I'd like to see this graph overlaid with a bitcoin price chart--I'm not a statistics geek and am not really interested in member activity, posts, registration, and so on, but it's interesting to me that it looks like activity and registration of new accounts booms and busts along with how bitcoin is performing. That's probably obvious to a lot of members, but I don't think I've ever seen any statistical correlation between btc price and bitcointalk variables.
You can see more details at my another thread: Assumed monthly statistics on registered accounts of bitcointalk.org (2009-2019)Plots are not overlaid because I don't remember where I stored data for those plots hence I can not re-draw them now. From two plots, you can see unconfirmed correlation between forum members' activities and BTC price. Remember there are bias factors: merit system's kick-off and the demotion on Jr. member -- they are likely random shocks but effects are systematic. To support this assumption, you can see plots for forum ads' statistics (at end of this post), there are visual correlations sure. That one is an overlaid plot but for 2019 only. Regarding to forum members' activities, there is Time Series on monthly statistics of forum (new users, new topics, new posts)Next few weeks, I will spend a little time each day to see how I can do with all collective data, to have such same plots in Impression counts for ads over years
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Now I am finding this more interesting. A private msg can actually help in making more enquiries rather than asking a public message when it not required
Some members have restrictions on PM from newbies so if you don't have troubles to ask publicly, don't go with PMs. They choose the restriction because some of newbies are scammers and they send multiple annoying PMs to older members just to try their advertisements or try to scam as many victims as possible. Profile > Personal Message Options > Allow newbies to send you PMs. (you can check your profile too).
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I've been working on this for almost a month but first I'm trying to scrape users based from different countries by their local board posts, by simply going to a local board and scrape every comments in every thread and in every page (this is really hard). I hope I could patent this idea so my work and time spent studying scraping wouldn't be wasted. After that, I think it would be easy if I had stats with the links of local users and simply scrape when they are active (but would take me another month studying another prog language I guess).
I appreciated your time to learn and your plan to build up a project. Honestly, I don't know how to scrape website's data.
Quality is better than quantity. Figures on active or inactive members do not reflect the real situation on the forum, such as the average quality of posts or threads created by members recently. Imagine that an active local board can be detected by higher number of posts in latest few weeks compare to the other local boards. But such figures can not make sure the quality of that active local board that is probably a spam place. More active more spam endemic inside. A wider view, the forum used to be more actively in the past, late of 2017 and early of 2018, but now we have a very better forum (less spam, higher quality).
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And make sure you use multiple source to prevent bias or fake information, i've seen many people only rely from 1 source and turned out the source is biased on specific topic.
"Buy the rumours, sell the news" that is a classic rule but in reality unfortunately most of investors do the opposite thing. They buy the news and sell the rumours. To gather news (both real and fake ones) then filter them and get only real news to use is not an easy task for newbies. Most of newbies sell the rumours because at beginnings they don't afford to lose with their decision, they only think of profits and don't have a preventive plan. FOMO to buy at peaks. Fear of losses and get out at bottoms. Both types of investments/ tradings have same ending, losses.
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Here you go: All average statistics have been on declining trends. Forum statistics (on daily basis) - Observed period: 01/7/2020 - 05/8/2020.
- new members, new posts, new topics.
- a_rpd: Average registration per day
- a_opd: Average online per day
- a_ppd: Average posts per day
- n_mem: Daily new members
- n_posts: Daily new posts
- n_topics: Daily new topics
Time series plots +--------------------------------------------------------------------+ | date n_mem n_topics n_posts a_rpd a_opd a_ppd | |--------------------------------------------------------------------| 1. | 01jul2020 . . . 368.34 155.51 6762.03 | 2. | 02jul2020 333 184 5551 368.25 155.47 6760.29 | 3. | 03jul2020 393 164 5523 368.15 155.43 6758.55 | 4. | 04jul2020 421 178 5532 368.06 155.39 6756.81 | 5. | 05jul2020 335 135 5091 367.96 155.35 6755.07 | |--------------------------------------------------------------------| 6. | 06jul2020 316 85 5585 367.87 155.31 6753.33 | 7. | 07jul2020 501 148 5300 367.77 155.27 6751.59 | 8. | 08jul2020 391 172 6368 367.68 155.23 6749.85 | 9. | 09jul2020 361 202 6724 367.58 155.19 6748.12 | 10. | 10jul2020 418 133 6448 367.49 155.15 6746.38 | |--------------------------------------------------------------------| 11. | 11jul2020 417 82 6455 367.39 155.11 6744.65 | 12. | 12jul2020 361 123 6025 367.3 155.07 6742.91 | 13. | 13jul2020 277 111 6377 367.2 155.03 6741.18 | 14. | 14jul2020 369 166 6615 367.11 154.99 6739.45 | 15. | 15jul2020 404 154 7369 367.02 154.95 6737.72 | |--------------------------------------------------------------------| 16. | 16jul2020 437 158 7049 366.92 154.91 6735.99 | 17. | 17jul2020 398 176 6929 366.83 154.87 6734.26 | 18. | 18jul2020 398 136 6500 366.73 154.83 6732.53 | 19. | 19jul2020 351 96 6228 366.64 154.79 6730.8 | 20. | 20jul2020 471 151 7534 366.55 154.75 6729.07 | |--------------------------------------------------------------------| 21. | 21jul2020 384 153 6698 366.45 154.71 6727.35 | 22. | 22jul2020 399 155 6870 366.36 154.67 6725.62 | 23. | 23jul2020 376 176 6511 366.26 154.63 6723.9 | 24. | 24jul2020 345 100 6567 366.17 154.59 6722.17 | 25. | 25jul2020 372 166 6532 366.08 154.55 6720.45 | |--------------------------------------------------------------------| 26. | 26jul2020 312 130 6262 365.98 154.51 6718.73 | 27. | 27jul2020 286 145 6948 365.89 154.47 6717.01 | 28. | 28jul2020 388 59 6536 365.79 154.39 6715.29 | 29. | 29jul2020 382 175 6773 365.7 154.39 6713.57 | 30. | 30jul2020 391 171 6403 365.61 154.35 6711.85 | |--------------------------------------------------------------------| 31. | 31jul2020 402 196 6175 365.51 154.31 6710.14 | 32. | 01aug2020 401 69 6810 365.42 154.27 6708.42 | 33. | 02aug2020 320 135 5925 365.33 154.23 6706.71 | 34. | 03aug2020 325 132 6523 365.23 154.2 6704.99 | 35. | 04aug2020 355 118 6000 365.14 154.16 6703.28 | |--------------------------------------------------------------------| 36. | 05aug2020 422 141 6316 365.05 154.12 6701.57 | +--------------------------------------------------------------------+
