Python Pandas：将行转换为列标题
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Python Pandas: Convert Rows as Column headers
提问by richie
I have the following dataframe:
我有以下数据框：
Year Country medal no of medals
1896 Afghanistan Gold 5
1896 Afghanistan Silver 4
1896 Afghanistan Bronze 3
1896 Algeria Gold 1
1896 Algeria Silver 2
1896 Algeria Bronze 3
I want it this way.
我想要这样。
Year Country Gold Silver Bronze
1896 Afghanistan 5 4 3
1896 Algeria 1 2 3
Stack/Unstack dont seem to work.
Stack/Unstack 似乎不起作用。
采纳答案by Andy Hayden
You're looking for pivot_table:
您正在寻找pivot_table：
In [11]: medals = df.pivot_table('no of medals', ['Year', 'Country'], 'medal')
In [12]: medals
Out[12]:
medal Bronze Gold Silver
Year Country
1896 Afghanistan 3 5 4
Algeria 3 1 2
and if you want to reorder the columns:
如果您想对列重新排序：
In [12]: medals.reindex_axis(['Gold', 'Silver', 'Bronze'], axis=1)
Out[12]:
medal Gold Silver Bronze
Year Country
1896 Afghanistan 5 4 3
Algeria 1 2 3
回答by Manu Sharma
Stack/ Unstack won't work until you have the desired column in your row/ column indexes. e.g. In simple words, Stack/ Unstack will bring the lowest level of column index to the lowest level of row index and vice versa.
在行/列索引中有所需的列之前，堆栈/取消堆栈将不起作用。例如，简单来说，Stack/Unstack 会将最低级别的列索引带到最低级别的行索引，反之亦然。
So in your case, you can achieve the same results with stack/unstack by
因此，在您的情况下，您可以通过 stack/unstack 获得相同的结果
