Source: polkadot.polkaholic.io
Relay Chain: polkadot Para ID: 0
Date | Start Block | End Block | # Blocks | # Extrinsics | # Active Accounts | # Passive Accounts | # New Accounts | # Addresses | # Events | # Transfers ($USD) | # XCM Transfers In ($USD) | # XCM Transfers Out ($USD) | # XCM In | # XCM Out | Issues |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
2022-03-31 | 9,661,927 | 9,676,319 | 14,393 | 10,669 | 5,155 | 945,779 | 288,801 | 9,518 ($252,532,505.00) | |||||||
2022-03-30 | 9,647,551 | 9,661,926 | 14,376 | 10,051 | 5,063 | 944,723 | 282,501 | 8,785 ($213,383,877.76) | |||||||
2022-03-29 | 9,633,151 | 9,647,550 | 14,400 | 10,629 | 5,387 | 943,954 | 286,582 | 9,325 ($480,217,832.19) | |||||||
2022-03-28 | 9,618,753 | 9,633,150 | 14,398 | 12,063 | 6,100 | 942,969 | 297,496 | 10,512 ($405,019,592.93) | |||||||
2022-03-27 | 9,604,368 | 9,618,752 | 14,385 | 8,978 | 4,572 | 941,950 | 275,304 | 7,721 ($72,834,645.09) | |||||||
2022-03-26 | 9,590,072 | 9,604,367 | 14,296 | 8,181 | 4,144 | 941,046 | 265,743 | 6,905 ($58,527,386.44) | |||||||
2022-03-25 | 9,575,680 | 9,590,071 | 14,392 | 9,403 | 4,708 | 940,398 | 275,460 | 8,320 ($143,893,705.25) | |||||||
2022-03-24 | 9,561,606 | 9,575,679 | 14,074 | 10,136 | 5,036 | 939,500 | 271,557 | 8,901 ($275,741,456.35) | |||||||
2022-03-23 | 9,547,503 | 9,561,605 | 14,103 | 9,827 | 4,720 | 938,535 | 278,635 | 8,472 ($135,907,542.46) | |||||||
2022-03-22 | 9,533,117 | 9,547,502 | 14,386 | 10,065 | 5,102 | 937,745 | 281,534 | 8,892 ($118,856,916.61) | |||||||
2022-03-21 | 9,518,718 | 9,533,116 | 14,399 | 8,371 | 4,178 | 936,866 | 270,573 | 7,211 ($82,055,730.04) | |||||||
2022-03-20 | 9,504,319 | 9,518,717 | 14,399 | 8,716 | 4,001 | 936,096 | 272,658 | 7,684 ($59,689,419.31) | |||||||
2022-03-19 | 9,489,920 | 9,504,318 | 14,399 | 9,318 | 4,374 | 935,234 | 270,221 | 8,251 ($67,042,261.28) | |||||||
2022-03-18 | 9,475,521 | 9,489,919 | 14,399 | 9,497 | 4,765 | 934,368 | 285,784 | 8,722 ($59,707,370.47) | |||||||
2022-03-17 | 9,461,122 | 9,475,520 | 14,399 | 9,913 | 4,942 | 933,730 | 287,856 | 8,814 ($81,197,548.22) | |||||||
2022-03-16 | 9,446,725 | 9,461,121 | 14,397 | 10,533 | 5,168 | 932,892 | 295,574 | 9,596 ($87,604,293.48) | |||||||
2022-03-15 | 9,432,325 | 9,446,724 | 14,400 | 10,445 | 5,238 | 932,151 | 292,829 | 9,254 ($82,962,996.19) | |||||||
2022-03-14 | 9,417,928 | 9,432,324 | 14,397 | 12,050 | 5,682 | 931,246 | 311,856 | 14,892 ($138,404,525.38) | |||||||
2022-03-13 | 9,403,547 | 9,417,927 | 14,381 | 8,787 | 4,211 | 930,147 | 281,525 | 8,725 ($132,780,634.35) | |||||||
2022-03-12 | 9,389,164 | 9,403,546 | 14,383 | 9,742 | 5,052 | 928,999 | 283,807 | 19,345 ($179,415,987.80) | |||||||
2022-03-11 | 9,374,767 | 9,389,163 | 14,397 | 9,935 | 4,938 | 926,793 | 216,531 | 9,129 ($88,545,560.46) | |||||||
2022-03-10 | 9,360,368 | 9,374,766 | 14,399 | 10,675 | 5,514 | 925,659 | 224,880 | 8,660 ($53,584,948.81) | |||||||
2022-03-09 | 9,345,989 | 9,360,367 | 14,379 | 11,731 | 5,838 | 924,413 | 240,560 | 11,057 ($68,377,762.91) | |||||||
2022-03-08 | 9,331,649 | 9,345,988 | 14,340 | 10,246 | 5,055 | 922,849 | 224,963 | 9,671 ($157,469,346.54) | |||||||
2022-03-07 | 9,317,288 | 9,331,648 | 14,361 | 9,753 | 4,757 | 921,535 | 222,768 | 9,403 ($82,440,339.48) | |||||||
2022-03-06 | 9,302,920 | 9,317,287 | 14,368 | 9,328 | 4,562 | 920,242 | 220,760 | 8,798 ($214,155,115.95) | |||||||