With multipliers (figures at the end are multipliers)
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I can see that a lot of posts suggesting new rules for the campaign are coming from those who are not participants and want to join the campaign. The manager has been here for long time and I'm very certain he knows how to improve and get the best out of the campaign. Repeated suggestion of already considered ideas are not necessary. If he sees anything to work on. I'm sure he will do it. Repeated suggestion is also part of spamming
The forum is for free discussions so that if posts or suggestions are not off topic, they are safe from any reports and they won't be considered as spamming. If you or manager think that such posts are off topic, you or manager can report (or anyone else) those spam, off topic posts to moderators. Then moderators will delete it or global moderator will posts in particular discussion to a new thread, in Reputation sub board.You are still in the campaign so try your best to keep your position. Follow the guides and requirements of manager and make your best posts then if anything comes you won't regret (I should try better, don't regret this way). I was in Bustadice before I joined BestChange and I got that bonus quite often often, and I admit it was a nice thing to see your name among those 4 that shared 100 USD (rule says up to 5 but in reality its always 4). But as you said, BestChange has much bigger number of participants (58 compared to 16 in Bustadice), so it wouldn't be an easy thing to do, to choose few winners each week. It would take a lot of extra effort.
Having bonuses weekly for most merit earners will cause a headache for manager, obviously. If I am a manager, I won't go with the idea, especially like you said there are many participants in the campaign. The earned merits itself can not reflect the truly quality of a poster, there are many bias factors that manager has to take into consideration - that is one of headache type. Another one is complaint from other top merit earners. It is something like an endless headache story. Merit are subjective like the rule on 5+ paged threads: It is not always true that posts are made in 10+paged thread have lower quality than posts are made in less than 5 paged threads. Not always like that but the point is the potential of exposures. Quality is key, but then locations are next secondary key factor (in which threads, and in which boards / sub boards).
You see, there are a few former participants of Chip Mixer. As you thought, by default they will easily get positions here and stay here forever. But life changes so fast and not smoothly this way. In reality they get positions but lost it because of changes in manager approach. Being a good poster is not enough, it also depends on both company and management strategies within each period as well as the growth speed of other competitors.
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Add a BBCode for your colors so that if someone want to use it they can easily know which BBCode to use. With your table, it is a challenge to find color codes to reproduce it for my tables. I guess your purpose when creating the thread is provide an easy tool with available color codes for visitors and if it is you have not build it up well enough. One more point, I don't think the color name is necessary, just show the color, and if people like it they will pick it (its code) to use. It saves more space for your table as well. In case you want to allocate each row in the table for a wide range of an initial color, example: green, dark green, lightgreen, limegreen, whatever, you can do it with the second table I gave you. Cheers. | | | | | | | | | | | | | | | | | | | | | | | | Color name | | | Color display | | | BBcode | | | | | Special purple | | | ▀▀▀▀▀▀▀▀▀▀▀▀▀▀▀▀▀▀▀ | | | #b19cd9 | | |
| | | | | | | | | | | | | | | | | | | | | | | | Color | | | BBcode | | | Color | | | BBcode | | | Color | | | BBcode | | | Color | | | BBcode | | | | | ▀▀▀▀▀▀▀ | | | #b19cd9 | | | ▀▀▀▀▀▀▀ | | | #b78c5f | | | ▀▀▀▀▀▀▀ | | | #a8eb12 | | | ▀▀▀▀▀▀▀ | | | #ffd77d | | |
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Statistics Bitcointalk.org [1] which used the statistics on BPIP.org. With support from LoyceV and data on loyce.club, I observed following daily statistics: - Total Members
- Total Posts
- Total Topics
- Average online per day
The observed period is a bit more than one month so I have not yet published it. Because of your request, I will show a time series plot for you later today (not have connection to dataset now). Of course, all of statistics do not satisfy your request completely. According to [1], there is a 3.6% drop in total active profiles between two months (July compares to June). . di (92373-95788)/95788*100 -3.5651647
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Let's start off by the term Newbies. - Who are newbies on the forum?
- Are all forum newbies are actually newbies in crypto space?
[1]: Who creates account and gets only one activity point or post a lot but has not yet receive a single merit. They are newbies on the forum, from the criteria of rank. That's it. [2]: Not all of them are actually newbies in crypto. Some of them are experts, tech gurus and they have a title (rank) newbie because of their limited time participated and contributed on the forum. - Scam accusation, as its name discloses clearly, is just a sub board for scam fightings and proofs of scam projects.
- Beginners & Help serves a bigger role: for more general and systematic guides on how to classify projects, detect scam ones, and avoid scam promotions, KYC-data stolen from scammers, etc.
My question to all of you after reading your replies: - Why will a begginer always want to read about a scam and not the benefits he can achieve being here?
- Did anyone here create a topic about benefits of cryptocurrency? or we assumed they know about it?
- We assumed they do not know about Scams or we are creating topics for Merits?
