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Wed Jul 06 2022 13:45:28 GMT+0000 (Coordinated Universal Time)

-- subquery to prepare the data
with prep_traffic as (
select
    user_pseudo_id,
    (select value.int_value from unnest(event_params) where key = 'ga_session_id') as session_id,
    max((select value.string_value from unnest(event_params) where key = 'medium')) as medium,
    max((select value.string_value from unnest(event_params) where key = 'source')) as source,
    max((select value.string_value from unnest(event_params) where key = 'campaign')) as campaign,
    max((select value.string_value from unnest(event_params) where key = 'session_engaged')) as session_engaged,
    max((select value.int_value from unnest(event_params) where key = 'engagement_time_msec')) as engagement_time_msec,
    -- change event_name to the event(s) you want to count
    countif(event_name = 'page_view') as event_count,
    -- change event_name to the conversion event(s) you want to count
    countif(event_name = 'add_payment_info') as conversions,
    sum(ecommerce.purchase_revenue) as total_revenue   
from
    -- change this to your google analytics 4 bigquery export location
    `bigquery-341716.analytics_278788286.events_*`
where
    -- change the date range by using static and/or dynamic dates
    _table_suffix between '20220705' and format_date('%Y%m%d',date_sub(current_date(), interval 1 day))
group by 
    user_pseudo_id,
    session_id)

-- main query
select
    concat(ifnull(source,'(direct)'),' / ',ifnull(medium,'(none)')) as session_source_medium,
    -- ifnull(medium,'(none)') as session_medium,
    -- ifnull(source,'(direct)') as session_source,
    -- ifnull(campaign,'(direct)') as session_campaign,
    /* -- definitions of the channel grouping based on the source / medium of every session
    case
        when source is null and (medium = '(not set)' or medium is null) then 'Direct'
        when medium = 'organic' then 'Organic Search'
        when regexp_contains(medium, r'^(social|social-network|social-media|sm|social network|social media)$') then 'Social'
        when medium = 'email' then 'Email'
        when medium = 'affiliate' then 'Affiliates'
        when medium = 'referral' then 'Referral'
        when regexp_contains(medium, r'^(cpc|ppc|paidsearch)$') then 'Paid Search'
        when regexp_contains(medium, r' ^(cpv|cpa|cpp|content-text)$') then 'Other Advertising'
        when regexp_contains(medium, r'^(display|cpm|banner)$') then 'Display'
        else '(Other)' end as session_default_channel_grouping,
    */
    count(distinct user_pseudo_id) as users,
    count(distinct concat(user_pseudo_id,session_id)) as sessions,
    count(distinct case when session_engaged = '1' then concat(user_pseudo_id,session_id) end) as engaged_sessions,
    safe_divide(count(distinct case when session_engaged = '1' then concat(user_pseudo_id,session_id) end),count(distinct user_pseudo_id)) as engaged_sessions_per_user,
    safe_divide(count(distinct case when session_engaged = '1' then concat(user_pseudo_id,session_id) end),count(distinct concat(user_pseudo_id,session_id))) as engagement_rate,
    sum(event_count) as event_count,
    sum(conversions) as conversions,
    ifnull(sum(total_revenue),0) as total_revenue
from
    prep_traffic
group by
    session_source_medium
    -- ,session_medium
    -- ,session_source
    -- ,session_campaign
    -- ,session_default_channel_grouping
order by
    users desc

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#sql #bigquery

percent rides from Reby versus other operators

with data as (
select
    date(created_at) as date,
    sum(if(app_promoting_co = 'Reby' and owner_co != 'Reby',1,0)) as hey,
    count(*) as all_
from `reby-cloud.analytics_reby_v1_eu.transactions_combined_reassigned_final`
where type like 'ride%'
    and date(created_at) > current_date - 50
    and service_area = 'Barcelona'
group by 1
--order by 1 desc
)
select hey / all_ from data order by 1 desc

