Sometime you may need to operate either the full data frame or a specific column with a function and add new column which consist the results. This is how you can do it:
# Create a test frame c_names = ['Prediction'] data1 = np.array([[0.12], [0.43], [0.90], [0.002], [0.52]]) df = h2o.H2OFrame().from_python(data1, destination_frame='df', column_names=c_names) # Applying the function on specific column from frame and creating new column into same data frame: df['new_prediction'] = df['Prediction']*1000 print df
Thats it, enjoy!!