1. Think of losses and prevent losses before thinking of profits. So yeah such threads are do helpful (some are extremely helpful). 2. There are around the forum. No need to ask so, mate. 3. Why did you think others create threads only because of merits?
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Don't trust, do your own research and verify info you have. - Influencers can be good guys or bad guys. Don't trust anything they tell you. Moreover, even good influencers can be wrong from their own research and analyses so be careful when putting your financial freedom to someone else.
- The rule can be expanded to softwares (wallets, ie.), investment plans / recommendations, and so forth.
- After verifying their words and check legitimacy of projects, you have to jump directly to ToS (Terms of conditions or Terms of Service) and FAQs to read most basic, and vital things on those platforms. See if their terms are fitted with your need, and you can satisfy their requirements (your nation is not in their list of restricted areas, ie.), let's go ahead. If not, stop at it and wait for other chances.
Listen/ Read > Research/ Investigate / Analysis > Read ToS/ FAQ > Make a decision **: Don't put all of your capital into anything because of influencers' recommendations.
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even though there are thousands of miners around the world, they are going into "groups" to share the work so each "group" ends up working on the same block and then share the reward. these "groups" are the mining pools and there are about 20 of them. so the competition is actually between these pools and the reward goes to the pool which then it spreads among the individual miners depending on how much work they contributed to.
There are many mining pools throughout history of Bitcoin and the top-10 mining pools change each year. These are charts from 3/1/2009 to 9/5/2020. Because of that, biggest pools have also found most of empty blocks on the network, 1.9% for AntPool and 1.1% for F2Pool in the same period above. For more details at:
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Follow the guide to report the fake app on Google Play to Google. Of course, it is Google fault but we should do and contribute something to protect crypto newbies. Google do their works not good enough to prevent fake apps appear on their store. I don't know with their superb power engines why they can not detect later born apps that have names contains some words of initial apps. It is not a big challenge for them. https://support.google.com/googleplay/answer/2853570
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ABSTRACT 2020w30, GMT timeData is the full dataset since 24/1/2018, and only dropped last 3 days belong to incomplete week - 2020w31 and an incomplete day (dayid = 920). Details on days dropped, please see above posts. Intra-day merits:- Total observed days: 917
- Potential outliers are days that have intraday total merits beyond 198 or 1178
- Median of intraday merits over the period is 671
- 50% of observed days have their intra-day merits range from 565 to 810 (the interquartile range)
- In medians, the highest and lowest days are Thursday and Saturday, respectively; whilst the highest and lowest days in means are Thursday and Sunday, respectively. See here.
- There are 62 potential outliers (beyond 198 or 1178) in total.
- The distribution of outliers over years are: 44 (71.0%) for 2018, 14 (22.6%) for 2019, and 4 (6.4%) for 2020. (see details)
- Minimum and maximum of intraday merits (full dataset) are 300, and 12676, on 04/8/2019 and 25/1/2018, respectively.
Intra-week merits:- Total observed weeks: 131
- The median of intra-week merits is 4650
- 50% of observed weeks (131 weeks in total), have total merits in the range 4259 to 5596 (the interquartile range of intra-week merits).
- Minimum and maximum of intra-week merits are 3186 and 27920, in 2018w35, and 2018w4, respectively;
- 9 potential outliers [beyond 2254 or 7602], only 2 of them occurred in the year 2019, on 2019w46 (11070), and 2019w47 (20397); none of them occured in 2020.
- The last week with 4518 merits has its position at 76th among 131 weeks so far.