2022-03-05 | 9,288,529 | 9,302,919 | 14,391 | 9,593 | 4,464 | 919,178 | 223,835 | 9,366 ($144,976,035.94) | |||||||
2022-03-04 | 9,274,132 | 9,288,528 | 14,397 | 10,415 | 4,760 | 917,793 | 226,232 | 10,241 ($187,286,365.60) | 1 | ||||||
2022-03-03 | 9,259,758 | 9,274,131 | 14,374 | 11,578 | 5,591 | 916,300 | 240,542 | 11,734 ($193,762,198.18) | |||||||
2022-03-02 | 9,245,361 | 9,259,757 | 14,397 | 12,646 | 6,156 | 914,398 | 241,063 | 12,494 ($91,215,580.95) | |||||||
2022-03-01 | 9,230,963 | 9,245,360 | 14,398 | 12,444 | 5,608 | 912,632 | 245,121 | 12,269 ($226,388,919.78) |
You can generate the above summary data using the following queries using the public dataset bigquery-public-data.crypto_polkadot
in Google BigQuery:
SELECT date(block_time) as logDT, MIN(number) startBN, MAX(number) endBN, COUNT(*) numBlocks
FROM `bigquery-public-data.crypto_polkadot.blocks0`
where LAST_DAY(date(block_time)) = "2022-03-31"
group by logDT
order by logDT
SELECT date(block_time) as logDT,
COUNT(*) numSignedExtrinsics
FROM `bigquery-public-data.crypto_polkadot.extrinsics0`
where signed and LAST_DAY(date(block_time)) = "2022-03-31"
group by logDT
order by logDT
SELECT date(ts) as logDT,
COUNT(*) numActiveAccounts
FROM `bigquery-public-data.crypto_polkadot.accountsactive0`
where LAST_DAY(date(ts)) = "2022-03-31"
group by logDT
order by logDT
SELECT date(ts) as logDT,
COUNT(*) numPassiveAccounts
FROM `bigquery-public-data.crypto_polkadot.accountspassive0`
where LAST_DAY(date(ts)) = "2022-03-31"
group by logDT
order by logDT
SELECT date(ts) as logDT,
COUNT(*) numNewAccounts
FROM `bigquery-public-data.crypto_polkadot.accountsnew0`
where LAST_DAY(date(ts)) = "2022-03-31"
group by logDT
order by logDT
SELECT date(ts) as logDT,
COUNT(distinct address_pubkey) numAddress
FROM `bigquery-public-data.crypto_polkadot.balances0`
where LAST_DAY(date(ts)) = "2022-03-31"
group by logDT
order by logDT
SELECT date(block_time) as logDT,
COUNT(*) numEvents
FROM `bigquery-public-data.crypto_polkadot.events0`
where LAST_DAY(date(block_time)) = "2022-03-31"
group by logDT
order by logDT
SELECT date(block_time) as logDT,
COUNT(*) numEvents
FROM `bigquery-public-data.crypto_polkadot.transfers0`
where LAST_DAY(date(block_time)) = "2022-03-31"
group by logDT
order by logDT
SELECT date(origination_ts) as logDT,
COUNT(*) numXCMTransfersOut
FROM `bigquery-public-data.crypto_polkadot.xcmtransfers`
where destination_para_id = 0 and LAST_DAY(date(origination_ts)) = "2022-03-31"
group by logDT order by logDT
SELECT date(origination_ts) as logDT,
COUNT(*) numXCMTransfersIn
FROM `bigquery-public-data.crypto_polkadot.xcmtransfers`
where origination_para_id = 0 and LAST_DAY(date(origination_ts)) = "2022-03-31"
group by logDT
order by logDT
SELECT date(origination_ts) as logDT,
COUNT(*) numXCMMessagesOut
FROM `bigquery-public-data.crypto_polkadot.xcm`
where destination_para_id = 0 and LAST_DAY(date(origination_ts)) = "2022-03-31"
group by logDT order by logDT
SELECT date(origination_ts) as logDT,
COUNT(*) numXCMMessagesIn
FROM `bigquery-public-data.crypto_polkadot.xcm`
where origination_para_id = 0 and LAST_DAY(date(origination_ts)) = "2022-03-31"
group by logDT
order by logDT
Report source: https://cdn.polkaholic.io/substrate-etl/polkadot/0.json | See Definitions for details