pandas 大熊猫，适用于数据框行条目的 args
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pandas, apply with args which are dataframe row entries
提问by Runner Bean
I have a pandas dataframe 'df' with two columns 'A' and 'B', I have a function with two arguments
我有一个带有两列“A”和“B”的Pandas数据框“df”，我有一个带有两个参数的函数
def myfunction(B, A):
# do something here to get the result
return result
and I would like to apply it row-by-row to df using the 'apply' function
我想使用“应用”函数将它逐行应用于 df
df['C'] = df['B'].apply(myfunction, args=(df['A'],))
but I get the error
但我得到了错误
ValueError: The truth value of a Series is ambiguous. Use a.empty, a.bool(), a.item(), a.any() or a.all().
whats happening here, it seems it takes df['A'] as the whole series! not just the row entry from that series as required.
这里发生了什么，似乎整个系列都需要 df['A'] ！不仅仅是该系列中所需的行条目。
回答by jezrael
I think you need:
我认为你需要：
import pandas as pd
df = pd.DataFrame({'A':[1,2,3],
'B':[4,5,6]})
print (df)
A B
0 1 4
1 2 5
2 3 6
def myfunction(B, A):
#some staff
result = B + A
# do something here to get the result
return result
df['C'] = df.apply(lambda x: myfunction(x.B, x.A), axis=1)
print (df)
A B C
0 1 4 5
1 2 5 7
2 3 6 9
Or:
或者：
def myfunction(x):
result = x.B + x.A
# do something here to get the result
return result
df['C'] = df.apply(myfunction, axis=1)
print (df)
A B C
0 1 4 5
1 2 5 7
2 3 6 9