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Intra-week merits (from 24/1/2018 to 28/7/2020)Last 3 days dropped due to incomplete week (2020w31) and an incomplete day (dayid = 920)Converted dataset: +-----------------+ | merit week | |-----------------| 1. | 27920 2018w4 | 2. | 20930 2018w5 | 3. | 14042 2018w6 | 4. | 11901 2018w7 | 5. | 8879 2018w8 | |-----------------| 6. | 9005 2018w9 | 7. | 7178 2018w10 | 8. | 7340 2018w11 | 9. | 7138 2018w12 | 10. | 6392 2018w13 | |-----------------| 11. | 6542 2018w14 | 12. | 5946 2018w15 | 13. | 4449 2018w16 | 14. | 4820 2018w17 | 15. | 5043 2018w18 | |-----------------| 16. | 4685 2018w19 | 17. | 4431 2018w20 | 18. | 3903 2018w21 | 19. | 4248 2018w22 | 20. | 4473 2018w23 | |-----------------| 21. | 3953 2018w24 | 22. | 4574 2018w25 | 23. | 4684 2018w26 | 24. | 4367 2018w27 | 25. | 4109 2018w28 | |-----------------| 26. | 4277 2018w29 | 27. | 3809 2018w30 | 28. | 3489 2018w31 | 29. | 4199 2018w32 | 30. | 3767 2018w33 | |-----------------| 31. | 3763 2018w34 | 32. | 3186 2018w35 | 33. | 3536 2018w36 | 34. | 3586 2018w37 | 35. | 9587 2018w38 | |-----------------| 36. | 4508 2018w39 | 37. | 4325 2018w40 | 38. | 3981 2018w41 | 39. | 4424 2018w42 | 40. | 4386 2018w43 | |-----------------| 41. | 3321 2018w44 | 42. | 4175 2018w45 | 43. | 4047 2018w46 | 44. | 4606 2018w47 | 45. | 3791 2018w48 | |-----------------| 46. | 3596 2018w49 | 47. | 3689 2018w50 | 48. | 3615 2018w51 | 49. | 3687 2018w52 | 50. | 4584 2019w1 | |-----------------| 51. | 6102 2019w2 | 52. | 5776 2019w3 | 53. | 4582 2019w4 | 54. | 4408 2019w5 | 55. | 4505 2019w6 | |-----------------| 56. | 4259 2019w7 | 57. | 4314 2019w8 | 58. | 4726 2019w9 | 59. | 4979 2019w10 | 60. | 4295 2019w11 | |-----------------| 61. | 4690 2019w12 | 62. | 5728 2019w13 | 63. | 4695 2019w14 | 64. | 5253 2019w15 | 65. | 4880 2019w16 | |-----------------| 66. | 4260 2019w17 | 67. | 4817 2019w18 | 68. | 5002 2019w19 | 69. | 5596 2019w20 | 70. | 4693 2019w21 | |-----------------| 71. | 4342 2019w22 | 72. | 4597 2019w23 | 73. | 5373 2019w24 | 74. | 4629 2019w25 | 75. | 4672 2019w26 | |-----------------| 76. | 3882 2019w27 | 77. | 4462 2019w28 | 78. | 4005 2019w29 | 79. | 4377 2019w30 | 80. | 3603 2019w31 | |-----------------| 81. | 3346 2019w32 | 82. | 3965 2019w33 | 83. | 3811 2019w34 | 84. | 3579 2019w35 | 85. | 3683 2019w36 | |-----------------| 86. | 4005 2019w37 | 87. | 4382 2019w38 | 88. | 4348 2019w39 | 89. | 4209 2019w40 | 90. | 4701 2019w41 | |-----------------| 91. | 5160 2019w42 | 92. | 5375 2019w43 | 93. | 4816 2019w44 | 94. | 4753 2019w45 | 95. | 11070 2019w46 | |-----------------| 96. | 20397 2019w47 | 97. | 6271 2019w48 | 98. | 4650 2019w49 | 99. | 4832 2019w50 | 100. | 6066 2019w51 | |-----------------| 101. | 7058 2019w52 | 102. | 5745 2020w1 | 103. | 5395 2020w2 | 104. | 7247 2020w3 | 105. | 6646 2020w4 | |-----------------| 106. | 6756 2020w5 | 107. | 5573 2020w6 | 108. | 6923 2020w7 | 109. | 6314 2020w8 | 110. | 5237 2020w9 | |-----------------| 111. | 4622 2020w10 | 112. | 5109 2020w11 | 113. | 5603 2020w12 | 114. | 5392 2020w13 | 115. | 6061 2020w14 | |-----------------| 116. | 5094 2020w15 | 117. | 5052 2020w16 | 118. | 4539 2020w17 | 119. | 5699 2020w18 | 120. | 5648 2020w19 | |-----------------| 121. | 5802 2020w20 | 122. | 5334 2020w21 | 123. | 4662 2020w22 | 124. | 4676 2020w23 | 125. | 4190 2020w24 | |-----------------| 126. | 4366 2020w25 | 127. | 4474 2020w26 | 128. | 4630 2020w27 | 129. | 4673 2020w28 | 130. | 4485 2020w29 | |-----------------| 131. | 4518 2020w30 | +-----------------+
Time series plotBasic statistics:- 50% of observed weeks ( 131 weeks) have total intra-week merits above 4650, whilst the rest 50% of them have total intra-week merits below 4650. 4650 is the median - p50. - 50% of observed weeks have total intra-week merits fluctuated in the range from 4259 to 5596 (the interquartile range, from p25 to p75, in raw statistics below). - Min - max: 3186 - 27920. variable | N mean sd p50 p25 p75 min max -------------+-------------------------------------------------------------------------------- merit | 131.0 5475.8 3181.2 4650.0 4259.0 5596.0 3186.0 27920.0 ----------------------------------------------------------------------------------------------
Potential outliers:. di 5596-4259 1337
. di 1337*1.5 2005.5
. di 5596+2005.5 7601.5
. di 4259-2005.5 2253.5
It means that potential outliers are weeks that have intra-week merits beyond 2254 or 7602. How many weeks are potential outliers? . count if (merit >= 7602 | merit < 2254) & merit != . 9
9 weeks are outliers, in total. List of those 9 weeks: +-----------------+ | merit week | |-----------------| 1. | 27920 2018w4 | 2. | 20930 2018w5 | 3. | 14042 2018w6 | 4. | 11901 2018w7 | 5. | 8879 2018w8 | |-----------------| 6. | 9005 2018w9 | 35. | 9587 2018w38 | 95. | 11070 2019w46 | 96. | 20397 2019w47 | +-----------------+
