[英]Slice a Time Series
Let's say I have a time series "TS" with the range of months. 假设我有一个月份范围的时间序列“TS”。 How can I get a sub-time series from TS with for example the range of one day. 如何从TS获取子时间序列,例如一天的范围。
I tried this code : 我试过这段代码:
subts = pd.Series(TS,index=pd.to_datetime(['2015-09-26','2015-09-27']))
But I get this error : 但我得到这个错误:
ValueError: Wrong number of items passed 472, placement implies 2
What I understood is, the method I chose matches every value from TS (472rows) an the time range I gave in the constructor (ie : ['2015-09-26','2015-09-27']) 我所理解的是,我选择的方法匹配TS(472rows)中的每个值和我在构造函数中给出的时间范围(即:['2015-09-26','2015-09-27'])
Is there a way to really slice a time series? 有没有办法真正切片时间序列? Just extract a part of it within a given time range? 只需在给定的时间范围内提取部分内容?
I think you can use selecting by []
, see also indexing : 我认为您可以使用[]
选择,另请参阅索引 :
subts = TS['2015-09-26':'2015-09-27']
Or: 要么:
subts = TS.loc['2015-09-26':'2015-09-27']
Sample: 样品:
np.random.seed(123)
TS = pd.Series(np.random.randint(10, size=10), pd.date_range('2015-09-24', periods=10))
print (TS)
2015-09-24 2
2015-09-25 2
2015-09-26 6
2015-09-27 1
2015-09-28 3
2015-09-29 9
2015-09-30 6
2015-10-01 1
2015-10-02 0
2015-10-03 1
Freq: D, dtype: int32
subts = TS['2015-09-26':'2015-09-27']
print (subts)
2015-09-26 6
2015-09-27 1
Freq: D, dtype: int32
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