如何使用多索引移动 Pandas DataFrame？
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How do you shift Pandas DataFrame with a multiindex?
提问by TravisVOX
With the following DataFrame, how can I shift the "beyer" column based on the index without having Pandas assign the shifted value to a different index value?
使用以下 DataFrame，如何在不让 Pandas 将移位值分配给不同索引值的情况下根据索引移动“beyer”列？
line_date line_race beyer
horse
Last Gunfighter 2013-09-28 10 99
Last Gunfighter 2013-08-18 10 102
Last Gunfighter 2013-07-06 8 103
.....
Paynter 2013-09-28 10 103
Paynter 2013-08-31 10 88
Paynter 2013-07-27 8 100
df['beyer'].shift(1)produces...
df['beyer'].shift(1)产生...
line_date line_race beyer beyer_shifted
horse
Last Gunfighter 2013-09-28 10 99 NaN
Last Gunfighter 2013-08-18 10 102 99
Last Gunfighter 2013-07-06 8 103 102
.....
Paynter 2013-09-28 10 103 71
Paynter 2013-08-31 10 88 103
Paynter 2013-07-27 8 100 88
The problem is that Paynter was given a beyer that Last Gunfighter (his first record) was assigned. Instead I want it to go like this...
问题是佩恩特获得了最后的枪手（他的第一个记录）被分配的拜尔。相反，我希望它像这样......
line_date line_race beyer beyer_shifted
horse
Last Gunfighter 2013-09-28 10 99 NaN
Last Gunfighter 2013-08-18 10 102 99
Last Gunfighter 2013-07-06 8 103 102
.....
Paynter 2013-09-28 10 103 NaN
Paynter 2013-08-31 10 88 103
Paynter 2013-07-27 8 100 88
回答by unutbu
Use groupby/shiftto apply the shift to each group individually: (Thanks to Jeff for pointing out this simplification.)
使用groupby/shift应用转移到各组分别：（感谢Jeff指出这个简化）
In [60]: df['beyer_shifted'] = df.groupby(level=0)['beyer'].shift(1); df
Out[61]:
line_date line_race beyer beyer_shifted
Last Gunfighter 2013-09-28 10 99 NaN
Last Gunfighter 2013-08-18 10 102 99
Last Gunfighter 2013-07-06 8 103 102
Paynter 2013-09-28 10 103 NaN
Paynter 2013-08-31 10 88 103
Paynter 2013-07-27 8 100 88
If you have a multiindex, you can group by more than one level by passing a sequence of intsor level names to groupby'slevelparameter.
如果您有一个多索引，您可以通过将一系列ints或级别名称传递给groupby'slevel参数来按多个级别进行分组。
