数据框中每行最大值的列名

Question

我有一个数据框，我想要一列填充每行的最大值，所以我使用了这个：

 df_1['Highest_Rew_patch'] = df_1.max(axis=1)

输出：

    Patch_0  Patch_1  Patch_2  ...  Patch_7  exp_patch  Highest_Rew_patch
0      0.0     70.0     70.0  ...      0.0          3               70.0
1      0.0     74.0     74.0  ...      0.0          4               74.0
2      0.0     78.0     78.0  ...      0.0          4               78.0
3      0.0     82.0     82.0  ...      0.0          4               82.0
4      0.0     82.0     82.0  ...      0.0          5               82.0
5      0.0     86.0     86.0  ...      0.0          6               86.0
6      0.0     90.0     90.0  ...      0.0          6               90.0
7      0.0     94.0     94.0  ...      0.0          6               94.0
8      0.0     98.0     98.0  ...      0.0          6               98.0
9      0.0     98.0     98.0  ...      0.0          7               98.0

但是我想要一些不同的结果：

Patch_0  Patch_1  Patch_2   Patch_7  exp_patch  Highest_Rew_patch
0        0.0      70.0      70.0       3            Patch_2,Patch_7...
1        0.0      74.0      74.0       4            Patch_2,Patch_7...

因此，我想要的不是行的最高值，而是具有最高值的特定行的该列的 header。

Answer 1

试试这个：

df['Highest_Rew_patch']=df.filter(like='Patch').apply(lambda x: ', '.join(x[x.eq(x.max())].index), axis=1)

apply在axis=1上，然后在, 上加入x的所有索引等于最大值。

输出：

   Patch_0  Patch_1  ...  exp_patch                   Highest_Rew_patch
0      0.0     70.0  ...          3  Patch_1, Patch_2, Patch_4, Patch_6
1      0.0     74.0  ...          4           Patch_1, Patch_2, Patch_6
2      0.0     78.0  ...          4           Patch_1, Patch_2, Patch_6
3      0.0     82.0  ...          4           Patch_1, Patch_2, Patch_6
4      0.0     82.0  ...          5           Patch_1, Patch_2, Patch_6

Answer 2

您可以 select 以 Patch 开头的列，然后只保留值等于最大值的列名称：

>> s = df.iloc[:, df.columns.str.startswith('Patch')].apply(
   lambda s: s.index[s.eq(s.max())].tolist(), axis=1)

>> s 

0    [Patch_1, Patch_2]
1    [Patch_1, Patch_2]
2    [Patch_1, Patch_2]
3    [Patch_1, Patch_2]
4    [Patch_1, Patch_2]
5    [Patch_1, Patch_2]
6    [Patch_1, Patch_2]
7    [Patch_1, Patch_2]
8    [Patch_1, Patch_2]
9    [Patch_1, Patch_2]

或作为字符串加入：

>> s = s.apply(lambda s: ','.join(s))

>> s
0    Patch_1,Patch_2
1    Patch_1,Patch_2
2    Patch_1,Patch_2
3    Patch_1,Patch_2
4    Patch_1,Patch_2
5    Patch_1,Patch_2
6    Patch_1,Patch_2
7    Patch_1,Patch_2
8    Patch_1,Patch_2
9    Patch_1,Patch_2
dtype: object

然后只需分配新列：

df['Highest_Rew_patch'] = s

数据框中每行最大值的列名

Column name of maximum of each row in a dataframe

python

python-3.x

pandas

dataframe

max