How does one create a pandas column (binary) based on whether or not another column contains dates

I am analyzing customer churn. My dataset contains years of customers that have stayed or left. I need to create a [‘CHURN_FLAG’] column based on whether or not there is a date in the [‘CHURN_DATE’] column. If there is a date in the [‘CHURN_DATE’] column then the customer churned.

Current data frame:

Desired:

I created a column [‘TODAY_DATE’] and have attempted to solve by assessing if the [‘CHURNdate’] < [‘TODAY_DATE’] then the binary 1 would populate, else 0. Here is the code:

df2['CHURNflag'] = np.where(df2['CHURNdate']<df2['TODAY_DATE'], 0, 1)

Naturally, it didn’t work. 🙁 The datatypes are datetime64

>Solution :

churn['CHURNflag'] = np.where(churn['CHURNdate'].isna(), 0, 1)

Out[24]: 
    CHURNdate  CHURNflag
0  2023-01-01          1
1         NaN          0