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bifrost Summary (Daily)

Source: bifrost.polkaholic.io

Relay Chain: polkadot Para ID: 2030

Daily Summary for Month ending in 2023-11-30

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
2023-11-30 3,551,231 3,557,601 6,371 530 143 51 15 7,107 18,972 694 ($39,815.31) 46 ($57,054.00) 7 ($13,773.69) 103 93
2023-11-29 3,544,971 3,551,230 6,260 653 155 1,661 514 7,092 25,251 2,680 ($497,636.11) 62 ($226,407.39) 14 ($179,932.69) 136 118
2023-11-28 3,538,723 3,544,970 6,248 579 127 62 6,580 19,101 539 ($427,190.63) 48 ($150,851.82) 11 ($163,456.01) 114 87
2023-11-27 3,532,513 3,538,722 6,210 451 125 46 12 6,546 17,584 531 ($6,189.28) 38 ($49,070.58) 9 ($1,148.23) 93 60
2023-11-26 3,526,108 3,532,512 6,405 487 127 48 6,537 18,452 640 ($7,798.67) 42 ($30,334.47) 10 ($13,668.34) 87 75
2023-11-25 3,519,531 3,526,107 6,577 561 157 55 23 6,524 19,439 648 ($18,753.70) 41 ($48,284.35) 21 ($74,078.49) 79 84
2023-11-24 3,513,029 3,519,530 6,502 634 159 49 6,501 19,732 715 ($7,019.81) 36 ($1,867,425.26) 18 ($51,447.93) 124 186
2023-11-23 3,506,338 3,513,028 6,691 738 169 193 20 6,489 22,357 1,090 ($63,468.37) 55 ($63,263.02) 22 ($70,544.95) 128 119
2023-11-22 3,499,597 3,506,337 6,741 634 154 57 19 6,470 20,792 766 ($11,486.49) 58 ($66,803.29) 10 ($1,758.26) 92 81
2023-11-21 3,493,469 3,499,596 6,128 734 145 54 17 6,452 21,029 982 ($32,177.86) 66 ($85,796.78) 14 ($19,904.01) 152 115
2023-11-20 3,487,297 3,493,468 6,172 634 139 61 18 6,436 19,586 654 ($28,683.77) 59 ($95,470.77) 17 ($8,155.58) 120 101
2023-11-19 3,480,961 3,487,296 6,336 616 149 90 19 6,418 21,005 891 ($203,445.70) 124 ($586,340.31) 37 ($62,142.53) 224 165
2023-11-18 3,474,637 3,480,960 6,324 564 128 54 11 6,401 19,528 677 ($81,110.84) 77 ($202,632.35) 8 ($3,626.61) 132 85
2023-11-17 3,468,375 3,474,636 6,262 828 169 50 13 6,390 21,725 986 ($14,123.55) 72 ($313,043.10) 11 ($3,646.77) 108 95
2023-11-16 3,462,062 3,468,374 6,313 683 158 41 6,377 20,790 814 ($14,830.61) 74 ($334,660.50) 24 ($221,692.86) 151 106
2023-11-15 3,455,872 3,462,061 6,190 632 162 61 23 6,356 20,565 822 ($9,222.81) 85 ($190,043.58) 34 ($71,069.08) 220 125
2023-11-14 3,449,663 3,455,871 6,209 723 148 62 20 6,333 21,229 920 ($15,924.94) 78 ($79,688.45) 18 ($6,641.19) 211 148
2023-11-13 3,443,507 3,449,662 6,156 600 158 60 17 6,313 19,800 917 ($11,003.17) 83 ($105,707.00) 6 ($1,299.41) 297 194
2023-11-12 3,437,326 3,443,506 6,181 699 176 45 26 6,296 20,865 1,035 ($17,600.08) 91 ($277,573.92) 6 ($3,884.26) 163 119
2023-11-11 3,431,016 3,437,325 6,310 697 189 56 9 6,272 20,804 904 ($11,611.53) 97 ($1,141,457.39) 6 ($13,363.33) 175 133
2023-11-10 3,424,660 3,431,015 6,356 710 177 49 16 6,266 20,919 806 ($23,509.96) 85 ($372,107.50) 11 ($2,496.04) 150 100
2023-11-09 3,418,391 3,424,659 6,269 760 185 52 25 6,252 21,289 864 ($18,104.31) 106 ($127,842.89) 15 ($10,451.18) 200 125
2023-11-08 3,412,075 3,418,390 6,316 710 176 51 33 6,227 20,806 826 ($17,238.00) 95 ($93,840.53) 20 ($10,530.52) 146 94
2023-11-07 3,405,549 3,412,074 6,526 719 195 51 28 6,194 21,331 911 ($41,319.64) 89 ($74,751.89) 9 ($10,006.92) 172 96
2023-11-06 3,399,069 3,405,548 6,480 683 164 45 25 6,166 20,775 673 ($55,313.48) 84 ($70,958.16) 10 ($19,173.92) 161 102
2023-11-05 3,392,707 3,399,068 6,362 784 178 59 29 6,141 21,548 884 ($20,267.47) 83 ($201,949.15) 15 ($17,357.17) 120 92
2023-11-04 3,386,333 3,392,706 6,374 702 166 51 22 6,116 20,795 729 ($23,606.79) 93 ($226,512.79) 14 ($28,213.88) 149 104
2023-11-03 3,379,950 3,386,332 6,383 965 187 51 19 6,095 23,107 964 ($16,425.29) 98 ($126,231.65) 10 ($5,572.68) 185 129
2023-11-02 3,373,652 3,379,949 6,298 2,048 207 70 28 6,077 29,625 1,036 ($24,943.18) 95 ($574,507.43) 16 ($14,145.13) 158 98
2023-11-01 3,367,289 3,373,651 6,363 681 171 62 22 6,050 20,804 979 ($26,253.98) 94 ($135,266.57) 9 ($12,400.21) 179 130

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)) = "2023-11-30" 
 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)) = "2023-11-30" 
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)) = "2023-11-30" 
 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)) = "2023-11-30" 
 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)) = "2023-11-30" 
 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)) = "2023-11-30" 
 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)) = "2023-11-30" 
 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)) = "2023-11-30" 
 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)) = "2023-11-30" 
 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)) = "2023-11-30" 
 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)) = "2023-11-30" 
 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)) = "2023-11-30" 
 group by logDT 
order by logDT

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