How can I modify apply and lambda function to create new column based on other in Python Pandas?

I have table like below in Python Pandas with float64 data type:

col1
--------
245.121
NaN
44.908

And I try to create new column "col2" using below code:

data["col2"] = data.apply(lambda x: 1 if x.col1== np.nan else 0, axis = 1)

Unfortunately, when I use above code I have 0 everywhere, why ? How can I modyfi my code to achieve something like below:

col1      col2
--------
245.121  | 0
NaN      | 1
44.908   | 0

How can I do that in Python Pandas ?

>Solution :

Try:

data["col2"] = data.apply(lambda x: 1 if x.col1 in [np.nan] else 0, axis = 1)

This should work, while yours doesn’t because it’s a feature that np.nan != np.nan