marketing-analytics/predicting/future-customer-value-segments/fcvs_pipeline_bq.py [546:582]:
- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
        )

        prediction_summary_temp = (
            prediction_by_customer
            | beam.Map(lambda x: (x[9], x))  # key: segment
            | 'Group customer predictions by segment' >> beam.GroupByKey()
            | beam.FlatMap(c.generate_prediction_summary,
                           pvalue.AsSingleton(options)
                           )  # (segment, average_retention_probability,
                              #  average_predicted_customer_value,
                              #  average_predicted_order_value,
                              #  average_predicted_purchases, total_customer_value,
                              #  number_of_customers)
        )

        tot_equity = (
            prediction_summary_temp
            | beam.Map(lambda x: x[5])  # total_customer_value
            | beam.CombineGlobally(sum)
        )

        prediction_summary = (
            prediction_summary_temp
            | beam.FlatMap(
                c.calculate_perc_of_total_customer_value,
                pvalue.AsSingleton(tot_equity),
                pvalue.AsSingleton(options)
                )  # (segment, average_retention_probability,
                   #  average_predicted_customer_value,
                   #  average_predicted_order_value,
                   #  average_predicted_purchases,
                   #  total_customer_value, number_of_customers,
                   #  perc_of_total_customer_value)
        )

        _ = (
            prediction_summary
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marketing-analytics/predicting/future-customer-value-segments/fcvs_pipeline_csv.py [451:487]:
- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
        )

        prediction_summary_temp = (
            prediction_by_customer
            | beam.Map(lambda x: (x[9], x))  # key: segment
            | 'Group customer predictions by segment' >> beam.GroupByKey()
            | beam.FlatMap(c.generate_prediction_summary,
                           pvalue.AsSingleton(options)
                           )  # (segment, average_retention_probability,
                              #  average_predicted_customer_value,
                              #  average_predicted_order_value,
                              #  average_predicted_purchases, total_customer_value,
                              #  number_of_customers)
        )

        tot_equity = (
            prediction_summary_temp
            | beam.Map(lambda x: x[5])  # total_customer_value
            | beam.CombineGlobally(sum)
        )

        prediction_summary = (
            prediction_summary_temp
            | beam.FlatMap(
                c.calculate_perc_of_total_customer_value,
                pvalue.AsSingleton(tot_equity),
                pvalue.AsSingleton(options)
                )  # (segment, average_retention_probability,
                   #  average_predicted_customer_value,
                   #  average_predicted_order_value,
                   #  average_predicted_purchases,
                   #  total_customer_value, number_of_customers,
                   #  perc_of_total_customer_value)
        )

        _ = (
            prediction_summary
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