How to find which columns contain any NaN value in Pandas dataframe
features_with_na=[features for features in dataframe.columns if dataframe[features].isnull().sum()>0]
for feature in features_with_na:
print(feature, np.round(dataframe[feature].isnull().mean(), 4),  '% missing values')
print(features_with_na)
it  will give % of missing value for each column in dataframe
Given a pandas dataframe containing possible NaN values scattered here and there:
Question: How do I determine which columns contain NaN values? In particular, can I get a list of the column names containing NaNs?