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bifrost Summary (Daily)

Source: bifrost.polkaholic.io

Relay Chain: polkadot Para ID: 2030

Daily Summary for Month ending in 2023-12-31

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
2023-12-31 3,751,433 3,758,523 7,091 401 30,495 19,002 517 ($79,671.73) 35 ($245,284.99) 14 ($60,382.15) 110 106
2023-12-30 3,744,306 3,751,432 7,127 429 30,482 19,474 502 ($86,020.94) 46 ($62,411.76) 15 ($94,054.49) 115 115
2023-12-29 3,737,190 3,744,305 7,116 576 30,469 20,898 680 ($97,091.01) 56 ($79,647.88) 12 ($57,926.18) 120 120
2023-12-28 3,730,073 3,737,189 7,117 730 30,446 21,859 766 ($99,492.90) 43 ($35,153.10) 9 ($39,485.92) 99 131
2023-12-27 3,722,985 3,730,072 7,088 616,425 30,427 4,480,753 232,612 ($9,858.60) 489 ($558,984.11) 46 ($77,196.13) 710 276
2023-12-26 3,715,888 3,722,984 7,097 586,982 17,855 4,121,444 129,402 ($86,101.72) 280 ($384,581.93) 44 ($183,947.67) 517 198
2023-12-25 3,708,810 3,715,887 7,078 321,110 12,206 4,332,220 36,924 ($79,319.23) 198 ($36,100.31) 20 ($92,389.27) 369 164
2023-12-24 3,701,882 3,708,809 6,928 1,146 7,341 29,348 1,258 ($129,845.40) 61 ($217,125.49) 45 ($103,065.02) 201 253
2023-12-23 3,695,679 3,701,881 6,203 735 7,278 21,048 944 ($79,401.73) 36 ($3,152,245.74) 34 ($39,003.85) 113 103
2023-12-22 3,689,702 3,695,678 5,977 661 7,244 19,795 862 ($184,043.82) 48 ($81,244.54) 12 ($67,354.07) 94 53
2023-12-21 3,683,703 3,689,701 5,999 606 7,225 19,057 718 ($57,416.27) 41 ($87,694.25) 22 ($43,530.05) 45 46
2023-12-20 3,677,396 3,683,702 6,307 757 7,214 25,145 2,953 ($136,501.06) 71 ($149,268.24) 23 ($40,052.44) 106 126
2023-12-19 3,671,123 3,677,395 6,273 402 7,159 17,291 448 ($225,686.32) 43 ($151,153.49) 13 ($49,938.59) 96 90
2023-12-18 3,664,734 3,671,122 6,389 664 7,149 20,399 561 ($487,576.90) 52 ($137,706.02) 48 ($10,616.06) 194 214
2023-12-17 3,658,442 3,664,733 6,292 360 7,142 16,689 306 ($41,399.90) 37 ($25,022.06) 16 ($28,599.24) 93 95
2023-12-16 3,652,090 3,658,441 6,352 545 7,135 18,689 555 ($36,678.31) 33 ($6,506.74) 15 ($484,779.96) 93 141
2023-12-15 3,645,633 3,652,089 6,457 649 7,124 20,188 548 ($204,369.97) 33 ($586,592.67) 20 ($215,620.20) 155 161
2023-12-14 3,639,267 3,645,632 6,366 797 7,116 21,392 1,153 ($5,472.36) 29 ($6,225.85) 5 ($2,148.75) 93 115
2023-12-13 3,632,834 3,639,266 6,433 548 7,270 23,008 2,548 ($366,015.96) 55 ($134,112.45) 18 ($89,400.65) 133 131
2023-12-12 3,626,485 3,632,833 6,349 414 7,255 17,474 491 ($5,146.36) 36 ($13,600.59) 8 ($3,180.46) 89 66
2023-12-11 3,620,184 3,626,484 6,301 540 7,244 18,845 678 ($13,962.68) 53 ($43,648.97) 7 ($17,941.99) 117 105
2023-12-10 3,613,911 3,620,183 6,273 525 7,227 18,553 650 ($12,424.06) 56 ($28,464.23) 8 ($13,183.69) 94 73
2023-12-09 3,607,845 3,613,910 6,066 549 7,206 18,737 736 ($31,420.82) 61 ($39,650.13) 22 ($46,925.74) 133 121
2023-12-08 3,601,773 3,607,844 6,072 582 7,188 18,595 612 ($13,405.48) 44 ($44,520.06) 15 ($8,453.26) 107 106
2023-12-07 3,595,639 3,601,772 6,134 534 140 37 6 7,173 18,226 582 ($23,108.68) 41 ($24,117.60) 8 ($15,451.54) 106 118
2023-12-06 3,589,352 3,595,638 6,287 612 153 1,589 28 7,167 23,177 2,473 ($51,415.63) 40 ($22,712.19) 18 ($6,245.14) 116 91
2023-12-05 3,582,998 3,589,351 6,354 1,032 144 52 3 7,142 24,593 1,686 ($20,522.78) 40 ($37,314.25) 21 ($24,666.47) 90 111
2023-12-04 3,576,605 3,582,997 6,393 416 126 44 9 7,141 17,511 410 ($38,516.04) 39 ($96,211.05) 11 ($34,299.92) 90 86
2023-12-03 3,570,298 3,576,604 6,307 367 102 35 8 7,133 16,662 348 ($8,032.89) 27 ($6,311.78) 10 ($12,385.08) 47 49
2023-12-02 3,563,966 3,570,297 6,332 431 127 41 7,126 17,494 398 ($16,061.84) 42 ($112,643.41) 8 ($6,138.52) 88 92
2023-12-01 3,557,602 3,563,965 6,364 449 140 53 7,117 17,808 485 ($11,602.85) 40 ($134,857.62) 11 ($57,848.48) 82 78