#sql #bigquery

kernel - OCI Reby

select
    money_in,
    money_out,
    count(*),
    sum(amount)
from (
select
 amount,
 date(date_ts) as date,
 case
    when amount between 0 and 20 then "0-20"
    when amount between 21 and 500 then "20-500"
    when amount between 21 and 500 then "500-1000"
    when amount >1000 then "+1000"
    else "other"
end as money_in,
case
    when amount between -20 and 0 then "0-20"
    when amount between -500 and -1000 then "20-500"
    when amount between -1000 and -500 then "500-1000"
    when amount <-1000 then "+1000"
    else "other"
end as money_out,

from `reby-cloud.reby_fin_eu.payments_all_platforms`
where
  date(date_ts) BETWEEN '2021-04-01' and '2021-06-30'
  and payment_provider = 'kernel'
--order by date_ts desc
)
group by 1,2

#sql #bigquery

user <> service_area

SELECT
    id,
    stats[offset(0)].total_rides,
    mv.service_area
FROM
  `reby-cloud.analytics_reby_v1_eu.pg_users_json` u
left join `reby-cloud.reby_marketing_eu.users_servicearea_first_mv_ride` mv on u.id = mv.user_id
where date(created_at) = current_date -2
order by 2 desc
;

#sql #bigquery

user interactions get ip for country and funnel

--with application_opened as (
select
    original_timestamp,
    anonymous_id,
    context_ip,
    context_network_carrier,
    context_os_name,
    context_os_version,
    user_id
from(
SELECT
    original_timestamp,
    anonymous_id,
    context_ip,
    context_network_carrier,
    context_os_name,
    context_os_version,
    user_id,
    row_number() over (partition by anonymous_id order by original_timestamp asc) as r_n
FROM
  `reby-safir.react_native.install_attributed`
WHERE
  context_app_name = 'Reby'
  --and user_id = 'usr_3t8h6t8c4ppubjp9vjvh'
  and anonymous_id = '1eafe4e3-f4d8-416d-80c1-db0a95191b55'
  /*
  and _PARTITIONTIME BETWEEN TIMESTAMP_TRUNC(TIMESTAMP_MICROS(UNIX_MICROS(CURRENT_TIMESTAMP()) - 60 * 60 * 60 * 24 * 1000000), DAY, 'UTC')
					AND TIMESTAMP_TRUNC(CURRENT_TIMESTAMP(), DAY, 'UTC')
    
			
    */
    )
--where r_n = 1
order by r_n asc
--)
;
select *
from `reby-safir.react_native.identifies`
where user_id = 'usr_3t8cxanx6kehxg38n5m1'
order by original_timestamp asc
;
select *
from `reby-safir.react_native.finish_ride`
where user_id = 'usr_3t8ethqfzs32sp1mcu5h'
order by original_timestamp asc
;

#sql #bigquery

facebook data from bigquery

with ads_data as (
SELECT
    ad_id,
    adset_id,
    campaign_id,
    status,
    sum(impressions) clicks,
    sum(spend) as investment
FROM `reby-cloud.facebook_ads.insights` ai
left join `reby-cloud.facebook_ads.ads` ads on ai.ad_id = ads.id

--WHERE DATE(_PARTITIONTIME) = "2021-07-06"
group by 1,2,3,4
)
select * from ads_data where ad_id = '23843560033720454' order by clicks desc