Most of them occured in the year 2018, and there is only 2 outliers week occured in 2019, in 2019w46 (11070), 2019w47 (20397). None of them occured in 2020 so far. List of weeks in descending weekly meritsThe last week (with 4518 merits) stays at the 76th position, among 131 weeks. +------------------------------+ | weeklyrank merit week | |------------------------------| 1. | 1 27920 2018w4 | 2. | 2 20930 2018w5 | 3. | 3 20397 2019w47 | 4. | 4 14042 2018w6 | 5. | 5 11901 2018w7 | |------------------------------| 6. | 6 11070 2019w46 | 7. | 7 9587 2018w38 | 8. | 8 9005 2018w9 | 9. | 9 8879 2018w8 | 10. | 10 7340 2018w11 | |------------------------------| 11. | 11 7247 2020w3 | 12. | 12 7178 2018w10 | 13. | 13 7138 2018w12 | 14. | 14 7058 2019w52 | 15. | 15 6923 2020w7 | |------------------------------| 16. | 16 6756 2020w5 | 17. | 17 6646 2020w4 | 18. | 18 6542 2018w14 | 19. | 19 6392 2018w13 | 20. | 20 6314 2020w8 | |------------------------------| 21. | 21 6271 2019w48 | 22. | 22 6102 2019w2 | 23. | 23 6066 2019w51 | 24. | 24 6061 2020w14 | 25. | 25 5946 2018w15 | |------------------------------| 26. | 26 5802 2020w20 | 27. | 27 5776 2019w3 | 28. | 28 5745 2020w1 | 29. | 29 5728 2019w13 | 30. | 30 5699 2020w18 | |------------------------------| 31. | 31 5648 2020w19 | 32. | 32 5603 2020w12 | 33. | 33 5596 2019w20 | 34. | 34 5573 2020w6 | 35. | 35 5395 2020w2 | |------------------------------| 36. | 36 5392 2020w13 | 37. | 37 5375 2019w43 | 38. | 38 5373 2019w24 | 39. | 39 5334 2020w21 | 40. | 40 5253 2019w15 | |------------------------------| 41. | 41 5237 2020w9 | 42. | 42 5160 2019w42 | 43. | 43 5109 2020w11 | 44. | 44 5094 2020w15 | 45. | 45 5052 2020w16 | |------------------------------| 46. | 46 5043 2018w18 | 47. | 47 5002 2019w19 | 48. | 48 4979 2019w10 | 49. | 49 4880 2019w16 | 50. | 50 4832 2019w50 | |------------------------------| 51. | 51 4820 2018w17 | 52. | 52 4817 2019w18 | 53. | 53 4816 2019w44 | 54. | 54 4753 2019w45 | 55. | 55 4726 2019w9 | |------------------------------| 56. | 56 4701 2019w41 | 57. | 57 4695 2019w14 | 58. | 58 4693 2019w21 | 59. | 59 4690 2019w12 | 60. | 60 4685 2018w19 | |------------------------------| 61. | 61 4684 2018w26 | 62. | 62 4676 2020w23 | 63. | 63 4673 2020w28 | 64. | 64 4672 2019w26 | 65. | 65 4662 2020w22 | |------------------------------| 66. | 66 4650 2019w49 | 67. | 67 4630 2020w27 | 68. | 68 4629 2019w25 | 69. | 69 4622 2020w10 | 70. | 70 4606 2018w47 | |------------------------------| 71. | 71 4597 2019w23 | 72. | 72 4584 2019w1 | 73. | 73 4582 2019w4 | 74. | 74 4574 2018w25 | 75. | 75 4539 2020w17 | |------------------------------| 76. | 76 4518 2020w30 | 77. | 77 4508 2018w39 | 78. | 78 4505 2019w6 | 79. | 79 4485 2020w29 | 80. | 80 4474 2020w26 | |------------------------------| 81. | 81 4473 2018w23 | 82. | 82 4462 2019w28 | 83. | 83 4449 2018w16 | 84. | 84 4431 2018w20 | 85. | 85 4424 2018w42 | |------------------------------| 86. | 86 4408 2019w5 | 87. | 87 4386 2018w43 | 88. | 88 4382 2019w38 | 89. | 89 4377 2019w30 | 90. | 90 4367 2018w27 | |------------------------------| 91. | 91 4366 2020w25 | 92. | 92 4348 2019w39 | 93. | 93 4342 2019w22 | 94. | 94 4325 2018w40 | 95. | 95 4314 2019w8 | |------------------------------| 96. | 96 4295 2019w11 | 97. | 97 4277 2018w29 | 98. | 98 4260 2019w17 | 99. | 99 4259 2019w7 | 100. | 100 4248 2018w22 | |------------------------------| 101. | 101 4209 2019w40 | 102. | 102 4199 2018w32 | 103. | 103 4190 2020w24 | 104. | 104 4175 2018w45 | 105. | 105 4109 2018w28 | |------------------------------| 106. | 106 4047 2018w46 | 107. | 107 4005 2019w37 | 108. | 108 4005 2019w29 | 109. | 109 3981 2018w41 | 110. | 110 3965 2019w33 | |------------------------------| 111. | 111 3953 2018w24 | 112. | 112 3903 2018w21 | 113. | 113 3882 2019w27 | 114. | 114 3811 2019w34 | 115. | 115 3809 2018w30 | |------------------------------| 116. | 116 3791 2018w48 | 117. | 117 3767 2018w33 | 118. | 118 3763 2018w34 | 119. | 119 3689 2018w50 | 120. | 120 3687 2018w52 | |------------------------------| 121. | 121 3683 2019w36 | 122. | 122 3615 2018w51 | 123. | 123 3603 2019w31 | 124. | 124 3596 2018w49 | 125. | 125 3586 2018w37 | |------------------------------| 126. | 126 3579 2019w35 | 127. | 127 3536 2018w36 | 128. | 128 3489 2018w31 | 129. | 129 3346 2019w32 | 130. | 130 3321 2018w44 | |------------------------------| 131. | 131 3186 2018w35 | +------------------------------+
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Medians and means of intra-day merits over days of weeks GMT timeColors: - Green: highest.
- Red: Lowest.
