datavortexdaily purchases
    Updated 2025-02-27
    SELECT
    DATE_TRUNC('day', block_timestamp) AS date,
    COUNT(DISTINCT tx_hash) AS "total purchases",
    COUNT(DISTINCT from_address) AS "purchasers",
    SUM(VALUE) AS "total Wklay",
    SUM(tx_fee) AS "total Purchase Fees(kaia)"
    FROM
    kaia.core.fact_transactions
    WHERE
    to_address = '0x703e56244b73427fe1fea3374e296606ca64096b'
    AND block_timestamp >= '2025-01-28'
    GROUP BY
    DATE_TRUNC('day', block_timestamp)
    ORDER BY
    date;

    Last run: 2 months ago
    DATE
    total purchases
    purchasers
    total Wklay
    total Purchase Fees(kaia)
    1
    2025-01-28 00:00:00.0005739497996554.986819.662816673
    2
    2025-01-29 00:00:00.000121098653201928.346641.444775973
    3
    2025-01-30 00:00:00.0001806913095215901.0927561.784954547
    4
    2025-01-31 00:00:00.0002034817117204288.950269.682978418
    5
    2025-02-01 00:00:00.0002066019779178339.869870.711007315
    6
    2025-02-02 00:00:00.00099839070150704.200434.202577138
    7
    2025-02-03 00:00:00.0002505424264122602.4111008889.269483308
    8
    2025-02-04 00:00:00.0005404952857196702.0037184.989201486
    9
    2025-02-05 00:00:00.0005743356003207619.8666196.925536846
    10
    2025-02-06 00:00:00.0001918116581695.55166.572724692
    11
    2025-02-07 00:00:00.00010003198834361524.7153340.81365815
    12
    2025-02-08 00:00:00.0002766126804155235.177795.471557816
    13
    2025-02-09 00:00:00.0003162530885195147.5166106.245010656
    14
    2025-02-10 00:00:00.0002520924499141077.469884.164327576
    15
    2025-02-11 00:00:00.0003966135807758269.492986124128.981644347
    16
    2025-02-12 00:00:00.0001662715830179199.4354.906193668
    17
    2025-02-13 00:00:00.00031742704144315.638910.876249693
    18
    2025-02-14 00:00:00.0002021419627243964.416166.236623761
    19
    2025-02-15 00:00:00.00058475188257969.135720.047847941
    20
    2025-02-16 00:00:00.00071016106340113.12524.367980534
    31
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