Pandas has both isna() and isnull(). I usually use isnull() to detect missing values and have never met the case so that I had to use
They both are same. As a best practice, always prefer to use isna() over isnull().
It is easy to remember what isna() is doing because when you look at numpy method np.isnan(), it checks NaN values. In pandas there are other similar method names like dropna(), fillna() that handles missing values and it always helps to remember easily.