Python Pandas：将多列汇总为一列，没有最后一列
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Pandas: sum up multiple columns into one column without last column
提问by Tuutsrednas
If I have a dataframe similar to this one
如果我有一个类似于这个的数据框
Apples Bananas Grapes Kiwis
2 3 nan 1
1 3 7 nan
nan nan 2 3
I would like to add a column like this
我想添加一个这样的列
Apples Bananas Grapes Kiwis Fruit Total
2 3 nan 1 6
1 3 7 nan 11
nan nan 2 3 5
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].sumcould 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?
我想你可以使用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完成。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？
回答by jezrael
回答by Francisco Dura
Using df['Fruit Total']= df.iloc[:, -4:-1].sum(axis=1)over your original df won't add the last column ('Kiwis'), you should use df.iloc[:, -4:]instead to select all columns:
使用df['Fruit Total']= df.iloc[:, -4:-1].sum(axis=1)原始 df 不会添加最后一列（'Kiwis'），您应该使用它df.iloc[:, -4:]来选择所有列：
print(df)
Apples Bananas Grapes Kiwis
0 2.0 3.0 NaN 1.0
1 1.0 3.0 7.0 NaN
2 NaN NaN 2.0 3.0
df['Fruit Total']=df.iloc[:,-4:].sum(axis=1)
print(df)
Apples Bananas Grapes Kiwis Fruit Total
0 2.0 3.0 NaN 1.0 6.0
1 1.0 3.0 7.0 NaN 11.0
2 NaN NaN 2.0 3.0 5.0
回答by Ramon
It is possible to do it without knowing the number of columns and even without iloc:
可以在不知道列数甚至没有 iloc 的情况下执行此操作：
print(df)
Apples Bananas Grapes Kiwis
0 2.0 3.0 NaN 1.0
1 1.0 3.0 7.0 NaN
2 NaN NaN 2.0 3.0
cols_to_sum = df.columns[ : df.shape[1]-1]
df['Fruit Total'] = df[cols_to_sum].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