- In median, the highest days are Thursday , Tuesday , and Friday at 704, 702, and 697, respectively; whislt the lowest days are Saturday, Sunday, and Monday at 608, 632, and 662, respectively. - In means, the highest days are Thursday, Friday, and Tuesday at 892, 840, and 799, respectively; whilst the lowest days are Sunday, Saturday, and Monday, at 694, 700, and 775, respectively. Basic statistics:Summary for variables: merit by categories of: dofw
dofw | N mean sd p50 p25 p75 min max ----------+-------------------------------------------------------------------------------- Sunday | 131.0 693.9 342.7 632.0 505.0 741.0 300.0 3240.0 Monday | 131.0 774.9 417.7 662.0 581.0 850.0 370.0 3343.0 Tuesday | 131.0 798.4 457.1 702.0 592.0 835.0 339.0 3826.0 Wednesday | 131.0 777.1 415.6 696.0 603.0 832.0 347.0 4103.0 Thursday | 131.0 891.8 1150.9 704.0 587.0 837.0 411.0 12676.0 Friday | 131.0 840.0 717.2 697.0 576.0 828.0 373.0 6348.0 Saturday | 131.0 699.7 445.1 608.0 503.0 741.0 375.0 4627.0 ----------+-------------------------------------------------------------------------------- Total | 917.0 782.3 623.7 671.0 565.0 810.0 300.0 12676.0 -------------------------------------------------------------------------------------------
Box plotsOutliers non-displayed. Details on ranks:In medians +----------------------------------------------------------------------+ | rankmedian dofw median mean p25 p75 min max | |----------------------------------------------------------------------| 1. | 1 Thursday 704 891.8244 587 837 411 12676 | 2. | 2 Tuesday 702 798.3664 592 835 339 3826 | 3. | 3 Friday 697 839.9771 576 828 373 6348 | 4. | 4 Wednesday 696 777.0992 603 832 347 4103 | 5. | 5 Monday 662 774.8931 581 850 370 3343 | |----------------------------------------------------------------------| 6. | 6 Sunday 632 693.916 505 741 300 3240 | 7. | 7 Saturday 608 699.7252 503 741 375 4627 | +----------------------------------------------------------------------+
In means +--------------------------------------------------------------------+ | rankmean dofw mean median p25 p75 min max | |--------------------------------------------------------------------| 1. | 1 Thursday 891.8244 704 587 837 411 12676 | 2. | 2 Friday 839.9771 697 576 828 373 6348 | 3. | 3 Tuesday 798.3664 702 592 835 339 3826 | 4. | 4 Wednesday 777.0992 696 603 832 347 4103 | 5. | 5 Monday 774.8931 662 581 850 370 3343 | |--------------------------------------------------------------------| 6. | 6 Saturday 699.7252 608 503 741 375 4627 | 7. | 7 Sunday 693.916 632 505 741 300 3240 | +--------------------------------------------------------------------+
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During the period from 24/1/2018 to 28/7/2020 (last 3 days dropped due to incomplete week, 2020w31 and an incomplete day - dayid = 920), the minimum and maximum of intra-day merit are 300 and 12676, on 04/8/2019 and 25/1/2018, respectively. List of the top 50-highest day in terms of intra-day merits: +-----------------------------------------------------------------------------+ | rank_max merit dayid date dofw week month year | |-----------------------------------------------------------------------------| 1. | 1 12676 2 25jan2018 Thursday 2018w4 2018m1 2018 | 2. | 2 6348 3 26jan2018 Friday 2018w4 2018m1 2018 | 3. | 3 5515 668 22nov2019 Friday 2019w47 2019m11 2019 | 4. | 4 4889 667 21nov2019 Thursday 2019w47 2019m11 2019 | 5. | 5 4627 4 27jan2018 Saturday 2018w4 2018m1 2018 | |-----------------------------------------------------------------------------| 6. | 6 4103 8 31jan2018 Wednesday 2018w5 2018m1 2018 | 7. | 7 3826 665 19nov2019 Tuesday 2019w47 2019m11 2019 | 8. | 8 3804 7 30jan2018 Tuesday 2018w5 2018m1 2018 | 9. | 9 3343 6 29jan2018 Monday 2018w5 2018m1 2018 | 10. | 10 3240 5 28jan2018 Sunday 2018w4 2018m1 2018 | |-----------------------------------------------------------------------------| 11. | 11 2797 23 15feb2018 Thursday 2018w7 2018m2 2018 | 12. | 12 2793 9 01feb2018 Thursday 2018w5 2018m2 2018 | 13. | 13 2783 664 18nov2019 Monday 2019w46 2019m11 2019 | 14. | 14 2621 10 02feb2018 Friday 2018w5 2018m2 2018 | 15. | 15 2584 666 20nov2019 Wednesday 2019w47 2019m11 2019 | |-----------------------------------------------------------------------------| 16. | 16 2553 237 17sep2018 Monday 2018w38 2018m9 2018 | 17. | 17 2476 11 03feb2018 Saturday 2018w5 2018m2 2018 | 18. | 18 2374 661 15nov2019 Friday 2019w46 2019m11 2019 | 19. | 19 2366 15 07feb2018 Wednesday 2018w6 2018m2 2018 | 20. | 20 2263 13 05feb2018 Monday 2018w6 2018m2 2018 | |-----------------------------------------------------------------------------| 21. | 21 2223 17 09feb2018 Friday 2018w6 2018m2 2018 | 22. | 22 2059 16 08feb2018 Thursday 2018w6 2018m2 2018 | 23. | 23 2004 14 06feb2018 Tuesday 2018w6 2018m2 2018 | 24. | 24 1807 238 18sep2018 Tuesday 2018w38 2018m9 2018 | 25. | 25 1793 19 11feb2018 Sunday 2018w6 2018m2 2018 | |-----------------------------------------------------------------------------| 26. | 26 1790 12 04feb2018 