#sql #bigquery

promos mal asignadas

--'usr_3t7nh9pkvax1j6412nv1'
select * from (
with promotions as (
SELECT * FROM EXTERNAL_QUERY("reby-cloud.eu.reby_prod", 
'''
SELECT
    id_to_time(id) as created_at,
    concat('acc_',id_to_text(account_id)) as account_id,
    balance__amount as balance_amount,
    balance__currency as balance_currency,
    concat('c_',id_to_text(company_id)) as company_id,
    free_unlocks,
    concat('cpua_',id_to_text(id)) as id,
    concat('tx_',id_to_text(last_promotion_transaction_id)) as transaction_id,
    concat('usr_',id_to_text(user_id)) as user_id
FROM company_user_promotion_account
--where user_id = id_from_text('3t7nh9pkvax1j6412nv1')
;
'''
    )
)
select
    *
from (
    SELECT
    --promotions.balance_amount,
    sa.service_area,
    cp.code,
    cpu.*
    FROM
    `reby-cloud.analytics_reby_v1_eu.pg_company_promotion_usage` cpu
    left join `reby-cloud.analytics_reby_v1_eu.pg_company_promotion` cp on cpu.company_promotion_id = cp.id
    left join `reby-cloud.analytics_reby_v1_eu.reby_users_servicearea` sa on sa.user_id = cpu.user_id
    --left join promotions on cpu.user_id =promotions.user_id
    --where sa.service_area in ('Zaragoza','Gijón')
    --and date(expiration_date) > current_date and date(cpu.created_at) > current_date -15
    --where cpu.user_id = 'usr_3t7nh9pkvax1j6412nv1'
    --order by cpu.created_at desc
)
where
    (service_area = 'Zaragoza' AND code in ('SEVILLAES','REBYBCN','REBYJON','REBYGONA','SEVILLAES','TOTAREBY','HOLAMOTOS')) OR
    (service_area = 'Sevilla' AND code in ('REBYBCN','REBYJON','REBYGONA','TOTAREBY','HOLAMOTOS','REBYGO')) OR
    (service_area = 'Gijón' AND code in ('SEVILLAES','REBYBCN','REBYGONA','SEVILLAES','TOTAREBY','HOLAMOTOS')) OR
    (service_area = 'Terrassa' AND code in ('SEVILLAES','REBYBCN','REBYGONA','SEVILLAES')) OR
    (service_area in ('Napoles','Lecce','Minturno','Bergamo','Grosseto','Caserta') AND code in ('SEVILLAES','REBYBCN','REBYJON','REBYGONA','SEVILLAES','REBYGO','HOLAMOTOS'))
)
--where user_id = 'usr_3t7nh9pkvax1j6412nv1'
where value_remaining_amount > 0
and is_expired is false

#sql #bigquery

fix serivce_area_pricing_daily when missing date

INSERT `reby-cloud.analytics_reby_v1_eu.service_area_pricing_daily`
    (date, name, company_id,service_area_id,vehicle_type,price_per_minute,
    price_base_amount,original_price_per_minute,original_price_base_amount)
SELECT date('2021-07-17'), name, company_id,service_area_id,vehicle_type,price_per_minute,
    price_base_amount,original_price_per_minute,original_price_base_amount
FROM `reby-cloud.analytics_reby_v1_eu.service_area_pricing_daily`
where date = '2021-07-18'

#sql #bigquery #datastudio

datastudio date range parameter format

WHERE DATE(cat_tbl.date)
    BETWEEN PARSE_DATE('%Y%m%d', @DS_START_DATE) AND
    PARSE_DATE('%Y%m%d', @DS_END_DATE)

