来自pandas数据框的几列总和 [英] Sum of several columns from a pandas dataframe

问题描述

所以说我有下表:

In [2]: df = pd.DataFrame({'a': [1,2,3], 'b':[2,4,6], 'c':[1,1,1]})

In [3]: df
Out[3]: 
   a  b  c
0  1  2  1
1  2  4  1
2  3  6  1

我可以这样对a和b求和:

I can sum a and b that way:

In [4]: sum(df['a']) + sum(df['b'])
Out[4]: 18

但是，这对于较大的数据框不是很方便，在较大的数据框中，您必须将多个列加在一起.

However this is not very convenient for larger dataframe, where you have to sum multiple columns together.

是否有一种比较整洁的方式来汇总列(类似于下面的内容)?如果我想对整个DataFrame求和而不指定列怎么办?

Is there a neater way to sum columns (similar to the below)? What if I want to sum the entire DataFrame without specifying the columns?

In [4]: sum(df[['a', 'b']]) #that will not work!
Out[4]: 18
In [4]: sum(df) #that will not work!
Out[4]: 21

推荐答案

我认为您可以使用双精度sum-首先

I think you can use double sum - first DataFrame.sum create Series of sums and second Series.sum get sum of Series:

print (df[['a','b']].sum())
a     6
b    12
dtype: int64

print (df[['a','b']].sum().sum())
18

您还可以使用:

print (df[['a','b']].sum(axis=1))
0    3
1    6
2    9
dtype: int64

print (df[['a','b']].sum(axis=1).sum())
18

谢谢您 pirSquared 另一种解决方案-通过

Thank you pirSquared for another solution - convert df to numpy array by values and then sum:

print (df[['a','b']].values.sum())
18

---

print (df.sum().sum())
21

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