Update data_preproc_functions.py to solve conversion to float issue (#…

…498)

* Using pandas built in functions to optimize time.

aif360/algorithms/preprocessing/optim_preproc_helpers/data_preproc_functions.py

@@ -265,7 +265,7 @@ def group_status(x):
         df['credit_history'] = df['credit_history'].apply(lambda x: group_credit_hist(x))
         df['savings'] = df['savings'].apply(lambda x: group_savings(x))
         df['employment'] = df['employment'].apply(lambda x: group_employ(x))
-        df['age'] = df['age'].apply(lambda x: np.float(x >= 26))
+        df['age'] = (df['age'] >= 26).astype(float)
         df['status'] = df['status'].apply(lambda x: group_status(x))
 
         return df