根据列表对 pandas 数据框进行排序 [英] sort pandas dataframe based on list

问题描述

我想对以下数据框进行排序:

I would like to sort the following dataframe:

Region           LSE          North      South
0                   Cn     33.330367   9.178917
1               Develd     -36.157025 -27.669988
2               Wetnds    -38.480206 -46.089908
3                Oands    -47.986764 -32.324991
4               Otherg    323.209834  28.486310
5                 Soys      34.936147   4.072872
6                  Wht     0.983977 -14.972555

我想对它进行排序，以便根据列表对LSE列进行重新排序:

I would like to sort it so the LSE column is reordered based on the list:

lst = ['Oands','Wetnds','Develd','Cn','Soys','Otherg','Wht']

当然，其他列也将需要相应地重新排序.熊猫有什么办法吗?

of, course the other columns will need to be reordered accordingly as well. Is there any way to do this in pandas?

推荐答案

pandas 0.15版中对Categorical的改进支持使您可以轻松地做到这一点:

The improved support for Categoricals in pandas version 0.15 allows you to do this easily:

df['LSE_cat'] = pd.Categorical(
    df['LSE'], 
    categories=['Oands','Wetnds','Develd','Cn','Soys','Otherg','Wht'], 
    ordered=True
)
df.sort('LSE_cat')
Out[5]: 
   Region     LSE       North      South LSE_cat
3       3   Oands  -47.986764 -32.324991   Oands
2       2  Wetnds  -38.480206 -46.089908  Wetnds
1       1  Develd  -36.157025 -27.669988  Develd
0       0      Cn   33.330367   9.178917      Cn
5       5    Soys   34.936147   4.072872    Soys
4       4  Otherg  323.209834  28.486310  Otherg
6       6     Wht    0.983977 -14.972555     Wht

如果这只是临时排序，则将LSE列保留为 Categorical可能不是您想要的，但是如果此顺序是 您希望能够利用几次的东西 在不同的情况下，Categoricals是一个很好的解决方案.

If this is only a temporary ordering then keeping the LSE column as a Categorical may not be what you want, but if this ordering is something that you want to be able to make use of a few times in different contexts, Categoricals are a great solution.

在pandas的更高版本中，sort已被sort_values替换，因此您需要:

In later versions of pandas, sort, has been replaced with sort_values, so you would need instead:

df.sort_values('LSE_cat')

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