Madibuyers/sellers ratio by period
Updated 2022-10-29
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with azuki as (
select BLOCK_TIMESTAMP, SELLER_ADDRESS, BUYER_ADDRESS
from ethereum.core.ez_nft_sales
where EVENT_TYPE = 'sale' and date_trunc('day',BLOCK_TIMESTAMP) <= '2022-03-12' and (CURRENCY_SYMBOL = 'ETH' or CURRENCY_SYMBOL = 'WETH' ) and (NFT_ADDRESS = lower('0xED5AF388653567Af2F388E6224dC7C4b3241C544')) and PRICE >0),
Doodles as (
select BLOCK_TIMESTAMP, SELLER_ADDRESS, BUYER_ADDRESS
from ethereum.core.ez_nft_sales
where EVENT_TYPE = 'sale' and date_trunc('day',BLOCK_TIMESTAMP) <= '2021-12-15' and (CURRENCY_SYMBOL = 'ETH' or CURRENCY_SYMBOL = 'WETH' ) and (NFT_ADDRESS = lower('0x8a90cab2b38dba80c64b7734e58ee1db38b8992e')) and PRICE >0),
goblin as (
select BLOCK_TIMESTAMP, SELLER_ADDRESS, BUYER_ADDRESS
from ethereum.core.ez_nft_sales
where EVENT_TYPE = 'sale' and date_trunc('day',BLOCK_TIMESTAMP) <= '2022-07-19' and (CURRENCY_SYMBOL = 'ETH' or CURRENCY_SYMBOL = 'WETH' ) and (NFT_ADDRESS = lower('0xbCe3781ae7Ca1a5e050Bd9C4c77369867eBc307e')) and PRICE >0),
df1 as (SELECT CASE WHEN contract_address = '0x8d0501d85becda92b89e56177ddfcea5fc1f0af2' then 'The Senses'
end as collection, *
from polygon.core.fact_event_logs
WHERE EVENT_REMOVED = 'false' and TX_STATUS = 'SUCCESS' and contract_address = '0x8d0501d85becda92b89e56177ddfcea5fc1f0af2' and date_trunc('day', BLOCK_TIMESTAMP) >= '2022-08-19'
),
df as (
SELECT a.BLOCK_TIMESTAMP, c.FROM_ADDRESS as FROM_ADDRESS, c.TO_ADDRESS as buyers
from df1 a join polygon.core.fact_token_transfers c on a.BLOCK_TIMESTAMP = c.BLOCK_TIMESTAMP),
datafr as (
SELECT date_trunc('day',BLOCK_TIMESTAMP) as date, ROW_NUMBER() OVER(ORDER BY date_trunc('day',BLOCK_TIMESTAMP) asc) AS Number_of_the_day,
'Azuki' as Collection, count (DISTINCT BUYER_ADDRESS) / count (DISTINCT SELLER_ADDRESS) as buyers_purch_ratio
from azuki group by date
UNION ALL
SELECT date_trunc('day',BLOCK_TIMESTAMP) as date, ROW_NUMBER() OVER(ORDER BY date_trunc('day',BLOCK_TIMESTAMP) asc) AS Number_of_the_day,
'Doodles' as Collection, count (DISTINCT BUYER_ADDRESS) / count (DISTINCT SELLER_ADDRESS) as buyers_purch_ratio
from Doodles group by date
Run a query to Download Data