按另一个索引的顺序对 Pandas Dataframe 进行排序
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Sorting Pandas Dataframe by order of another index
提问by AJG519
Say I have two dataframes, df1 and df2 that share the same index. df1 is sorted in the order that I want df2 to be sorted.
假设我有两个数据帧，df1 和 df2，它们共享相同的索引。df1 按照我希望 df2 排序的顺序进行排序。
df=pd.DataFrame(index=['Arizona','New Mexico', 'Colorado'],columns=['A','B','C'], data=[[1,2,3],[4,5,6],[7,8,9]])
print df
A B C
Arizona 1 2 3
New Mexico 4 5 6
Colorado 7 8 9
df2=pd.DataFrame(index=['Arizona','Colorado', 'New Mexico'], columns=['D'], data=['Orange','Blue','Green'])
print df2
D
Arizona Orange
Colorado Blue
New Mexico Green
What is the best / most efficient way of sorting the second dataframe by the index of the first?
按第一个数据帧的索引对第二个数据帧进行排序的最佳/最有效方法是什么？
One option is just joining them, sorting, and then dropping the columns:
一种选择是加入它们，排序，然后删除列：
df.join(df2)[['D']]
D
Arizona Orange
New Mexico Green
Colorado Blue
Is there a more elegant way of doing this?
有没有更优雅的方法来做到这一点？
Thanks!
谢谢！
回答by chrisb
reindexwould work - be aware that it will create missing values for index values that are df, not in df2.
reindex会起作用 - 请注意，它会为 df 而不是 df2 的索引值创建缺失值。
In [18]: df2.reindex(df.index)
Out[18]:
D
Arizona Orange
New Mexico Green
Colorado Blue
