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In [5]: df = pd.DataFrame({'a':[1,2,np.nan], 'b':[np.nan,1,np.nan]})
In [6]: df.isna().sum()
Out[6]:
a 1
b 2
dtype: int64
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null_cols = df.columns[df.isnull().all()]
df.drop(null_cols, axis = 1, inplace = True)
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cols_with_missing = [col for col in X_train.columns
if X_train[col].isnull().any()]
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cols_to_delete = df.columns[df.isnull().sum()/len(df) > .90]
df.drop(cols_to_delete, axis = 1, inplace = True)