#sql #bigquery #datastudio

check non_promoted from gerard and oficial table

create or replace table `temp_eu.delete_gerardm_rcnp_` as (
select npr_rscb = RCnp as bool,* from (
SELECT 
        --vd.*,
        r.created_at,
        r.user_id,
        r.id as ride_id,
        SUM(rc.theoretical_cost)/100 AS RC, 
        SUM(rc.non_promoted)/100 AS RCnp, 
        SUM(rc.theoretical_cost-rc.non_promoted)/100 AS RCp,
        --ops_managers_dashboard.TRUNC_DATE_ISO('DAY', date(datetime(r.created_at,"Europe/Madrid"))) as week_at 
    FROM`reby-cloud.analytics_reby_v1_eu.pg_rides` AS r
    LEFT JOIN `reby-cloud.analytics_reby_v1_eu.vehicle_daily` AS vd
        ON r.vehicle_id = vd.vehicle_id AND date(datetime(r.created_at,"Europe/Madrid")) = vd.date
    LEFT JOIN `reby-cloud.analytics_reby_v1_eu.py_ridestatus_combined` AS rc
        ON r.id = rc.ride_id
    LEFT JOIN `reby-cloud.analytics_reby_v1_eu.pg_vehicles` AS v
        ON r.vehicle_id = v.id
    LEFT JOIN `reby-cloud.analytics_reby_v1_eu.pg_service_area` AS sa
        ON r.service_area_id = sa.service_area_id
    LEFT JOIN `reby-cloud.analytics_reby_v1_eu.pg_tpl` AS tpl
        ON vd.tpl_provider_id = tpl.id
   -- WHERE 
        --date(datetime(r.created_at,"Europe/Madrid")) >= ops_managers_dashboard.DATE_AGO_MANAGERS_ISO('DAY')
        --AND ST_DISTANCE (ST_GEOGPOINT(r.longitude_initial, r.latitude_initial), ST_GEOGPOINT(tpl.longitude, tpl.latitude)) > 200
        --AND ST_WITHIN(ST_GEOGPOINT(r.longitude_initial, r.latitude_initial), ST_GeogFromText(sa.geometry))
        --AND v.printed_code IS NOT NULL AND vd.date >= ops_managers_dashboard.DATE_AGO_MANAGERS_ISO('DAY')
        --AND rc.ride_id IS NOT NULL
        --where r.id = 'r_3rytmr4br7g5qlu4jbqh'
        group by 1,2,3
    --GROUP BY week_at 
    --ORDER BY week_at DESC
) as a--where ride_id = 'r_3t26l79xmu2xa7nyu3n1'
full join (select ride_id ride_id_rscb,service_area, sum(non_promoted)/100 as npr_rscb
            from `reby-cloud.analytics_reby_v1_eu.py_ridestatus_combined` group by 1,2) b
    on a.ride_id = b.ride_id_rscb
)

/*
create or replace table `reby-cloud.analytics_reby_v1_eu.vehicle_daily` 
PARTITION BY date
CLUSTER BY service_area_id,company_id
AS
select * except(r_n) from (
select
    *,
    row_number() over (partition by date,vehicle_id order by created_at asc) as r_n
from `reby-cloud.analytics_reby_v1_eu.vehicle_daily`
) where r_n = 1
*/

