Python

df.isna().sum()

null_cols = df.columns[df.isnull().all()]
df.drop(null_cols, axis = 1, inplace = True)

df.isna().any()

df = df[df.columns[~df.isnull().all()]]

cols_with_missing = [col for col in X_train.columns
                     if X_train[col].isnull().any()]

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