Sunday 2018w5 2018m2 2018 | 27. | 27 1740 24 16feb2018 Friday 2018w7 2018m2 2018 | 28. | 28 1727 39 03mar2018 Saturday 2018w9 2018m3 2018 | 29. | 29 1630 660 14nov2019 Thursday 2019w46 2019m11 2019 | 30. | 30 1590 669 23nov2019 Saturday 2019w47 2019m11 2019 | |-----------------------------------------------------------------------------| 31. | 31 1589 26 18feb2018 Sunday 2018w7 2018m2 2018 | 32. | 32 1585 662 16nov2019 Saturday 2019w46 2019m11 2019 | 33. | 33 1580 22 14feb2018 Wednesday 2018w7 2018m2 2018 | 34. | 34 1475 20 12feb2018 Monday 2018w7 2018m2 2018 | 35. | 35 1465 678 02dec2019 Monday 2019w48 2019m12 2019 | |-----------------------------------------------------------------------------| 36. | 36 1442 28 20feb2018 Tuesday 2018w8 2018m2 2018 | 37. | 37 1431 25 17feb2018 Saturday 2018w7 2018m2 2018 | 38. | 38 1414 35 27feb2018 Tuesday 2018w9 2018m2 2018 | 39. | 39 1390 57 21mar2018 Wednesday 2018w12 2018m3 2018 | 40. | 40 1377 663 17nov2019 Sunday 2019w46 2019m11 2019 | |-----------------------------------------------------------------------------| 41. | 41 1372 33 25feb2018 Sunday 2018w8 2018m2 2018 | 42. | 42 1364 755 17feb2020 Monday 2020w7 2020m2 2020 | 43. | 43 1347 239 19sep2018 Wednesday 2018w38 2018m9 2018 | 44. | 44 1345 38 02mar2018 Friday 2018w9 2018m3 2018 | 45. | 45 1334 18 10feb2018 Saturday 2018w6 2018m2 2018 | |-----------------------------------------------------------------------------| 46. | 46 1316 49 13mar2018 Tuesday 2018w11 2018m3 2018 | 47. | 47 1302 36 28feb2018 Wednesday 2018w9 2018m2 2018 | 48. | 48 1289 27 19feb2018 Monday 2018w8 2018m2 2018 | 49. | 49 1289 21 13feb2018 Tuesday 2018w7 2018m2 2018 | 50. | 50 1277 30 22feb2018 Thursday 2018w8 2018m2 2018 | +-----------------------------------------------------------------------------+
List of the top 50-lowest days in terms of intra-day merits: +-----------------------------------------------------------------------------+ | rank_min merit dayid date dofw week month year | |-----------------------------------------------------------------------------| 1. | 1 300 558 04aug2019 Sunday 2019w31 2019m8 2019 | 2. | 2 333 341 30dec2018 Sunday 2018w52 2018m12 2018 | 3. | 3 339 343 01jan2019 Tuesday 2019w1 2019m1 2019 | 4. | 4 347 330 19dec2018 Wednesday 2018w51 2018m12 2018 | 5. | 5 347 299 18nov2018 Sunday 2018w46 2018m11 2018 | |-----------------------------------------------------------------------------| 6. | 6 351 334 23dec2018 Sunday 2018w51 2018m12 2018 | 7. | 7 366 218 29aug2018 Wednesday 2018w35 2018m8 2018 | 8. | 8 367 565 11aug2019 Sunday 2019w32 2019m8 2019 | 9. | 9 370 223 03sep2018 Monday 2018w36 2018m9 2018 | 10. | 10 373 339 28dec2018 Friday 2018w52 2018m12 2018 | |-----------------------------------------------------------------------------| 11. | 11 375 340 29dec2018 Saturday 2018w52 2018m12 2018 | 12. | 12 377 600 15sep2019 Sunday 2019w37 2019m9 2019 | 13. | 13 378 567 13aug2019 Tuesday 2019w33 2019m8 2019 | 14. | 14 378 305 24nov2018 Saturday 2018w47 2018m11 2018 | 15. | 15 378 566 12aug2019 Monday 2019w32 2019m8 2019 | |-----------------------------------------------------------------------------| 16. | 16 380 192 03aug2018 Friday 2018w31 2018m8 2018 | 17. | 17 381 336 25dec2018 Tuesday 2018w52 2018m12 2018 | 18. | 18 385 215 26aug2018 Sunday 2018w34 2018m8 2018 | 19. | 19 385 327 16dec2018 Sunday 2018w50 2018m12 2018 | 20. | 20 391 221 01sep2018 Saturday 2018w35 2018m9 2018 | |-----------------------------------------------------------------------------| 21. | 21 394 188 30jul2018 Monday 2018w31 2018m7 2018 | 22. | 22 395 872 13jun2020 Saturday 2020w24 2020m6 2020 | 23. | 23 399 593 08sep2019 Sunday 2019w36 2019m9 2019 | 24. | 24 401 557 03aug2019 Saturday 2019w31 2019m8 2019 | 25. | 25 401 288 07nov2018 Wednesday 2018w45 2018m11 2018 | |-----------------------------------------------------------------------------| 26. | 26 402 263 13oct2018 Saturday 2018w41 2018m10 2018 | 27. | 27 404 229 09sep2018 Sunday 2018w36 2018m9 2018 | 28. | 28 406 277 27oct2018 Saturday 2018w43 2018m10 2018 | 29. | 29 408 530 07jul2019 Sunday 2019w27 2019m7 2019 | 30. | 30 409 123 26may2018 Saturday 2018w21 2018m5 2018 | |-----------------------------------------------------------------------------| 31. | 31 409 589 04sep2019 Wednesday 2019w36 2019m9 2019 | 32. | 32 410 279 29oct2018 Monday 2018w44 2018m10 2018 | 33. | 33 411 578 24aug2019 Saturday 2019w34 2019m8 2019 | 34. | 34 411 569 15aug2019 Thursday 2019w33 2019m8 2019 | 35. | 35 414 528 05jul2019 Friday 2019w27 2019m7 2019 | |-----------------------------------------------------------------------------| 36. | 36 421 193 04aug2018 Saturday 2018w31 2018m8 2018 | 37. | 37 425 588 03sep2019 Tuesday 2019w36 2019m9 2019 | 38. | 38 426 346 04jan2019 Friday 2019w1 2019m1 2019 | 39. | 39 426 230 10sep2018 Monday 2018w37 2018m9 2018 | 40. | 40 427 141 13jun2018 Wednesday 2018w24 2018m6 2018 | |-----------------------------------------------------------------------------| 41. | 41 430 207 18aug2018 Saturday 2018w33 2018m8 2018 | 42. | 42 432 587 02sep2019 Monday 2019w35 2019m9 2019 | 43. | 43 435 522 29jun2019 Saturday 2019w26 2019m6 2019 | 44. | 44 436 419 18mar2019 Monday 2019w11 2019m3 2019 | 45. | 45 439 880 21jun2020 Sunday 2020w25 2020m6 2020 | |-----------------------------------------------------------------------------| 46. | 46 440 265 15oct2018 Monday 2018w42 2018m10 2018 | 47. | 47 440 559 05aug2019 Monday 2019w31 2019m8 2019 | 48. | 48 440 585 31aug2019 Saturday 2019w35 2019m8 2019 | 49. | 49 441 319 08dec2018 Saturday 2018w49 2018m12 2018 | 50. | 50 441 404 03mar2019 Sunday 2019w9 2019m3 2019 | +-----------------------------------------------------------------------------+
