DATE | TRANSACTIONS | BUYERS | SELLERS | VOLUME_NEAR | AVERAGE_VOLUME_NEAR | MEDIAN_VOLUME_NEAR | VOLUME_USD | AVERAGE_VOLUME_USD | MEDIAN_VOLUME_USD | NEW_BUYERS | RETURNING_BUYERS | CUMULATIVE_TRANSACTIONS | CUMULATIVE_VOLUME_NEAR | CUMULATIVE_VOLUME_USD | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
1 | 2022-09-01 00:00:00.000 | 19 | 11 | 8 | 114.8 | 6.042105263 | 6 | 419.966208431 | 22.103484654 | 21.410558086 | 11 | 0 | 19 | 114.8 | 419.966208431 |
2 | 2022-10-01 00:00:00.000 | 33 | 21 | 19 | 471.323 | 14.282515152 | 12 | 1498.512451228 | 45.409468219 | 36.228887002 | 17 | 4 | 52 | 586.123 | 1918.478659659 |
3 | 2022-11-01 00:00:00.000 | 41 | 26 | 15 | 705.48 | 17.206829268 | 6 | 1559.482885176 | 38.036167931 | 18.722444342 | 24 | 2 | 93 | 1291.603 | 3477.961544835 |
4 | 2022-12-01 00:00:00.000 | 77 | 23 | 27 | 1130.73 | 14.684805195 | 4.3 | 1708.699384203 | 22.190901094 | 7.315376198 | 13 | 10 | 170 | 2422.333 | 5186.660929038 |
5 | 2023-01-01 00:00:00.000 | 60 | 30 | 26 | 785.16 | 13.086 | 5.9 | 1649.756804094 | 27.495946735 | 10.905670559 | 24 | 6 | 230 | 3207.493 | 6836.417733131 |
6 | 2023-02-01 00:00:00.000 | 102 | 45 | 43 | 1323.25 | 12.973039216 | 7.25 | 3323.934393132 | 32.58759209 | 18.148356327 | 30 | 15 | 332 | 4530.743 | 10160.352126263 |
7 | 2023-03-01 00:00:00.000 | 392 | 80 | 186 | 2199.160998998 | 5.610104589 | 3 | 4310.829576881 | 10.997014227 | 5.810714496 | 64 | 16 | 724 | 6729.903998998 | 14471.181703144 |
8 | 2023-04-01 00:00:00.000 | 138 | 59 | 64 | 1371.2909 | 9.93689058 | 5.25 | 2817.083695496 | 20.413649967 | 10.248281787 | 42 | 17 | 862 | 8101.194898998 | 17288.26539864 |
9 | 2023-05-01 00:00:00.000 | 82 | 36 | 32 | 886.6233 | 10.812479268 | 4.5 | 1557.445480461 | 18.993237567 | 7.81148687 | 23 | 13 | 944 | 8987.818198998 | 18845.710879101 |
10 | 2023-06-01 00:00:00.000 | 53 | 28 | 23 | 562.61062209 | 10.615294756 | 4.8 | 786.512827441 | 14.839864669 | 6.771366128 | 15 | 13 | 997 | 9550.428821088 | 19632.223706542 |
11 | 2023-07-01 00:00:00.000 | 71 | 39 | 25 | 1778.9113 | 25.055088732 | 14.99 | 2476.872378988 | 34.885526465 | 23.741954615 | 27 | 12 | 1068 | 11329.340121088 | 22109.09608553 |
12 | 2023-08-01 00:00:00.000 | 89 | 38 | 30 | 972.313 | 10.924865169 | 3 | 1218.794552181 | 13.694320811 | 4.00926725 | 18 | 20 | 1157 | 12301.653121088 | 23327.890637712 |
13 | 2023-09-01 00:00:00.000 | 42 | 24 | 21 | 621.11 | 14.788333333 | 7.5 | 688.367885415 | 16.389711558 | 8.206525321 | 11 | 13 | 1199 | 12922.763121088 | 24016.258523127 |
14 | 2023-10-01 00:00:00.000 | 41 | 17 | 20 | 477.435 | 11.644756098 | 5 | 547.144352401 | 13.344984205 | 5.066492271 | 6 | 11 | 1240 | 13400.198121088 | 24563.402875528 |
15 | 2023-11-01 00:00:00.000 | 84 | 35 | 30 | 830.058 | 9.881642857 | 3 | 1415.181697385 | 16.847401159 | 5.450146361 | 16 | 19 | 1324 | 14230.256121088 | 25978.584572913 |
16 | 2023-12-01 00:00:00.000 | 512 | 101 | 97 | 6862.6591 | 13.403631055 | 3 | 19329.296304968 | 37.752531846 | 8.414810661 | 70 | 31 | 1836 | 21092.915221088 | 45307.880877881 |
17 | 2024-01-01 00:00:00.000 | 146 | 48 | 47 | 1762.318999999 | 12.070678082 | 4.55 | 5667.07681515 | 38.815594624 | 14.079694765 | 27 | 21 | 1982 | 22855.234221087 | 50974.957693031 |
18 | 2024-02-01 00:00:00.000 | 184 | 97 | 91 | 8841.4114 | 48.051148913 | 3.66 | 28822.685626134 | 156.645030577 | 11.471919766 | 84 | 13 | 2166 | 31696.645621087 | 79797.643319164 |
19 | 2024-03-01 00:00:00.000 | 164 | 80 | 80 | 2771.094 | 16.896914634 | 4.325 | 17842.19130228 | 108.793849404 | 31.294758517 | 58 | 22 | 2330 | 34467.739621087 | 97639.834621445 |
20 | 2024-04-01 00:00:00.000 | 1008 | 379 | 612 | 4127.851151 | 4.095090428 | 0.3 | 25536.177176178 | 25.333509103 | 1.764602181 | 354 | 25 | 3338 | 38595.590772087 | 123176.011797623 |
Afonso_DiazOvertime
Updated 9 days ago
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with
main as (
select
tx_hash,
block_timestamp,
buyer_address,
seller_address,
price,
price_usd,
nft_address,
token_id
from near.nft.ez_nft_sales
where
platform_name = 'TradePort'
),
new_buyers as (
select
date_trunc('{{ period }}', min_date) as date,
count(distinct buyer_address) as new_buyer
from (
select
buyer_address,
min(block_timestamp) as min_date
from
main
group by 1
)
group by 1
),
overtime as (
select
date_trunc('{{ period }}', block_timestamp) as date,
count(distinct tx_hash) as transactions,
Last run: 9 days ago
32
5KB
5s