Python 查找每行具有最大值的列名
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Find the column name which has the maximum value for each row
提问by markov zain
I have a DataFrame like this one:
我有一个像这样的 DataFrame：
In [7]:
frame.head()
Out[7]:
Communications and Search Business General Lifestyle
0 0.745763 0.050847 0.118644 0.084746
0 0.333333 0.000000 0.583333 0.083333
0 0.617021 0.042553 0.297872 0.042553
0 0.435897 0.000000 0.410256 0.153846
0 0.358974 0.076923 0.410256 0.153846
In here, I want to ask how to get column name which has maximum value for each row, the desired output is like this:
在这里，我想问一下如何获取每行具有最大值的列名，所需的输出是这样的：
In [7]:
frame.head()
Out[7]:
Communications and Search Business General Lifestyle Max
0 0.745763 0.050847 0.118644 0.084746 Communications
0 0.333333 0.000000 0.583333 0.083333 Business
0 0.617021 0.042553 0.297872 0.042553 Communications
0 0.435897 0.000000 0.410256 0.153846 Communications
0 0.358974 0.076923 0.410256 0.153846 Business
采纳答案by Alex Riley
You can use idxmaxwith axis=1to find the column with the greatest value on each row:
您可以使用idxmaxwithaxis=1查找每行中具有最大值的列：
>>> df.idxmax(axis=1)
0 Communications
1 Business
2 Communications
3 Communications
4 Business
dtype: object
To create the new column 'Max', use df['Max'] = df.idxmax(axis=1).
要创建新列“Max”，请使用df['Max'] = df.idxmax(axis=1).
To find the rowindex at which the maximum value occurs in each column, use df.idxmax()(or equivalently df.idxmax(axis=0)).
要查找每列中出现最大值的行索引，请使用df.idxmax()（或等效地df.idxmax(axis=0)）。
回答by Zero
You could applyon dataframe and get argmax()of each row via axis=1
您可以apply在数据帧上argmax()通过axis=1
In [144]: df.apply(lambda x: x.argmax(), axis=1)
Out[144]:
0 Communications
1 Business
2 Communications
3 Communications
4 Business
dtype: object
Here's a benchmark to compare how slow applymethod is to idxmax()for len(df) ~ 20K
这里有一个基准来比较慢apply的方法是idxmax()为len(df) ~ 20K
In [146]: %timeit df.apply(lambda x: x.argmax(), axis=1)
1 loops, best of 3: 479 ms per loop
In [147]: %timeit df.idxmax(axis=1)
10 loops, best of 3: 47.3 ms per loop
回答by user1718097
And if you want to produce a column containing the name of the column with the maximum value but considering only a subset of columns then you use a variation of @ajcr's answer:
如果您想生成一个包含具有最大值的列的名称但只考虑列的子集的列，那么您可以使用@ajcr 答案的变体：
df['Max'] = df[['Communications','Business']].idxmax(axis=1)