#sql #bigquery #datastudio

informe sevilla

--Creación de usuarixs nuevxs
with base_data as (
select 
    date(u.created_at) as date,
    date_trunc(date(u.created_at),MONTH) as month,
    mv.service_area,
    sum(if(mv.first_ride_date is not null,1,0)) as has_ride,
    count(*) users_created
from `reby-cloud.analytics_reby_v1_eu.pg_users_json` u
left join `reby-cloud.reby_marketing_eu.users_servicearea_first_mv_ride` mv
    on u.id = mv.user_id
where mv.service_area = 'Sevilla'
group by 1,2,3
--order by 1 desc
)
select 
    *
    --lag(users_created) over (partition by month order by month asc) as prev_month_users
from base_data
order by date desc
;
--métricas de viajes individuales
select
    date(created_at) as date,
    r.id as ride_id,
    r.minutes,
    extract(hour from datetime(created_at,"Europe/Madrid")) as hour,
    if(plan_usage_id is null,0,1) as plan_usage,
    FORMAT_DATE('%A', date(created_at)) AS weekday_name,
    r.distance/100 as distance_km,
    r.ride_cost_time as ride_cost,
    geo.Distri_11D as distrito_inicial,
    geo2.Distri_11D as distrito_final,
from analytics_reby_v1_eu.pg_rides r
join `reby-cloud.analytics_reby_v1_eu.geo_sevilla_distritos` geo
    on st_within(st_geogpoint(r.longitude_initial,r.latitude_initial),geo.geometry)
join `reby-cloud.analytics_reby_v1_eu.geo_sevilla_distritos` geo2
    on st_within(st_geogpoint(r.longitude_final,r.latitude_final),geo2.geometry)
where r.service_area_id = 'sa_3qr9213ajv94b6v49h5h'
order by 1 desc
;
--ride linestrings
with rides_data as (
select
	id,
  created_at,
  starting.latitude as lat_init,
  starting.longitude as long_init,
  ending.latitude as lat_fin,
  ending.longitude as long_fin,
  distance/1000 as dist_km,
  minutes,
	--CONCAT(starting.latitude,',',starting.longitude) AS marker_start,
	--CONCAT(ending.latitude,',',ending.longitude) AS marker_end
from (
select
  r.created_at,
  r.minutes,
  r.distance,
  r.id,
  --path,
  path[offset(0)] as starting,
  path[offset(array_length(path)-1)] as ending,
  --array_length(path)
from `analytics_reby_v1_eu.pg_rides_json` r
left join `reby-cloud.analytics_reby_v1_eu.pg_vehicles` v
  on r.vehicle_id = v.id
where array_length(path) > 3
and date(r.created_at) >= '2021-06-01'
and date(r.created_at) <= '2021-09-01'
and r.service_area_id = 'sa_3qr9213ajv94b6v49h5h'
--and v.vehicle_type = 'motorcycle'
--where id = 'r_3qm5ua4jymv1ta3tbmq1'
--group by 1
  )
),

linestrings as (
select 
  ri.id,
  --st_asgeojson(st_geogpoint(rd.long_init,rd.lat_init)) as starting_point,
  concat("Linestring(",string_agg(concat(p.longitude," ",p.latitude), ","),")") as path
from `analytics_reby_v1_eu.pg_rides_json` ri, unnest(path) as p
where id in (select id from rides_data)
and date(created_at) >= '2021-06-01'
and date(created_at) <= '2021-09-01'
group by 1
),

linestrings_geo as (
select 
  rd.id,
  st_asgeojson(st_geogpoint(rd.long_init,rd.lat_init)) as starting_point,
  st_asgeojson(st_geogpoint(rd.long_fin,rd.lat_fin)) as ending_point,
  st_asgeojson(SAFE.st_geogfromtext(path)) as paths
from linestrings ls
join rides_data rd on ls.id = rd.id
)

select * from linestrings_geo

#sql #bigquery #datastudio

banned users

--usuarios con varias tarjetas
SELECT concat('https://admin.reby.tech/riders/usr_', id_to_text(ppg.user_id)),
       count(distinct(card__fingerprint))
FROM payment_processor_gateway ppg
LEFT JOIN banned_device bd ON ppg.user_id=bd.user_id
where reason is null
GROUP BY 1
having count(distinct(card__fingerprint))>5
ORDER BY 2 DESC
LIMIT 100;


--tarjetas utilizadas por varias cuentas
SELECT --concat('https://admin.reby.tech/riders/usr_', id_to_text(ppg.user_id)),
card__fingerprint,
card__last_four,
       count(distinct(ppg.user_id))
FROM payment_processor_gateway ppg
left join public.user on public.user.id=ppg.user_id
LEFT JOIN banned_device bd ON ppg.user_id=bd.user_id
where reason is null and card__fingerprint is not null
GROUP BY 1,2
having count(distinct(ppg.user_id))>3
ORDER BY 3 DESC;

--usuarios que utilizan la tarjeta con código que introduzcáis:
SELECT 
distinct(concat('https://admin.reby.tech/riders/usr_', id_to_text(ppg.user_id))),
--distinct(ppg.user_id),
card__fingerprint
FROM payment_processor_gateway ppg
LEFT JOIN banned_device bd ON ppg.user_id=bd.user_id
where reason is null and card__fingerprint='+7qy4w/5VsCCCtwf'   
ORDER BY 1 DESC
LIMIT 100


