How to remove columns with too many missing values in Python
The fastest way to find the sum of NaN or the percentage by columns is:

for the sum: df.isna().sum()
for the percentage: df.isna().mean()
I'm working on a machine learning problem in which there are many missing values in the features. There are 100's of features and I would like to remove those features that have too many missing values (it can be features with more than 80% missing values). How can I do that in Python?
My data is a Pandas dataframe.