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Mise à jour d'elementary et ajouts des modèles relatifs aux statistiques de campagnes (#2880)
* Updates elementary to latest version Also adds two models to monitor campaigns statistics. * Fixes where clause issue * true to True * Updates where clause * Adds distance filter
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‎dbt/models/metrics/_monthly_stats_acceptability_rules.yml‎

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models:
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- name: monthly_stats_acceptability_rules
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description: >
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Estimation du nombre de journeys ne respectant pas les règles d'acceptabilité et du montant d'incitation estimé associé.
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Les paramètres pris pour l'estimation sont 4% des trajets ne respectant pas les règles pour un montant moyen de 1,045€.
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Le montant moyen correspond à la moyenne entre l'incitation moyenne des trajets capturés en S1 2024 (avec Ynstant)
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et celle des trajets capturés en S2 2023 (Sans Ynstant).
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Estimation du nombre de journeys ne respectant pas les règles d'acceptabilité et du montant d'incitation
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estimé associé.
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Les paramètres pris pour l'estimation sont 4% des trajets ne respectant pas les règles pour un montant
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moyen de 1,045€.
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Le montant moyen correspond à la moyenne entre l'incitation moyenne des trajets capturés en S1 2024
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(avec Ynstant) et celle des trajets capturés en S2 2023 (Sans Ynstant).
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Voir https://www.notion.so/KPIs-r-gle-acceptabilit-191994bec93180c38b76e8560ad1f891?pvs=4.
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columns:
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- name: mois
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- name: month
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data_type: timestamp with time zone
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- name: journeys_count
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data_type: numeric

‎dbt/models/metrics/_monthly_stats_campaigns_revenues.yml‎

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version: 2
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models:
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- name: monthly_stats_campaigns_revenues
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columns:
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- name: month
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data_type: timestamp with time zone
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- name: siret
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data_type: character varying
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- name: legal_name
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data_type: character varying
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- name: journeys_count
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data_type: bigint
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- name: avg_driver_revenue
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data_type: numeric
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- name: avg_distance
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data_type: numeric
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- name: min_revenue
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data_type: integer
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- name: avg_driver_revenue_per_km
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data_type: numeric
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- name: avg_driver_revenue_per_km_18_30
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data_type: numeric
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- name: avg_driver_revenue_per_km_filtered
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data_type: numeric
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- name: avg_driver_revenue_per_km_filtered_18_30
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data_type: numeric
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- name: avg_passenger_contribution_per_km
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data_type: numeric
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- name: avg_passenger_contribution_per_km_18_30
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data_type: numeric
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- name: avg_passenger_contribution_per_km_filtered
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data_type: numeric
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- name: avg_passenger_contribution_per_km_filtered_18_30
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data_type: numeric
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- name: avg_incentive_per_km
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data_type: numeric
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- name: avg_incentive_per_km_18_30
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data_type: numeric
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- name: avg_incentive_per_km_filtered
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data_type: numeric
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- name: avg_incentive_per_km_filtered_18_30
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data_type: numeric

‎dbt/models/metrics/_monthly_stats_campaigns_revenues_by_operator.yml‎

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version: 2
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models:
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- name: monthly_stats_campaigns_revenues_by_operator
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columns:
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- name: month
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data_type: timestamp with time zone
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- name: operator_id
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data_type: integer
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- name: operator_name
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data_type: character varying
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- name: siret
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data_type: character varying
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- name: legal_name
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data_type: character varying
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- name: journeys_count
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data_type: bigint
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- name: avg_driver_revenue
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data_type: numeric
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- name: avg_distance
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data_type: numeric
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- name: min_revenue
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data_type: integer
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- name: avg_driver_revenue_per_km
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data_type: numeric
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- name: avg_driver_revenue_per_km_18_30
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data_type: numeric
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- name: avg_driver_revenue_per_km_filtered
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data_type: numeric
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- name: avg_driver_revenue_per_km_filtered_18_30
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data_type: numeric
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- name: avg_passenger_contribution_per_km
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data_type: numeric
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- name: avg_passenger_contribution_per_km_18_30
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data_type: numeric
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- name: avg_passenger_contribution_per_km_filtered
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data_type: numeric
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- name: avg_passenger_contribution_per_km_filtered_18_30
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data_type: numeric
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- name: avg_incentive_per_km
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data_type: numeric
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- name: avg_incentive_per_km_18_30
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data_type: numeric
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- name: avg_incentive_per_km_filtered
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data_type: numeric
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- name: avg_incentive_per_km_filtered_18_30
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data_type: numeric

‎dbt/models/metrics/_monthly_stats_interoperator_rules.yml‎

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models:
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- name: monthly_stats_interoperator_rules
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description: >
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Estimation du nombre de journeys ne respectant pas les règles antifraudes interopérateurs et du montant d'incitation estimé associé.
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Les paramètres pris pour l'estimation sont 7% des trajets ne respectant pas les règles ce qui conerne également 7% des incitations.
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Estimation du nombre de journeys ne respectant pas les règles antifraudes interopérateurs et du
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montant d'incitation estimé associé.
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Les paramètres pris pour l'estimation sont 7% des trajets ne respectant pas les règles ce qui conerne
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également 7% des incitations.
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Voir https://www.notion.so/Calculer-le-montant-de-Fraude-inter-op-rateur-vit-1ca994bec93180ae817bee35f00a847c?pvs=4.
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columns:
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- name: mois
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- name: month
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data_type: timestamp with time zone
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- name: journeys_count
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data_type: numeric

