DATE | TX_CATEGORY | UNIQUE_ADDRESSES | TOTAL_DAILY_ACTIVE_ADDRESSES | PERCENTAGE_OF_DAILY_TOTAL | |
|---|---|---|---|---|---|
1 | 2025-05-10 00:00:00.000 | Single TX | 204 | 433 | 47.11 |
2 | 2025-05-10 00:00:00.000 | 2-5 TXs | 144 | 433 | 33.26 |
3 | 2025-05-10 00:00:00.000 | 6-10 TXs | 35 | 433 | 8.08 |
4 | 2025-05-10 00:00:00.000 | 11-20 TXs | 17 | 433 | 3.93 |
5 | 2025-05-10 00:00:00.000 | 20+ TXs | 33 | 433 | 7.62 |
6 | 2025-05-09 00:00:00.000 | Single TX | 215 | 464 | 46.34 |
7 | 2025-05-09 00:00:00.000 | 2-5 TXs | 168 | 464 | 36.21 |
8 | 2025-05-09 00:00:00.000 | 6-10 TXs | 30 | 464 | 6.47 |
9 | 2025-05-09 00:00:00.000 | 11-20 TXs | 18 | 464 | 3.88 |
10 | 2025-05-09 00:00:00.000 | 20+ TXs | 33 | 464 | 7.11 |
11 | 2025-05-08 00:00:00.000 | Single TX | 165 | 429 | 38.46 |
12 | 2025-05-08 00:00:00.000 | 2-5 TXs | 161 | 429 | 37.53 |
13 | 2025-05-08 00:00:00.000 | 6-10 TXs | 41 | 429 | 9.56 |
14 | 2025-05-08 00:00:00.000 | 11-20 TXs | 27 | 429 | 6.29 |
15 | 2025-05-08 00:00:00.000 | 20+ TXs | 35 | 429 | 8.16 |
16 | 2025-05-07 00:00:00.000 | Single TX | 226 | 470 | 48.09 |
17 | 2025-05-07 00:00:00.000 | 2-5 TXs | 146 | 470 | 31.06 |
18 | 2025-05-07 00:00:00.000 | 6-10 TXs | 22 | 470 | 4.68 |
19 | 2025-05-07 00:00:00.000 | 11-20 TXs | 26 | 470 | 5.53 |
20 | 2025-05-07 00:00:00.000 | 20+ TXs | 50 | 470 | 10.64 |
Abbas_ra21Daily Active addresses breakdown by TX Count
Updated 2025-05-11
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WITH daily_tx_counts AS (
SELECT
DATE_TRUNC('day', block_timestamp) as date,
from_address as address,
COUNT(*) as daily_tx_count
FROM swell.core.fact_transactions where date < current_date
GROUP BY 1, 2
),
categorized_addresses AS (
SELECT
date,
CASE
WHEN daily_tx_count = 1 THEN 'Single TX'
WHEN daily_tx_count BETWEEN 2 AND 5 THEN '2-5 TXs'
WHEN daily_tx_count BETWEEN 6 AND 10 THEN '6-10 TXs'
WHEN daily_tx_count BETWEEN 11 AND 20 THEN '11-20 TXs'
ELSE '20+ TXs'
END as tx_category,
COUNT(DISTINCT address) as unique_addresses
FROM daily_tx_counts
GROUP BY 1, 2
)
SELECT
date,
tx_category,
unique_addresses,
SUM(unique_addresses) OVER (PARTITION BY date) as total_daily_active_addresses,
ROUND(unique_addresses * 100.0 / SUM(unique_addresses) OVER (PARTITION BY date), 2) as percentage_of_daily_total
FROM categorized_addresses
ORDER BY date DESC,
CASE tx_category
WHEN 'Single TX' THEN 1
WHEN '2-5 TXs' THEN 2
WHEN '6-10 TXs' THEN 3
WHEN '11-20 TXs' THEN 4
Last run: 13 days ago
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