import pandas as pd
sql = ‘’’
with
create_player as(
select player_id, max(timestamp) as timestamp from mafia1_ods.game_log_create_player
where timestamp >= ‘2018-01-01’
group by player_id),

rank as(
SELECT CAST(FLOOR(group_id/5) as int64) as group_id, SUM(pay_dollar) as pay_dollars, count(*) as count FROM
(select MOD(CAST(CONCAT(‘0x’, SUBSTR(TO_HEX(MD5(CONCAT(‘0j46o’, CAST(player_id AS STRING)))),0, 8)) AS INT64), 100) as group_id, pay_dollar as pay_dollar FROM heidao-market.mafia1_pf.v_paid_order
WHERE pay_time >=‘2020-06-12 06:30:00’ and pay_time < ‘2020-06-20 00:00:00’ and player_id not in (select player_id from mafia1_pf.v_internal_player)
#last_timestamp = None
#and player_id in (select player_id from create_player where timestamp between ‘2020-05-12 03:00:00’ and ‘2020-06-01’)
)
group by group_id
order by pay_dollars)

select group_id, pay_dollars/total_dollars as ratio, count, pay_dollars, pay_dollars/count as mean FROM rank, (select SUM(pay_dollars) as total_dollars FROM rank)
#Order by ratio desc
order by group_id desc
‘’’
result = pd.read_gbq(sql, dialect=‘standard’, project_id = ‘heidao-market’)
print(result.head(50))

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