采用means()会导致错误：

尝试了df.head().resample(“M”,how =’mean’)和df.head().groupby(lambda x：x.month).mean()

并获取错误：DataError：没有要聚合的数字类型

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,**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,numeric_only)
   2356 
   2357     def _cython_agg_general(self,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,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