将Pandas TimeDelta转换为整数 [英] Convert Pandas TimeDelta to integer

问题描述

假设我有一个包含TimeDelta数据的熊猫系列. 实际上，它是通过将DateTimeIndex与自身的偏移版本进行比较而生成的，因此给出了连续时间戳之间的差异.

Suppose I have a Pandas Series that contains TimeDelta data. In fact it has been generated by taking the difference of a DateTimeIndex with a shifted version of itself, hence giving the delta between consecutive timestamps.

看起来像

timestamp
2015-02-01 00:00:04   00:00:04
2015-02-01 00:00:08   00:00:04
2015-02-01 00:00:12   00:00:04
....
Name: timestamp, dtype: timedelta64[ns]

这些值显然是numpy.timedelta64，但我需要将它们设置为几秒钟. 与此相关的问题也有类似的问题，但我尚未看到与Pandas 0.16.1有关的答案.

The values are obviously numpy.timedelta64 but I need to get them into seconds. There have been similar questions asked relating to this but no answers I have seen yet that deals with Pandas 0.16.1.

我尝试过的是:

ts.apply(lambda x: x.seconds)

哪个错误

AttributeError:"numpy.timedelta64"对象没有属性"seconds"

AttributeError: 'numpy.timedelta64' object has no attribute 'seconds'

然后尝试

numpy.int64(ts)

但是，这给了我一个数组.现在我知道我可以将其转换为Series了，但是在一个Pandas调用或映射函数中没有其他方法可以做到这一点吗?

But that gives me an array. Now I know I can convert that back into a Series but is there not another way to do this in one Pandas call or mapping function?

推荐答案

以下内容对我有用:

In [24]:

t="""index,timestamp
2015-02-01 00:00:04,00:00:04
2015-02-01 00:00:08,00:00:04
2015-02-01 00:00:12,00:00:04"""
s = pd.read_csv(io.StringIO(t),parse_dates=[0,1], squeeze=True, index_col=[0])
In [26]:

s.dt.second
Out[26]:
index
2015-02-01 00:00:04    4
2015-02-01 00:00:08    4
2015-02-01 00:00:12    4
dtype: int64

datetime dtype值具有 dt 访问器，您可以在其中访问seconds属性.

datetime dtype values have a dt accessor where you can access the seconds attribute.

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