Let’s see whether it is true.print(train.banner_pos.value_counts()/len(train))Figure 16banner_pos = train.banner_pos.unique()banner_pos.sort()ctr_avg_list=[]for i in banner_pos: ctr_avg=train.loc[np.where((train.banner_pos == i))].click.mean() ctr_avg_list.append(ctr_avg) print("for banner position: {},…
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