实际问题
就像这个小例子所示,我试图对一个pandas数据帧进行每周重新采样:
import datetime
import pandas as pd
df = pd.DataFrame([{
'A' : datetime.datetime.now() - datetime.datetime.now(),
'B' : 2
},{
'A' : datetime.datetime.now() - datetime.datetime.now(),
'B' : 3
}])
df = df.set_index('A')
df.resample('W', how="mean")
这会抛出一个 AttributeError
异常:
AttributeError: 'Week' object has no attribute 'nanos'
(注意:如果我使用“D”重新采样,则不会出现问题)
如果我将索引转换为日期时间:
df.index = pd.to_datetime(df.index.values)
df.resample('W', how="mean")
重新采样也可以工作。
问题:是否有一种不依赖于纳秒的Pandas时间差类型?
或者:您是否有比利用datetime
进行timedelta
更优雅的方式?
完整跟踪:
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
File "/Library/Python/2.7/site-packages/pandas/core/generic.py", line 3266, in resample
return sampler.resample(self).__finalize__(self)
File "/Library/Python/2.7/site-packages/pandas/tseries/resample.py", line 98, in resample
rs = self._resample_timestamps(kind='timedelta')
File "/Library/Python/2.7/site-packages/pandas/tseries/resample.py", line 272, in _resample_timestamps
self._get_binner_for_resample(kind=kind)
File "/Library/Python/2.7/site-packages/pandas/tseries/resample.py", line 122, in _get_binner_for_resample
self.binner, bins, binlabels = self._get_time_delta_bins(ax)
File "/Library/Python/2.7/site-packages/pandas/tseries/resample.py", line 236, in _get_time_delta_bins
name=ax.name)
File "/Library/Python/2.7/site-packages/pandas/tseries/tdi.py", line 167, in __new__
closed=closed)
File "/Library/Python/2.7/site-packages/pandas/tseries/tdi.py", line 235, in _generate
index = _generate_regular_range(start, end, periods, offset)
File "/Library/Python/2.7/site-packages/pandas/tseries/tdi.py", line 895, in _generate_regular_range
stride = offset.nanos
AttributeError: 'Week' object has no attribute 'nanos'
版本
>>> pd.__version__
'0.16.2'
>>> np.__version__
'1.10.1'