JeffersSold prices over time
    Updated 2025-03-23
    with tx_hashes as
    (
    select
    distinct m.tx_hash
    from monad.testnet.fact_event_logs m
    join monad.testnet.fact_transactions t
    on m.tx_hash = t.tx_hash
    -- join private_mint pm
    -- on m.origin_from_address = pm.mint_address
    where (m.contract_address = '0xe8f0635591190fb626f9d13c49b60626561ed145'
    or (m.contract_address = '0x760afe86e5de5fa0ee542fc7b7b713e1c5425701' and m.origin_to_address = '0x224ecb4eae96d31372d1090c3b0233c8310dbbab'))
    and m.block_timestamp >= '2025-02-19 16:00:00'
    and t.tx_succeeded = TRUE
    ),

    transfers as
    (
    select
    m.block_timestamp,
    m.tx_hash,
    m.contract_address AS nft_contract,
    m.origin_from_address,
    m.origin_to_address,
    m.topic_0,
    m.topic_1,
    m.topic_2,
    CASE
    when topic_3 = NULL
    then 0
    else TO_NUMERIC(utils.udf_hex_to_int(topic_3)) -- convert tokenid to numeric
    END as token_id,
    CASE
    when m.contract_address = '0x760afe86e5de5fa0ee542fc7b7b713e1c5425701'
    then TO_NUMERIC(utils.udf_hex_to_int(REPLACE(m.data, '0x0000000000000000000000000000000000000000000000', ''))) / POWER(10,18) -- make the hex WMON value numeric
    else 0
    END as data_converted,
    Last run: about 1 month ago
    ADJUSTED_TIMESTAMP
    TX_HASH
    TOKEN_ID
    FINAL_PRICE
    1
    2025-03-12 12:18:47.0000xe4cf0a3e96c97a73a4b5b5116b3e9bc17045fb781f82c88d9961672f69d048d54562828
    2
    2025-03-03 17:38:13.0000x8bdd0e39df7179a1f0d7e8daa69d2febd2ecdd06a353c1b5479c71bccbc0d563602097
    3
    2025-02-20 19:59:48.0000xe7dd3b39b0e09e8d6fd544ba80c19df4d888d8512949c08dd7eaf690707bea3b2771000
    4
    2025-02-20 19:59:48.0010xe7dd3b39b0e09e8d6fd544ba80c19df4d888d8512949c08dd7eaf690707bea3b2881000
    5
    2025-02-20 18:33:12.0000xd5cf699dd26f62a46a758e2e79f44a89c1ce59b9c981228d7e632745463949f6477888
    6
    2025-02-21 11:34:20.0000x5393d5dd5c818ce4aa82b176e90059170e65e39950a9ccef4b06fe180a49998c1561999
    7
    2025-02-26 02:33:14.0000x8ed97799d01b7c061d5706809460e7398bf9126805c095e4ea7bca5af32abaaf3802900
    8
    2025-02-20 18:41:05.0000x602c62a6ae35d39b10be4c0d8902aa00b5b90cf2685b5bf609e14c400bc26a601451000
    9
    2025-03-04 02:08:31.0000xa7f9c3a9914c8ac189d7e7a0f5240826e8a570e38f8362c9f4553ac300f80c0c4461542
    10
    2025-03-02 05:38:18.0000x3af73b9c312efaa4e8d3226450db82d2673868d367e14698d3a6e6c75e997aa14002299
    11
    2025-02-28 04:25:32.0000xb02961196217c750a60709d39eab6bbcbcd58a032a8ecca92a10547756609ec83052200
    12
    2025-02-22 21:03:16.0000xc8df24132d629b99ac30d0e1bf3b8ff9ebcfcc842cba88a7636fcbf4135524de4477700
    13
    2025-03-08 11:47:18.0000x53f7df43503b9c894b08d62686bee1bdc604463a1ed8aafa82bc73db7bda1d3f3682550
    14
    2025-02-20 18:27:14.0000xbac83c7659628dfb7ac1bff5f9622d9f4ff4e16091b39cfa292a72e00e9262e44331080
    15
    2025-02-28 15:19:08.0000xf122c128696b9e9dc514b919f1e389d6e224e5f3683fdfd15f5a683b9363417e712999
    16
    2025-03-04 19:21:24.0000xc8b54088e7eb6b8bdbf05d02dcb875f375c187e9489bf91b4a32012ca244387c2682250
    17
    2025-03-11 12:52:33.0000xedb79d65935530d4b4022b10d561b457faf9debe8c0f4649ac1b45793811d25c3121500
    18
    2025-03-03 08:11:39.0000xce9ac79089314e509a02e4052193e2affe3d93219d8a3148b066d307a14a27c83181735
    19
    2025-02-20 21:29:09.0000x4a5417419232fbe36435b09c8f0f73c3082b05db9d9ab55653491a67e54a886f681614
    20
    2025-02-20 21:29:09.0010x4a5417419232fbe36435b09c8f0f73c3082b05db9d9ab55653491a67e54a886f3081614
    ...
    411
    43KB
    54s