Question

我有一个pandas数据帧：

    name    my_timestamp
------------------------------------------
0   a1      2016-07-28 09:27:07.536963-07:00
1   a2      2016-07-28 09:27:07.536963-07:00
2   a3      2016-08-15 13:05:54.924185-07:00
3   a4      2016-08-30 04:04:18.971667-07:00
4   a5      2016-03-22 14:36:22.999825-07:00
5   a6      2016-08-30 04:04:18.971667-07:00

我正在尝试过滤我的pandas数据框中的某些行，如下所示：

import datetime
my_df[my_df.my_timestamp > datetime.datetime(2016, 7, 1)]

但是得到以下错误：

TypeErrorTraceback (most recent call last)
<ipython-input-21-35be746f191d> in <module>()
      1 import datetime
----> 2 my_df[my_df.my_timestamp > datetime.datetime(2016, 7, 1)]

/usr/local/lib/python2.7/dist-packages/pandas/core/ops.pyc in wrapper(self, other, axis)
    761                 other = np.asarray(other)
    762 
--> 763             res = na_op(values, other)
    764             if isscalar(res):
    765                 raise TypeError('Could not compare %s type with Series' %

/usr/local/lib/python2.7/dist-packages/pandas/core/ops.pyc in na_op(x, y)
    681                     result = lib.vec_compare(x, y, op)
    682             else:
--> 683                 result = lib.scalar_compare(x, y, op)
    684         else:
    685 

pandas/lib.pyx in pandas.lib.scalar_compare (pandas/lib.c:14261)()

TypeError: can't compare offset-naive and offset-aware date times

这似乎是时区问题。在这里忽略时区的最佳方法是什么？谢谢！

Answer 1

假设数据框中的所有时间戳都在同一时区：

tz_info = my_df.iloc[0].my_timestamp.tzinfo
my_df[my_df.my_timestamp > datetime.datetime(2016, 7, 1, tzinfo=tz_info)]

pandas过滤日期时间：TypeError：无法比较offset-naive和offset-aware datetimes

1 个答案: