How to count nan values in a pandas DataFrame?

Question

What is the best way to account for (not a number) nan values in a pandas DataFrame?

The following code:

import numpy as np
import pandas as pd
dfd =         


        

Answer 1

A good clean way to count all NaN's in all columns of your dataframe would be ...

import pandas as pd 
import numpy as np


df = pd.DataFrame({'a':[1,2,np.nan], 'b':[np.nan,1,np.nan]})
print(df.isna().sum().sum())

Using a single sum, you get the count of NaN's for each column. The second sum, sums those column sums.