即使inplace=Tru，pandas replace也不会替换value

Question

我的数据是这样的。如果'no_of_children'不是nan，我想用'Married'替换婚姻状况'Missing'。你知道吗

>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

这就是我所尝试的：

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

但这没什么用。你知道吗

Answer 1

为避免chained assignments分配回代值：

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