Sample Queries:

You can generate the above summary data using the following queries using the public dataset bigquery-public-data.crypto_polkadot in Google BigQuery:

Blocks

Schema

SELECT date(block_time) as logDT, MIN(number) startBN, MAX(number) endBN, COUNT(*) numBlocks 
 FROM `bigquery-public-data.crypto_polkadot.blocks2030`  
 where LAST_DAY(date(block_time)) = "2023-12-31" 
 group by logDT 
 order by logDT

Signed Extrinsics

Schema

SELECT date(block_time) as logDT, 
COUNT(*) numSignedExtrinsics 
FROM `bigquery-public-data.crypto_polkadot.extrinsics2030`  
where signed and LAST_DAY(date(block_time)) = "2023-12-31" 
group by logDT 
order by logDT

Active Accounts

Schema

SELECT date(ts) as logDT, 
 COUNT(*) numActiveAccounts 
 FROM `bigquery-public-data.crypto_polkadot.accountsactive2030` 
 where LAST_DAY(date(ts)) = "2023-12-31" 
 group by logDT 
 order by logDT

Passive Accounts

Schema

SELECT date(ts) as logDT, 
 COUNT(*) numPassiveAccounts 
 FROM `bigquery-public-data.crypto_polkadot.accountspassive2030` 
 where LAST_DAY(date(ts)) = "2023-12-31" 
 group by logDT 
 order by logDT

New Accounts

Schema

SELECT date(ts) as logDT, 
 COUNT(*) numNewAccounts 
 FROM `bigquery-public-data.crypto_polkadot.accountsnew2030` 
 where LAST_DAY(date(ts)) = "2023-12-31" 
 group by logDT
 order by logDT

Addresses with Balances

Schema

SELECT date(ts) as logDT,
 COUNT(distinct address_pubkey) numAddress 
 FROM `bigquery-public-data.crypto_polkadot.balances2030` 
 where LAST_DAY(date(ts)) = "2023-12-31" 
 group by logDT 
 order by logDT

Events

Schema

SELECT date(block_time) as logDT, 
 COUNT(*) numEvents 
 FROM `bigquery-public-data.crypto_polkadot.events2030` 
 where LAST_DAY(date(block_time)) = "2023-12-31" 
 group by logDT 
 order by logDT

Transfers:

Schema

SELECT date(block_time) as logDT, 
 COUNT(*) numEvents 
 FROM `bigquery-public-data.crypto_polkadot.transfers2030` 
 where LAST_DAY(date(block_time)) = "2023-12-31" 
 group by logDT 
 order by logDT

XCM Transfers In:

Schema

SELECT date(origination_ts) as logDT, 
 COUNT(*) numXCMTransfersOut 
 FROM `bigquery-public-data.crypto_polkadot.xcmtransfers` 
 where destination_para_id = 2030 and LAST_DAY(date(origination_ts)) = "2023-12-31" 
 group by logDT order by logDT

XCM Transfers Out:

Schema

SELECT date(origination_ts) as logDT, 
 COUNT(*) numXCMTransfersIn 
 FROM `bigquery-public-data.crypto_polkadot.xcmtransfers` 
 where origination_para_id = 2030 and LAST_DAY(date(origination_ts)) = "2023-12-31" 
 group by logDT 
order by logDT

XCM Messages In:

Schema

SELECT date(origination_ts) as logDT, 
 COUNT(*) numXCMMessagesOut 
 FROM `bigquery-public-data.crypto_polkadot.xcm` 
 where destination_para_id = 2030 and LAST_DAY(date(origination_ts)) = "2023-12-31" 
 group by logDT order by logDT

XCM Messages Out:

Schema

SELECT date(origination_ts) as logDT, 
 COUNT(*) numXCMMessagesIn 
 FROM `bigquery-public-data.crypto_polkadot.xcm` 
 where origination_para_id = 2030 and LAST_DAY(date(origination_ts)) = "2023-12-31" 
 group by logDT 
order by logDT

Report source: https://cdn.polkaholic.io/substrate-etl/polkadot/2030.json | See Definitions for details