--usuarios que han utilizado tarjetas que se han utilizado en más de 5 cuentas
with data as (SELECT --concat('https://admin.reby.tech/riders/usr_', id_to_text(ppg.user_id)),
card__fingerprint,
       count(distinct(ppg.user_id))
FROM payment_processor_gateway ppg
left join public.user on public.user.id=ppg.user_id
LEFT JOIN banned_device bd ON ppg.user_id=bd.user_id
where reason is null and card__fingerprint is not null and public.user.is_staff is false and public.user.is_deleted=false
GROUP BY 1
having count(distinct(ppg.user_id))>3
ORDER BY 2 DESC)
select
distinct(public.user.phone_number),
public.user.first_name,
public.user.last_name
--data.card__fingerprint
--distinct(ppg.user_id),
FROM data 
left join payment_processor_gateway ppg on ppg.card__fingerprint=data.card__fingerprint 
left join public.user on public.user.id=ppg.user_id
and public.user.is_staff is false and public.user.phone_number is not null
--order by data.card__fingerprint;

--usuarios con dispositivos en los que se han registrado más de 5 cuentas
with data as (SELECT hash_device,
       count(hash_device) as number_accounts
FROM user_device ud
GROUP BY 1
HAVING count(hash_device)>=5
ORDER BY 2 desc)
SELECT distinct(public.user.phone_number),
public.user.first_name,
       public.user.last_name,
       public.user.phone_number,
       --data.hash_device,
       service_area.name,
       user_last_location.last_location_at
FROM DATA
LEFT JOIN user_device ud ON ud.hash_device=data.hash_device
LEFT JOIN public.user ON public.user.id=ud.user_id
AND public.user.is_staff IS FALSE
AND public.user.phone_number IS NOT NULL
and public.user.is_deleted=false
left join user_last_location on public.user.id=user_last_location.user_id 
left join service_area on user_last_location.last_service_area_id = service_area.id
where service_area.name='Terrassa'
ORDER BY user_last_location.last_location_at desc
;

--Análisis usuario Alba
SELECT 
distinct(concat('https://admin.reby.tech/riders/usr_', id_to_text(ppg.user_id))),
--distinct(ppg.user_id),
card__fingerprint,
card__last_four
FROM payment_processor_gateway ppg
LEFT JOIN banned_device bd ON ppg.user_id=bd.user_id
where /* reason is null and*/ card__last_four in('1058','9219')  
ORDER BY 1 DESC
LIMIT 100

--usuarios que se han registrado en más de 5 dispositivos y balance negativo
with data as (SELECT id_to_text(user_id) as user_id,
       count(hash_device) as number_devices
FROM user_device ud
GROUP BY 1
HAVING count(hash_device)>=5
ORDER BY 2 desc)
SELECT public.user.first_name,
       public.user.last_name,
       public.user.phone_number,
       data.user_id,
       data.number_devices,
       service_area.name,
       user_last_location.last_location_at,
       account.balance__amount
FROM DATA
LEFT JOIN public.user ON id_to_text(public.user.id)=data.user_id
AND public.user.is_staff IS FALSE
AND public.user.phone_number IS NOT NULL
and public.user.is_deleted=false
left join user_last_location on public.user.id=user_last_location.user_id 
left join service_area on user_last_location.last_service_area_id = service_area.id
left join account on public.user.balance_account_id=account.id
where service_area.name='Terrassa' and account.balance__amount<0
ORDER BY user_last_location.last_location_at desc
;

#sql #bigquery #datastudio

banned users

--usuarios con varias tarjetas
SELECT concat('https://admin.reby.tech/riders/usr_', id_to_text(ppg.user_id)),
       count(distinct(card__fingerprint))
FROM payment_processor_gateway ppg
LEFT JOIN banned_device bd ON ppg.user_id=bd.user_id
where reason is null
GROUP BY 1
having count(distinct(card__fingerprint))>5
ORDER BY 2 DESC
LIMIT 100;


