2012-03-20 25 views

回答

9

這工作:

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 

比照http://pandas.pydata.org/pandas-docs/stable/indexing.html#advanced-indexing-with-labels

第一原理df[d1:d2]應該工作,因爲它確實爲系列:

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 

這裏創建一個問題:https://github.com/pydata/pandas/issues/946

7

嘗試truncate方法:

df.truncate(before=d1, after=d2) 

它不會改變你原來的df並返回截斷的一個。

從文檔:

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 
+0

您可以鏈接到一個源出於此?我在http://pandas.pydata.org/pandas-docs/stable/timeseries.html#daterange-is-a-valid-index,我還沒有找到截斷函數。 – Paragon 2012-03-20 14:17:04

+0

它的工作原理,謝謝。有沒有理由更方便的'df [d1:d2]'不起作用? – saroele 2012-03-20 20:15:41

+0

@Paragon:這裏是當前文檔(v0.7.2)中truncate描述的鏈接:http://pandas.pydata.org/pandas-docs/stable/generated/pandas.DataFrame.truncate.html?highlight=截斷#pandas.DataFrame.truncate – saroele 2012-03-20 20:17:37