Python Pandas 为所选列的行列最大值添加列
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Python Pandas add column for row-wise max value of selected columns
提问by user2333196
data = {'name' : ['bill', 'joe', 'steve'],
'test1' : [85, 75, 85],
'test2' : [35, 45, 83],
'test3' : [51, 61, 45]}
frame = pd.DataFrame(data)
I would like to add a new column that shows the max value for each row.
我想添加一个新列，显示每行的最大值。
desired output:
所需的输出：
name test1 test2 test3 HighScore
bill 75 75 85 85
joe 35 45 83 83
steve 51 61 45 61
Sometimes
有时
frame['HighScore'] = max(data['test1'], data['test2'], data['test3'])
works but most of the time gives this error:
有效，但大多数情况下会出现此错误：
ValueError: The truth value of an array with more than one element is ambiguous. Use a.any() or a.all()
ValueError：包含多个元素的数组的真值不明确。使用 a.any() 或 a.all()
Why does it only work sometimes? Is there another way of doing it?
为什么它只是有时有效？还有另一种方法吗？
采纳答案by Roman Pekar
>>> frame['HighScore'] = frame[['test1','test2','test3']].max(axis=1)
>>> frame
name test1 test2 test3 HighScore
0 bill 85 35 51 85
1 joe 75 45 61 75
2 steve 85 83 45 85
回答by alko
>>> frame['HighScore'] = frame[['test1','test2','test3']].apply(max, axis=1)
>>> frame
name test1 test2 test3 HighScore
0 bill 85 35 51 85
1 joe 75 45 61 75
2 steve 85 83 45 85
回答by Vikas goel
if a maxor minvalue between multiple columns in a dfis to be determined then use:
如果要确定a 中多列之间的amax或min值，df则使用：
df['Z']=df[['A','B','C']].apply(np.max,axis=1)
