DATE | TX_CATEGORY | UNIQUE_ADDRESSES | TOTAL_DAILY_ACTIVE_ADDRESSES | PERCENTAGE_OF_DAILY_TOTAL | |
|---|---|---|---|---|---|
1 | 2025-04-24 00:00:00.000 | Single TX | 221 | 431 | 51.28 |
2 | 2025-04-24 00:00:00.000 | 2-5 TXs | 139 | 431 | 32.25 |
3 | 2025-04-24 00:00:00.000 | 6-10 TXs | 23 | 431 | 5.34 |
4 | 2025-04-24 00:00:00.000 | 11-20 TXs | 15 | 431 | 3.48 |
5 | 2025-04-24 00:00:00.000 | 20+ TXs | 33 | 431 | 7.66 |
6 | 2025-04-23 00:00:00.000 | Single TX | 194 | 408 | 47.55 |
7 | 2025-04-23 00:00:00.000 | 2-5 TXs | 145 | 408 | 35.54 |
8 | 2025-04-23 00:00:00.000 | 6-10 TXs | 25 | 408 | 6.13 |
9 | 2025-04-23 00:00:00.000 | 11-20 TXs | 16 | 408 | 3.92 |
10 | 2025-04-23 00:00:00.000 | 20+ TXs | 28 | 408 | 6.86 |
11 | 2025-04-22 00:00:00.000 | Single TX | 290 | 536 | 54.1 |
12 | 2025-04-22 00:00:00.000 | 2-5 TXs | 158 | 536 | 29.48 |
13 | 2025-04-22 00:00:00.000 | 6-10 TXs | 35 | 536 | 6.53 |
14 | 2025-04-22 00:00:00.000 | 11-20 TXs | 26 | 536 | 4.85 |
15 | 2025-04-22 00:00:00.000 | 20+ TXs | 27 | 536 | 5.04 |
16 | 2025-04-21 00:00:00.000 | Single TX | 184 | 330 | 55.76 |
17 | 2025-04-21 00:00:00.000 | 2-5 TXs | 93 | 330 | 28.18 |
18 | 2025-04-21 00:00:00.000 | 6-10 TXs | 19 | 330 | 5.76 |
19 | 2025-04-21 00:00:00.000 | 11-20 TXs | 9 | 330 | 2.73 |
20 | 2025-04-21 00:00:00.000 | 20+ TXs | 25 | 330 | 7.58 |
Abbas_ra21Daily Active addresses breakdown by TX Count
Updated 21 hours ago
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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: about 21 hours ago
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