DIS | USER_COUNT | USER_COUNT_PERCENTAGE | |
|---|---|---|---|
1 | B. 2-3 | 55665 | 14.586079 |
2 | D. 8-15 | 25197 | 6.602451 |
3 | A. 1 | 149357 | 39.136496 |
4 | H. 128-255 | 13998 | 3.667941 |
5 | E. 16-31 | 17880 | 4.685154 |
6 | C. 4-7 | 36139 | 9.469619 |
7 | I. 256-511 | 15559 | 4.076975 |
8 | F. 32-63 | 14874 | 3.897482 |
9 | J. more than 512 | 39363 | 10.314414 |
10 | G. 64-127 | 13599 | 3.56339 |
elsinaDistribution of User Transactions
Updated 2025-02-23
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with per_user as (
SELECT
origin_from_address as user,
count(distinct tx_hash) as tx_count
from
kaia.core.fact_event_logs
where
contract_address in ('0x84f8c3c8d6ee30a559d73ec570d574f671e82647', '0x990d8cfbce8892e2126f85637f3728b53266b45e', '0x63d4f17d2a8a729fd050f7679d961b1dfbb1e3af',
'0x6b684816884def88cbc72e1bfa47242ff27fd0de', '0x9bcb2efc545f89986cf70d3adc39079a1b730d63', '0x8da74ba3db7b440264421373d2cbfca2b10e2e3b', '0x26e7e1f2351a39c3b718512bb4480aa6892bef9b',
'0x976232eb7eb92287ff06c5d145bd0d1c033eca58', '0xa9dc3a0a9b0fd00f5572996cfb1fac79a78eb9f1', '0xaeb0c547c3175aed37f67f4565a5064ee48b8cae', '0xb97c9b2a4ea46672f46e05740621a12c7928d73e',
'0xe777abd2594c81149d1b0dd35203ccbafaa234fd', '0x2e5be2ad0473ec82fd66f2f476a510c9f3962583', '0x144Fa704D6d7A12950AC4EaD5C48cB5D5e79cD14', '0x52678aeff4b82b0b167ca3e37c272f574ca9fde0',
'0x9d0c0675a995d5F12b03E880763F639d0628b5C6', '0x3b58a4C865B568a2F6a957C264F6b50CbA35D8CE', '0x0A6cE134Bcb399D0F7a25D2d776fFbed4557c7AF', '0xabbF528374c9f431dFd45E25c01490389Ff8fd6a',
'0x1a818d53ecdcdb9a3af102a9df4436122b9a643c', '0x8D967653D64Ad05c57927995866DCB45399210aA', '0x13AF3A8f1428dDC20be8Bd47821F69779e24F80c')
group by
user
)
select
case
when tx_count < 2 then 'A. 1'
when tx_count < 4 then 'B. 2-3'
when tx_count < 8 then 'C. 4-7'
when tx_count < 16 then 'D. 8-15'
when tx_count < 32 then 'E. 16-31'
when tx_count < 64 then 'F. 32-63'
when tx_count < 128 then 'G. 64-127'
when tx_count < 256 then 'H. 128-255'
when tx_count < 512 then 'I. 256-511'
else 'J. more than 512' end as dis,
count(distinct user) as user_count,
100.0 * count(distinct user) / sum(count(distinct user)) over () as user_count_percentage
from per_user
group by 1
Last run: about 2 months ago
10
288B
23s