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You can extract rows/columns containing missing values from pandas. DataFrame by using the isnull() or isna() method that checks if an element is a missing value.
In order to check null values in Pandas DataFrame, we use isnull() function this function return dataframe of Boolean values which are True for NaN values.
You can use any axis=1 to check for least one True per row, then filter with boolean indexing:
null_data = df[df.isnull().any(axis=1)]
df.isnull().any(axis = 1).sum()
this gives you the total number of rows with at least one missing data
If you want to see only the rows that contains the NaN values you could do:
data_frame[data_frame.iloc[:, insert column number here]=='NaN']
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