‎dbt/models/metrics/monthly_stats_campaigns_revenues.sql‎

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{{
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config(
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materialized = 'incremental',
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unique_key = ['month',"siret"],
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incremental_strategy = "delete+insert",
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indexes = [{"columns":['month',"siret"],"unique":True}]
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)
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}}
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with trips as (
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select
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c._id,
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oi.siret,
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max(c.start_datetime) as start_datetime,
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max(c.distance) as distance,
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max(c.driver_revenue) as driver_revenue,
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max(c.passenger_contribution) as passenger_contribution,
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sum(oi.amount) as amount
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from carpool_v2.carpools as c
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left join carpool_v2.operator_incentives as oi
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on
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c._id = oi.carpool_id
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{% if is_incremental() %}
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where
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c.start_datetime
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>= coalesce((select max(month) from {{ this }}), '1900-01-01')
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{% else %}
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where c.start_datetime >= '2022-01-01'
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{% endif %}
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-- account for multiple incentives amounts for the same siret on the same trip
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group by 1, 2
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),
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agg_data as (
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select
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date_trunc(
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'month', start_datetime
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) as month,
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siret,
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count(
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distinct _id
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) as journeys_count,
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count(
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distinct _id
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) filter (
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where distance between 18000 and 30000
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)
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as journeys_count_18_30,
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count(
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distinct _id
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) filter (
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where amount > 0
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)
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as journeys_count_filtered,
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count(
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distinct _id
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) filter (
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where (distance between 18000 and 30000) and amount > 0
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)
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as journeys_count_filtered_18_30,
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avg(
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driver_revenue / 100
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) as avg_driver_revenue,
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avg(
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distance / 1000
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) as avg_distance,
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min(
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driver_revenue / 100
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) as min_revenue,
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10
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* avg(
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driver_revenue::numeric / distance
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) as avg_driver_revenue_per_km,
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10
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* avg(driver_revenue::numeric / distance) filter (
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where distance between 18000 and 30000
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) as avg_driver_revenue_per_km_18_30,
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10
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* avg(driver_revenue::numeric / distance) filter (
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where amount > 0
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) as avg_driver_revenue_per_km_filtered,
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10
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* avg(driver_revenue::numeric / distance) filter (
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where (distance between 18000 and 30000) and amount > 0
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) as avg_driver_revenue_per_km_filtered_18_30,
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10
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* avg(
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passenger_contribution::numeric / distance
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) as avg_passenger_contribution_per_km,
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10
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* avg(passenger_contribution::numeric / distance) filter (
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where distance between 18000 and 30000
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) as avg_passenger_contribution_per_km_18_30,
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10
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* avg(passenger_contribution::numeric / distance) filter (
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where amount > 0
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) as avg_passenger_contribution_per_km_filtered,
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10
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* avg(passenger_contribution::numeric / distance) filter (
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where (distance between 18000 and 30000) and amount > 0
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) as avg_passenger_contribution_per_km_filtered_18_30,
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10
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* avg(
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amount::numeric / distance
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) as avg_incentive_per_km,
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10
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* avg(amount::numeric / distance) filter (
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where distance between 18000 and 30000
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) as avg_incentive_per_km_18_30,
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10
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* avg(amount::numeric / distance) filter (
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where amount > 0
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) as avg_incentive_per_km_filtered,
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10
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* avg(amount::numeric / distance) filter (
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where (distance between 18000 and 30000) and amount > 0
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) as avg_incentive_per_km_filtered_18_30
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from trips
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where distance > 0
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group by 1, 2
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order by 1
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)
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select
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a.month,
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a.siret,
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c.legal_name,
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a.journeys_count,
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a.journeys_count_18_30,
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a.journeys_count_filtered,
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a.journeys_count_filtered_18_30,
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a.avg_driver_revenue,
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a.avg_distance,
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a.min_revenue,
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a.avg_driver_revenue_per_km,
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a.avg_driver_revenue_per_km_18_30,
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a.avg_driver_revenue_per_km_filtered,
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a.avg_driver_revenue_per_km_filtered_18_30,
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a.avg_passenger_contribution_per_km,
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a.avg_passenger_contribution_per_km_18_30,
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a.avg_passenger_contribution_per_km_filtered,
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a.avg_passenger_contribution_per_km_filtered_18_30,
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a.avg_incentive_per_km,
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a.avg_incentive_per_km_18_30,
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a.avg_incentive_per_km_filtered,
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a.avg_incentive_per_km_filtered_18_30
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from agg_data as a
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left join company.companies as c on a.siret = c.siret

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