count(distinct TX_HASH) as count_tx,count_tx/unique_addresses as avg_tx_user,

date_trunc('day', block_timestamp) as block_day,

case

when block_timestamp >= '2022-06-01 00:00:00.000' and block_timestamp < '2022-07-01 00:00:00.000' then 'June'

when block_timestamp >= '2022-07-01' then 'July'

end as time_category

from polygon.core.fact_transactions

where block_timestamp >= '2022-06-01 00:00:00.000'

group by block_day,time_category