python - Pandas 两列之和 - 正确处理纳米值

Question

当对两个 pandas 列求和时，当两列之一是 float 时，我想忽略纳米值。但是，当 nan 出现在两列中时，我想将 nan 保留在输出中(而不是 0.0)。

初始数据框:

Surf1     Surf2
0         0
NaN       8
8         15
NaN       NaN
16        14
15        7

所需输出:

Surf1     Surf2     Sum
0         0         0
NaN       8         8
8         15        23
NaN       NaN       NaN
16        14        30
15        7         22

尝试过的代码:-> 下面的代码忽略 nan 值，但是当取两个 nan 值之和时，它在输出中给出 0.0，在这种特殊情况下我想将其保留为 NaN，以将这些空值与实际为 0 的值分开求和后。

import pandas as pd
import numpy as np

data = pd.DataFrame({"Surf1": [10,np.nan,8,np.nan,16,15], "Surf2": [22,8,15,np.nan,14,7]})
print(data)

data.loc[:,'Sum'] = data.loc[:,['Surf1','Surf2']].sum(axis=1)
print(data)

Answer 1

来自documentation pandas.DataFrame.sum

By default, the sum of an empty or all-NA Series is 0.

>>> pd.Series([]).sum() # min_count=0 is the default 0.0

This can be controlled with the min_count parameter. For example, if you’d like the sum of an empty series to be NaN, pass min_count=1.

将代码更改为

data.loc[:,'Sum'] = data.loc[:,['Surf1','Surf2']].sum(axis=1, min_count=1)

输出

   Surf1  Surf2
0   10.0   22.0
1    NaN    8.0
2    8.0   15.0
3    NaN    NaN
4   16.0   14.0
5   15.0    7.0
   Surf1  Surf2   Sum
0   10.0   22.0  32.0
1    NaN    8.0   8.0
2    8.0   15.0  23.0
3    NaN    NaN   NaN
4   16.0   14.0  30.0
5   15.0    7.0  22.0