FROM_ADDRESS as u1,

min(BLOCK_TIMESTAMP) as add_time

from polygon.udm_events

where TO_ADDRESS= '0x0319000133d3ada02600f0875d2cf03d442c3367'

and BLOCK_TIMESTAMP>= '2022-01-01'

group by 1),

t2 as(select

TO_ADDRESS as u2,

max(BLOCK_TIMESTAMP) as remove_time

from polygon.udm_events

where FROM_ADDRESS= '0x0319000133d3ada02600f0875d2cf03d442c3367'

and BLOCK_TIMESTAMP>= '2022-01-01'

group by 1)

t1.u1 as users,

abs(DATEDIFF(day, add_time,remove_time)) as average_time

from t1 inner join t2 on t1.u1=t2.u2)

select

case

when average_time<=10 then 'under 10 days'

when average_time between 11 and 50 then '11-50 days'

when average_time between 51 and 100 then '51-100 days'

when average_time>=100 then 'over 100 days'

end as times,

count (distinct users) as wallets

from total group by 1 having times is not null