python - 即使使用 inplace=True，pandas replace 也不会替换值

Question

我的数据是这样的。如果 'no_of_children' 不是 nan，我想用 'Married' 替换 marital_status 'Missing'。

>cust_data_df[['marital_status','no_of_children']]
>

    marital_status  no_of_children

0   Married           NaN
1   Married           NaN
2   Missing            1
3   Missing            2
4   Single            NaN
5   Single            NaN
6   Married           NaN
7   Single            NaN
8   Married           NaN
9   Married           NaN
10  Single            NaN

这是我尝试过的:

cust_data_df.loc[cust_data_df['no_of_children'].notna()==True, 'marital_status'].replace({'Missing':'Married'},inplace=True)

但这并没有做任何事情。

Answer 1

为避免 chained assignments 分配回替换值:

m = cust_data_df['no_of_children'].notna()
d = {'Missing':'Married'}
cust_data_df.loc[m, 'marital_status'] = cust_data_df.loc[m, 'marital_status'].replace(d)

如果需要设置所有值:

cust_data_df.loc[m, 'marital_status'] = 'Married'

编辑:

感谢@Quickbeam2k1 的解释:

cust_data_df.loc[cust_data_df['no_of_children'].notna()==True, 'marital_status'] is just a new object which has no reference. Replacing there, will leave the original object unchanged