我知道有很多问题,例如Getting daily averages with pandas 和How get monthly mean in pandas using groupby,但我得到一个奇怪的错误。
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
然而,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')]}
尝试使用means()导致错误:
已尝试过df.head().resample("M", how='mean')
和df.head().groupby(lambda x: x.month).mean()
并收到错误: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
答案 0 :(得分:10)
是的,您应该尝试将A
强制转换为df['A'] = df['A'].astype(int)
之类的数字。可能值得检查初始数据读入中是否有任何内容导致它成为对象而不是数字。