--tarjetas utilizadas por varias cuentas
SELECT --concat('https://admin.reby.tech/riders/usr_', id_to_text(ppg.user_id)),
card__fingerprint,
card__last_four,
       count(distinct(ppg.user_id))
FROM payment_processor_gateway ppg
left join public.user on public.user.id=ppg.user_id
LEFT JOIN banned_device bd ON ppg.user_id=bd.user_id
where reason is null and card__fingerprint is not null
GROUP BY 1,2
having count(distinct(ppg.user_id))>3
ORDER BY 3 DESC;

--usuarios que utilizan la tarjeta con código que introduzcáis:
SELECT 
distinct(concat('https://admin.reby.tech/riders/usr_', id_to_text(ppg.user_id))),
--distinct(ppg.user_id),
card__fingerprint
FROM payment_processor_gateway ppg
LEFT JOIN banned_device bd ON ppg.user_id=bd.user_id
where reason is null and card__fingerprint='+7qy4w/5VsCCCtwf'   
ORDER BY 1 DESC
LIMIT 100


--usuarios que han utilizado tarjetas que se han utilizado en más de 5 cuentas
with data as (SELECT --concat('https://admin.reby.tech/riders/usr_', id_to_text(ppg.user_id)),
card__fingerprint,
       count(distinct(ppg.user_id))
FROM payment_processor_gateway ppg
left join public.user on public.user.id=ppg.user_id
LEFT JOIN banned_device bd ON ppg.user_id=bd.user_id
where reason is null and card__fingerprint is not null and public.user.is_staff is false and public.user.is_deleted=false
GROUP BY 1
having count(distinct(ppg.user_id))>3
ORDER BY 2 DESC)
select
distinct(public.user.phone_number),
public.user.first_name,
public.user.last_name
--data.card__fingerprint
--distinct(ppg.user_id),
FROM data 
left join payment_processor_gateway ppg on ppg.card__fingerprint=data.card__fingerprint 
left join public.user on public.user.id=ppg.user_id
and public.user.is_staff is false and public.user.phone_number is not null
--order by data.card__fingerprint;

--usuarios con dispositivos en los que se han registrado más de 5 cuentas
with data as (SELECT hash_device,
       count(hash_device) as number_accounts
FROM user_device ud
GROUP BY 1
HAVING count(hash_device)>=5
ORDER BY 2 desc)
SELECT distinct(public.user.phone_number),
public.user.first_name,
       public.user.last_name,
       public.user.phone_number,
       --data.hash_device,
       service_area.name,
       user_last_location.last_location_at
FROM DATA
LEFT JOIN user_device ud ON ud.hash_device=data.hash_device
LEFT JOIN public.user ON public.user.id=ud.user_id
AND public.user.is_staff IS FALSE
AND public.user.phone_number IS NOT NULL
and public.user.is_deleted=false
left join user_last_location on public.user.id=user_last_location.user_id 
left join service_area on user_last_location.last_service_area_id = service_area.id
where service_area.name='Terrassa'
ORDER BY user_last_location.last_location_at desc
;

--Análisis usuario Alba
SELECT 
distinct(concat('https://admin.reby.tech/riders/usr_', id_to_text(ppg.user_id))),
--distinct(ppg.user_id),
card__fingerprint,
card__last_four
FROM payment_processor_gateway ppg
LEFT JOIN banned_device bd ON ppg.user_id=bd.user_id
where /* reason is null and*/ card__last_four in('1058','9219')  
ORDER BY 1 DESC
LIMIT 100

