Python3.x 每个数据行中每个数据帧值的总和

我有一个数据帧:

import pandas as pd

d = {
'Country': ["Austria", "Austria", "Belgium", "USA", "USA", "USA", "USA"], 
'Number2020': [15, None, 18, 20, 22, None,  30],
'Number2021': [20, 25, 18, None, None, None, 32],    
}

df = pd.DataFrame(data=d)
df

    Country   Number2020    Number2021
0   Austria   15.0          20.0
1   Austria   NaN           25.0
2   Belgium   18.0          18.0
3   USA       20.0          NaN
4   USA       22.0          NaN
5   USA       NaN           NaN
6   USA       30.0          32.0

我想总结每个国家的nan值.例如.

    Country       Count_nans
    Austria       1
    
    USA           4

我已经过滤了数据帧，只留下带有NaN的行.

df_nan = df[df.Number2021.isna() | df.Number2020.isna()]

    Country   Number2020    Number2021
1   Austria   NaN           25.0
3   USA       20.0          NaN
4   USA       22.0          NaN
5   USA       NaN           NaN

看起来像是一个分组操作？我试过这个.

nasum2021 = df_nan['Number2021'].isna().sum()

df_nan['countNames2021'] = df_nan.groupby(['Number2021'])['Number2021'].transform('count').fillna(nasum2021)
df_nan

它给了我1个nan代表奥地利，但给了3个代表美国，而它应该是4.所以这是不对的.