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問題描述
如果我有一個(gè)類似于這個(gè)的數(shù)據(jù)框
If I have a dataframe similar to this one
Apples Bananas Grapes Kiwis
2 3 nan 1
1 3 7 nan
nan nan 2 3
我想添加這樣的列
Apples Bananas Grapes Kiwis Fruit Total
2 3 nan 1 6
1 3 7 nan 11
nan nan 2 3 5
我猜你可以使用 df['Apples'] + df['Bananas'] 等等，但我的實(shí)際數(shù)據(jù)框比這大得多.我希望像 df['Fruit Total']=df[-4:-1].sum 這樣的公式可以在一行代碼中解決問題.然而這并沒有奏效.有沒有辦法在不明確總結(jié)所有列的情況下做到這一點(diǎn)?
I guess you could use df['Apples'] + df['Bananas'] and so on, but my actual dataframe is much larger than this. I was hoping a formula like df['Fruit Total']=df[-4:-1].sum could do the trick in one line of code. That didn't work however. Is there any way to do it without explicitly summing up all columns?
推薦答案
可以先通過 iloc 然后是 sum:
You can first select by iloc and then sum:
df['Fruit Total']= df.iloc[:, -4:-1].sum(axis=1)
print (df)
Apples Bananas Grapes Kiwis Fruit Total
0 2.0 3.0 NaN 1.0 5.0
1 1.0 3.0 7.0 NaN 11.0
2 NaN NaN 2.0 3.0 2.0
所有列的總和使用:
df['Fruit Total']= df.sum(axis=1)
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