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问题描述
如果我有一个类似于这个的数据框
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
我想添加这样的列
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，但我的实际数据框比这大得多.我希望像 df['Fruit Total']=df[-4:-1].sum 这样的公式可以在一行代码中解决问题.然而这并没有奏效.有没有办法在不明确总结所有列的情况下做到这一点?
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?
推荐答案
可以先通过 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
所有列的总和使用:
df['Fruit Total']= df.sum(axis=1)
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