--usuarios que se han registrado en más de 5 dispositivos y balance negativo
with data as (SELECT id_to_text(user_id) as user_id,
       count(hash_device) as number_devices
FROM user_device ud
GROUP BY 1
HAVING count(hash_device)>=5
ORDER BY 2 desc)
SELECT public.user.first_name,
       public.user.last_name,
       public.user.phone_number,
       data.user_id,
       data.number_devices,
       service_area.name,
       user_last_location.last_location_at,
       account.balance__amount
FROM DATA
LEFT JOIN public.user ON id_to_text(public.user.id)=data.user_id
AND public.user.is_staff IS FALSE
AND public.user.phone_number IS NOT NULL
and public.user.is_deleted=false
left join user_last_location on public.user.id=user_last_location.user_id 
left join service_area on user_last_location.last_service_area_id = service_area.id
left join account on public.user.balance_account_id=account.id
where service_area.name='Terrassa' and account.balance__amount<0
ORDER BY user_last_location.last_location_at desc
;

#sql #bigquery #datastudio

create company_user table

SELECT
     *
     FROM
     EXTERNAL_QUERY("reby-cloud.eu.reby_prod",
     '''
     select 
     concat('cu_',id_to_text(cu.id)) as id,
     id_to_time(cu.id) as created_at,
     concat('acc_',id_to_text(cu.balance_account_id)) as account_id,
     concat('c_',id_to_text(cu.company_id)) as company_id,
     concat('usr_',id_to_text(cu.user_id)) as user_id,
     --id_to_time(cu.user_id) as user_first_created_at,
     firebase_user_token,
     is_deleted,
     updated_at
     from company_user cu 
     --where id >= id_from_time(NOW() - INTERVAL '1 DAY')
     --where date(id_to_time(id)) > now() - interval '3 day'
     where id < id_from_time(date('2020-06-01'))
     ''' )
     ;

#sql #bigquery #datastudio

conciliacion stripe con datos internos

create or replace table `temp_eu.delete_stripe_refunds` as (
select * from (
with pre_process as (
    SELECT
		*
		FROM
		`reby-cloud.reby_stripe.py_stripe_preprocessed`
		--where id in (select id from`reby-cloud.temp_eu.delete_stripe` where amount_refunded > 0 )
		--where customer = 'cus_GorMSGP2VREHQs'
		where rn = 1
		order by customer,id,rn asc
)

select
    case when refunds.charge is not null and charges.type ='refund' then refunds.balance_transaction else charges.balance_transaction
        end as balance_transaction,
    case when refunds.charge is not null and charges.type ='refund' then refunds.created_at else charges.created_at
        end as created_at,
    charges.charge_id,
    charges.type,
    charges.paid,
    charges.amount as charge_amount,
    case when refunds.charge is not null and charges.type ='refund' then refunds.amount else null
        end as refund_amount,
    charges.customer,
    charges.user_id
from (
    select
        spp.balance_transaction,
        s.*,
        u.id as user_id,
        sa.service_area
    from `reby-cloud.reby_stripe.py_stripe_processed` s
    left join `reby-cloud.analytics_reby_v1_eu.pg_users_json` u
        on s.customer = u.payment_processor[safe_offset(0)].token
    left join `reby-cloud.reby_marketing_eu.users_servicearea_first_mv_ride` sa
        on u.id = sa.user_id
    left join pre_process spp
            on spp.id = s.charge_id
    --order by 1,2,3,4,5,6,7,8,9,10,11,12,13
    where date(s.created_at) between '2021-02-01' and '2021-09-03'
    --order by balance_transaction desc
    ) as charges
    left join `reby-cloud.reby_stripe.stripe_refunds_api` refunds on charges.charge_id = refunds.charge
    --where refunds.status = 'succeeded'
)
)
;
select
  st.*,
  str.created_at,
  str.balance_transaction,
  str.user_id,
  str.charge_amount 
 from `reby-cloud.temp_eu.delete_stripe_downloaded_transactions` st
 left join `reby-cloud.temp_eu.delete_stripe_refunds` str on st.balance_transaction_id = str.balance_transaction

#sql #bigquery #datastudio

join python

left_df.merge(right_df, on='user_id', how='left', indicator=True)

meduim

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