如何更改pandas多索引列的顺序/分组/级别？

Question

我正在尝试对pandas数据框中的/swaplevel/pivot/something列重新排序。 列是一个多索引，但我找不到做我想做的事的佐料。

多索引中变化最快的列是month，但我希望它是变化最慢的列。

我有一个nbviewer笔记本，如果你想自己试试的话： http://nbviewer.ipython.org/gist/flamingbear/4cfac24c80fe34a67474

我所拥有的：

+-------------------------------------------------------------------+
|+-----+------+------+-----+------+-----+-----+------+-----+-----+  |
||     |weight             |extent            |rank                ||
|+-----+------+------+-----+------+-----+-----+------+-----+-----+  |
||month|'1Jan'|'Feb' |'Mar'|'1Jan'|'Feb'|'Mar'|'1Jan'|'Feb'|'Mar'|  |
|+-----+------+------+-----+------+-----+-----+------+-----+-----+  |
||year |      |      |     |      |     |     |      |     |     |  |
|+-----+------+------+-----+------+-----+-----+------+-----+-----+  |
||2000 |45.1  |46.1  |25.1 |13.442|14.94|15.02|13    |17   |14   |  |
|+-----+------+------+-----+------+-----+-----+------+-----+-----+  |
||2001 |85.0  |16.0  |49.0 |13.380|14.81|15.14|12    |15   |17   |  |
|+-----+------+------+-----+------+-----+-----+------+-----+-----+  |
||2002 |90.0  |33.0  |82.0 |13.590|15.13|14.88|15    |22   |10   |  |
|+-----+------+------+-----+------+-----+-----+------+-----+-----+  |
||2003 |47.0  |34.0  |78.0 |13.640|14.83|15.27|17    |16   |22   |  |
|+-----+------+------+-----+------+-----+-----+------+-----+-----+  |
+-------------------------------------------------------------------+

我想要什么

+------------------------------------------------------------------+
|+-----+------+------+----+------+------+-----+------+------+----+ |
||month|1Jan              |Feb                |Mar                ||
|+-----+------+------+----+------+------+-----+------+------+----+ |
||     |weight|extent|rank|weight|extent|rank |weight|extent|rank| |
|+-----+------+------+----+------+------+-----+------+------+----+ |
||year |      |      |    |      |      |     |      |      |    | |
|+-----+------+------+----+------+------+-----+------+------+----+ |
||2000 |45.1  |13.442|13  |46.1  |14.94 |17   | 25.1 |15.02 |14  | |
|+-----+------+------+----+------+------+-----+------+------+----+ |
||2001 |85.0  |13.380|12  |16.0  |14.81 |15   | 49.0 |15.14 |17  | |
|+-----+------+------+----+------+------+-----+------+------+----+ |
||2002 |90.0  |13.590|15  |33.0  |15.13 |22   | 82.0 |14.88 |10  | |
|+-----+------+------+----+------+------+-----+------+------+----+ |
||2003 |47.0  |13.640|17  |34.0  |14.83 |16   | 78.0 |15.27 |22  | |
|+-----+------+------+-----------+------+-----+------+------+----+ |
+------------------------------------------------------------------+

任何帮助都将不胜感激。我可以使用我的原始数据帧，但是用所需的顺序写入CSV将是非常棒的。

提前谢谢你， 马特

Answer 1

您的列是一个多索引。您需要使用从交换现有多索引的级别创建的新多索引重新分配数据帧的列：

df.columns = df.columns.swaplevel(0, 1)
df.sortlevel(0, axis=1, inplace=True)
>>> df

month   '1Jan'                 'Feb'                 'Mar'              
        weight  extent  rank  weight  extent  rank  weight  extent  rank
year                                                                    
2000      45.1  13.442    13    46.1   14.94    17    25.1   15.02    14
2001      85.0  13.380    12    16.0   14.81    15    49.0   15.14    17
2002      90.0  13.590    15    33.0   15.13    22    82.0   14.88    10
2003      47.0  13.640    17    34.0   14.83    16    78.0   15.27    22

然后可以导出到csv：

df.to_csv(filename)

编辑

根据下面@Silas的注释，sortlevel已被弃用。相反，请使用：

df.sort_index(axis=1, level=0, inplace=True)