如何在计算中直接使用Pandas日期时间索引? [英] How to directly use Pandas Date-time index in calculations?

问题描述

我有以下有效的代码:

table['CALC_DOM']=table.index
table['CALC_DOM']=table['END_DATE']-['CALC_DOM']

没有更好的方法可以直接从table.index转换吗?像:

Shouldn't there be a better way to directly convert from table.index? like:

table['CALC_DOM']=table.index
table['CALC_DOM']=table['END_DATE']-(table.index()) 

我尝试使用
table.index.get_values
和
table.index.date

I have tried using
table.index.get_values
and
table.index.date

...但是我得到的是:
TypeError: incompatible type [object] for a datetime/timedelta operation.

...but all I get is:
TypeError: incompatible type [object] for a datetime/timedelta operation.

推荐答案

非常接近！

In [1]: df = DataFrame(randn(5,2),index=date_range('20130101',periods=5))

In [3]: df['date'] = Timestamp('20130102')

In [4]: df
Out[4]: 
                   0         1                date
2013-01-01  2.406932 -0.313473 2013-01-02 00:00:00
2013-01-02  0.034162 -0.708450 2013-01-02 00:00:00
2013-01-03 -1.585031  0.587243 2013-01-02 00:00:00
2013-01-04  1.454818  1.089208 2013-01-02 00:00:00
2013-01-05 -0.778016 -0.994242 2013-01-02 00:00:00

In [5]: df['td'] = df['date']-df.index.to_series()

In [6]: df
Out[6]: 
                   0         1                date                td
2013-01-01  2.406932 -0.313473 2013-01-02 00:00:00  1 days, 00:00:00
2013-01-02  0.034162 -0.708450 2013-01-02 00:00:00          00:00:00
2013-01-03 -1.585031  0.587243 2013-01-02 00:00:00 -1 days, 00:00:00
2013-01-04  1.454818  1.089208 2013-01-02 00:00:00 -2 days, 00:00:00
2013-01-05 -0.778016 -0.994242 2013-01-02 00:00:00 -3 days, 00:00:00

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