PYTHON

pandas count nan in each row

df.isna().sum(axis=1)

count rows with nan pandas

 np.count_nonzero(df.isnull().values)   
 np.count_nonzero(df.isnull())           # also works  

Count NaN values of an DataFrame

df.isna().sum().sum()

pandas count nans in column

import pandas as pd
## df1 as an example data frame 
## col1 name of column for which you want to calculate the nan values
sum(pd.isnull(df1['col1']))

pandas include nan in value_counts

df.groupby(['No', 'Name'], dropna=False, as_index=False).size()

pandas include nan in value_counts

df.groupby(['No', 'Name'], dropna=False, as_index=False).size()

pandas include nan in value_counts

df.groupby(['No', 'Name'], dropna=False, as_index=False).size()

pandas include nan in value_counts

df.groupby(['No', 'Name'], dropna=False, as_index=False).size()