block_timestamp::Date AS date,tx_hash,

amount_in_usd AS amountUSD,

origin_from_address as user

from polygon.defi.ez_dex_swaps

where amount_in_usd<power(10,6)

and tx_hash in (select distinct(tx_hash) from polygon.core.ez_decoded_event_logs where origin_to_address in ('0xec7be89e9d109e7e3fec59c222cf297125fefda2','0xef1c6e67703c7bd7107eed8303fbe6ec2554bf6b','0x4c60051384bd2d3c01bfc845cf5f4b44bcbe9de5','0x643770e279d5d0733f21d6dc03a8efbabf3255b4'))

and date>='2023-01-01'

and platform = 'uniswap-v3'

case when date>='2023-10-17' then 'after fee changes' else 'before fee changes' end as type,

count(distinct(user)) as "Users",

count(distinct tx_hash) as "Swaps",

avg(amountUSD) as "Amount Avg",

sum(amountUSD) as "Volume",

date_trunc('{{ time }}', date) as dt,

sum("Swaps") over (partition by type order by date_trunc('{{ time }}', date)) as "Swaps(cum)",

sum("Volume") over (partition by type order by date_trunc('{{ time }}', date)) as "Volume(cum)",

(("Swaps" - lag("Swaps", 1) over (partition by type order by date_trunc('{{ time }}', date)))/lag("Swaps", 1) over (partition by type order by date_trunc('{{ time }}', date))) * 100 as "swap changes(%)",

(("Volume" - lag("Volume", 1) over (partition by type order by date_trunc('{{ time }}', date)))/lag("Volume", 1) over (partition by type order by date_trunc('{{ time }}', date))) * 100 as "volume changes(%)",

(("Users" - lag("Users", 1) over (partition by type order by date_trunc('{{ time }}', date)))/lag("Users", 1) over (partition by type order by date_trunc('{{ time }}', date))) * 100 as "user changes(%)"

from polygon

group by type,dt