case when payer ='0xecfad18ba9582d4f' then 'JoyRide'

when payer ='0x18eb4ee6b3c026d2' then 'Dapper (Mainly Used For NBA TopShot)'

when payer ='0x55ad22f01ef568a1' then 'Blocto'

when payer= '0x1b65c33d7a352c61' then 'Cricket Moments'

when payer= '0x6f649aee955bef6d' then 'RCRDSHP'

when payer= '0x94bb84386cfc3b5d' then 'Everbloom'

when payer= '0x9b00972a3ecb364b' then 'Seussibles'

when payer = '0x93615d25d14fa337' then 'ChainMonsters'

when payer = '0x8234007b36f8113c' then 'Monsoon'

when payer = '0x4bbff461fa8f6192' then 'Fantastec'

when payer = '0x39e42c67cc851cfb' then 'lilico'

else payer end as Payer_Name,

count (distinct t1.tx_id) as TX_Count,

count (distinct proposer) as Users_Count

from flow.core.fact_transactions t1 join flow.core.fact_events t2 on t1.tx_id = t2.tx_id

where EVENT_TYPE='TokensWithdrawn'

and t1.TX_SUCCEEDED ilike 'true'

group by 1,2

order by Users_Count DESC

limit 10)

select date_trunc(week,mindate) as date,

Payer_Name,

count (distinct proposer) as New_Users,

sum (new_users) over (partition by payer_name order by date) as Total_Users

from (

select proposer,

payer,

case when payer ='0xecfad18ba9582d4f' then 'JoyRide'

when payer ='0x18eb4ee6b3c026d2' then 'Dapper (NBA TopShot Wallet)'

when payer ='0x55ad22f01ef568a1' then 'Blocto'

when payer= '0x1b65c33d7a352c61' then 'Cricket Moments'

when payer= '0x6f649aee955bef6d' then 'RCRDSHP'

when payer= '0x94bb84386cfc3b5d' then 'Everbloom'