PYTHON

dataframe find nan rows

df[df.isnull().any(axis=1)]

count nan pandas

#Python, pandas
#Count missing values for each column of the dataframe df

df.isnull().sum()

pandas count nan in each row

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

select rows with nan pandas

df[df['Col2'].isnull()]

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()

how to find total no of nan values in pandas

# will give count of nan values of every column.
df.isna().sum()

value_counts with nan

df['column_name'].value_counts(dropna=False)

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()