Question

我有pandas系列，其中index是整数列表（时间戳），如何将它们转换为datetime.datetime（带时区）比低于原始转换更有效？

pd.Series(data=s.values, index=map(lambda x:datetime.datetime.fromtimestamp(x,tz=utc), s.index))

Answer 1

In [49]: s = Series(range(10))

使用to_datetime，您可以提供一个单位来选择整数的含义。

In [50]: pd.to_datetime(s,unit='s')
Out[50]: 
0   1970-01-01 00:00:00
1   1970-01-01 00:00:01
2   1970-01-01 00:00:02
3   1970-01-01 00:00:03
4   1970-01-01 00:00:04
5   1970-01-01 00:00:05
6   1970-01-01 00:00:06
7   1970-01-01 00:00:07
8   1970-01-01 00:00:08
9   1970-01-01 00:00:09
dtype: datetime64[ns]

In [51]: pd.to_datetime(s,unit='ms')
Out[51]: 
0          1970-01-01 00:00:00
1   1970-01-01 00:00:00.001000
2   1970-01-01 00:00:00.002000
3   1970-01-01 00:00:00.003000
4   1970-01-01 00:00:00.004000
5   1970-01-01 00:00:00.005000
6   1970-01-01 00:00:00.006000
7   1970-01-01 00:00:00.007000
8   1970-01-01 00:00:00.008000
9   1970-01-01 00:00:00.009000
dtype: datetime64[ns]

In [52]: pd.to_datetime(s,unit='D')
Out[52]: 
0   1970-01-01
1   1970-01-02
2   1970-01-03
3   1970-01-04
4   1970-01-05
5   1970-01-06
6   1970-01-07
7   1970-01-08
8   1970-01-09
9   1970-01-10
dtype: datetime64[ns]

创建系列非常简单

In [54]: Series(s.values,index=pd.to_datetime(s,unit='s'))
Out[54]: 
1970-01-01 00:00:00    0
1970-01-01 00:00:01    1
1970-01-01 00:00:02    2
1970-01-01 00:00:03    3
1970-01-01 00:00:04    4
1970-01-01 00:00:05    5
1970-01-01 00:00:06    6
1970-01-01 00:00:07    7
1970-01-01 00:00:08    8
1970-01-01 00:00:09    9
dtype: int64

Answer 2

In [63]: s = pd.Series(range(10))

In [64]: s.index = pd.DatetimeIndex(s.index.asi8*10**9, tz='utc')

In [65]: s
Out[65]: 
1970-01-01 00:00:00+00:00    0
1970-01-01 00:00:01+00:00    1
1970-01-01 00:00:02+00:00    2
1970-01-01 00:00:03+00:00    3
1970-01-01 00:00:04+00:00    4
1970-01-01 00:00:05+00:00    5
1970-01-01 00:00:06+00:00    6
1970-01-01 00:00:07+00:00    7
1970-01-01 00:00:08+00:00    8
1970-01-01 00:00:09+00:00    9
dtype: int64

将时间戳转换为pandas.Series中的datetime.datetime

2 个答案: