我有一个pandas.DataFrame df1索引与pandas.DateRange对象索引.
如果我有一个d1和d2,作为日期时间,为什么不起作用df[d1:d2],我怎么能获得这片?
这有效:
In [25]: df.ix[d1:d2]
Out[25]:
A B C D
2000-01-10 1.149815 0.686696 -1.230991 -1.610557
2000-01-11 -1.296118 -0.172950 -0.603887 0.383690
2000-01-12 -1.034574 -0.523238 0.626968 0.471755
2000-01-13 -0.193280 1.857499 -0.046383 0.849935
2000-01-14 -1.043492 -0.820525 0.868685 -0.773050
2000-01-17 -1.622019 -0.363992 1.207590 0.577290
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比照 http://pandas.pydata.org/pandas-docs/stable/indexing.html#advanced-indexing-with-labels
第一原则df[d1:d2]应该像系列一样工作:
In [27]: df['A'][d1:d2]
Out[27]:
2000-01-10 1.149815
2000-01-11 -1.296118
2000-01-12 -1.034574
2000-01-13 -0.193280
2000-01-14 -1.043492
2000-01-17 -1.622019
Name: A
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在此处创建问题:https://github.com/pydata/pandas/issues/946
尝试truncate方法:
df.truncate(before=d1, after=d2)
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它不会修改您的原件df,并将返回截断的原件.
来自docs:
Function truncate a sorted DataFrame / Series before and/or after
some particular dates.
Parameters
----------
before : date
Truncate before date
after : date
Truncate after date
Returns
-------
truncated : type of caller
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