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Time-series plots:Full dataset:Truncated dataset: Basic statistics (for full dataset): Only drop last 3 days that belong to the 2020w31 (daydi = 918, 919), the incomplete week & incomlete day (dayid = 920). variable | N mean sd p50 p25 p75 min max -------------+-------------------------------------------------------------------------------- merit | 917 782.2574 623.7105 671 565 810 300 12676 ----------------------------------------------------------------------------------------------
Applied formulas in previous weeks, potential outliers are days have intra-day merits beyond 198 or 1178. . di 810-565 245
. di 245*1.5 367.5
. di 810+367.5 1177.5
. di 565-367.5 197.5
There are 62 outliers (beyond 1178 or 198) in full dataset, in total. . count if (merit >= 1178 | merit <= 198) & merit != . 62
Those days are: +---------------------------+ | dayid merit date | |---------------------------| 2. | 2 12676 25jan2018 | 3. | 3 6348 26jan2018 | 4. | 4 4627 27jan2018 | 5. | 5 3240 28jan2018 | 6. | 6 3343 29jan2018 | 7. | 7 3804 30jan2018 | 8. | 8 4103 31jan2018 | 9. | 9 2793 01feb2018 | 10. | 10 2621 02feb2018 | 11. | 11 2476 03feb2018 | 12. | 12 1790 04feb2018 | 13. | 13 2263 05feb2018 | 14. | 14 2004 06feb2018 | 15. | 15 2366 07feb2018 | 16. | 16 2059 08feb2018 | 17. | 17 2223 09feb2018 | 18. | 18 1334 10feb2018 | 19. | 19 1793 11feb2018 | 20. | 20 1475 12feb2018 | 21. | 21 1289 13feb2018 | 22. | 22 1580 14feb2018 | 23. | 23 2797 15feb2018 | 24. | 24 1740 16feb2018 | 25. | 25 1431 17feb2018 | 26. | 26 1589 18feb2018 | 27. | 27 1289 19feb2018 | 28. | 28 1442 20feb2018 | 30. | 30 1277 22feb2018 | 31. | 31 1250 23feb2018 | 33. | 33 1372 25feb2018 | 35. | 35 1414 27feb2018 | 36. | 36 1302 28feb2018 | 38. | 38 1345 02mar2018 | 39. | 39 1727 03mar2018 | 49. | 49 1316 13mar2018 | 51. | 51 1224 15mar2018 | 57. | 57 1390 21mar2018 | 58. | 58 1211 22mar2018 | 69. | 69 1181 02apr2018 | 70. | 70 1186 03apr2018 | 237. | 237 2553 17sep2018 | 238. | 238 1807 18sep2018 | 239. | 239 1347 19sep2018 | 240. | 240 1221 20sep2018 | |---------------------------| 429. | 429 1247 28mar2019 | 476. | 476 1215 14may2019 | 505. | 505 1227 12jun2019 | 660. | 660 1630 14nov2019 | 661. | 661 2374 15nov2019 | 662. | 662 1585 16nov2019 | 663. | 663 1377 17nov2019 | 664. | 664 2783 18nov2019 | 665. | 665 3826 19nov2019 | 666. | 666 2584 20nov2019 | 667. | 667 4889 21nov2019 | 668. | 668 5515 22nov2019 | 669. | 669 1590 23nov2019 | 678. | 678 1465 02dec2019 | |---------------------------| 726. | 726 1192 19jan2020 | 755. | 755 1364 17feb2020 | 756. | 756 1195 18feb2020 | 845. | 845 1198 17may2020 | +---------------------------+
Distributions of outliers over years:- 2018: 44 (71.0%)
- 2019: 14 (22.6%)
- 2020: 4 (6.4%)
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1miau has his good thread on List of useful Bitcoin block explorers and there are subjective ratings on those explorers as well. Personally, I would like to use the three explorers: The first one also gives us blockchain data, that has been used by LoyceV and is stored in loyce.club ( Bitcoin block data available in CSV format). One more thing I like from the explorer is it gives newbies an indicator on priority of their unconfirmed transactions. Blockchain.com is used by many people but their stats are incorrect sometimes and it does not display well on mobile (info for transaction hashes are not displayed fully, something are missing from the screen)
For all explorers: Use them with Tor to protect privacy.
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You can consider to add the table. Consolidate 5 small input into one output will save 65.8% fee when moving it later. The percentage of saving does not count fee for consolidation process. | | | | | | | | | | | | | | | | | | | | | | | | No of Outputs | | | Size (bytes) | | | % save in fee | | | | | 1 | | | 192 | | | 0 | | | | | 2 | | | 226 | | | 41.1 | | | | | 3 | | | 260 | | | 54.9 | | | | | 4 | | | 294 | | | 61.7 | | | | | 5 | | | 328 | | | 65.8 | | | | | 6 | | | 362 | | | 68.6 | | | | | 7 | | | 396 | | | 70.5 | | | | | 8 | | | 430 | | | 72.0 | | | | | 9 | | | 464 | | | 73.1 | | | | | 10 | | | 498 | | | 74.1 | | | | | 15 | | | 668 | | | 76.8 | | | | | 20 | | | 838 | | | 78.2 | | |
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