Update:Time series plot of median and interquartile range
Dataset for median, interquartile range of intraday merits. list week median q1 q3 merit
+------------------------------------------+
| week median q1 q3 merit |
|------------------------------------------|
1. | 2018w26 733 609 991 4465 |
2. | 2018w27 715 598 979 4278 |
3. | 2018w28 707 592 963 4247 |
4. | 2018w29 693 589 922 4167 |
5. | 2018w30 684 577 902 3661 |
|------------------------------------------|
6. | 2018w31 682 575 891 3863 |
7. | 2018w32 675 567 880 4011 |
8. | 2018w33 667 559 867 3631 |
9. | 2018w34 652 555 848 3805 |
10. | 2018w35 642 537 844 3072 |
|------------------------------------------|
11. | 2018w36 639 528 838 3590 |
12. | 2018w37 634 528 829 5644 |
13. | 2018w38 641 530 846 7837 |
14. | 2018w39 640 531 839 4395 |
15. | 2018w40 639 528 829 4310 |
|------------------------------------------|
16. | 2018w41 637 528 808 3816 |
17. | 2018w42 639 530 807 4829 |
18. | 2018w43 639 528 801 3953 |
19. | 2018w44 628 521 796 3347 |
20. | 2018w45 630 522 789 4525 |
|------------------------------------------|
21. | 2018w46 628 523 788 3747 |
22. | 2018w47 628 522.5 783.5 4575 |
23. | 2018w48 627 522 778 3765 |
24. | 2018w49 623.5 520 775 3571 |
25. | 2018w50 622 520 774 3805 |
|------------------------------------------|
26. | 2018w51 621.5 517.5 770 3769 |
27. | 2018w52 617.5 514 764 3338 |
28. | 2019w1 617 514 769 4803 |
29. | 2019w2 621.5 515 775 6632 |
30. | 2019w3 623 517 777 5317 |
|------------------------------------------|
31. | 2019w4 623.5 518.5 775 4667 |
32. | 2019w5 622 518 775 4491 |
33. | 2019w6 622 520 775 4332 |
34. | 2019w7 621 522 771 4221 |
35. | 2019w8 621.5 521 770 4521 |
|------------------------------------------|
36. | 2019w9 622 520 769 4638 |
37. | 2019w10 624 522 766 4913 |
38. | 2019w11 624 522 762 4326 |
39. | 2019w12 626.5 523 761 4609 |
40. | 2019w13 628 525 766 6130 |
|------------------------------------------|
41. | 2019w14 627.5 529 761 4526 |
42. | 2019w15 629 530 762 5271 |
43. | 2019w16 632.5 530.5 764 4688 |
44. | 2019w17 629 530 762 4448 |
45. | 2019w18 629 531 762 4764 |
|------------------------------------------|
46. | 2019w19 636 532 762 5454 |
47. | 2019w20 638.5 532.5 767.5 5214 |
48. | 2019w21 639 533 766 4580 |
49. | 2019w22 639 535 761 4445 |
50. | 2019w23 639 535 761 4687 |
|------------------------------------------|
51. | 2019w24 640 536 764 5354 |
52. | 2019w25 640 537 762 4726 |
53. | 2019w26 640 535 762 4367 |
54. | 2019w27 640 535 761 4225 |
55. | 2019w28 639 532.5 761 4119 |
|------------------------------------------|
56. | 2019w29 639 532 761 4277 |
57. | 2019w30 636.5 533 760 4176 |
List of median, q1, q3 of intra-day merits over weeks, in descending orders of medians.. list week median q1 q3 merit
+------------------------------------------+
| week median q1 q3 merit |
|------------------------------------------|
1. | 2019w1 617 514 769 4803 |
2. | 2018w52 617.5 514 764 3338 |
3. | 2019w7 621 522 771 4221 |
4. | 2019w2 621.5 515 775 6632 |
5. | 2018w51 621.5 517.5 770 3769 |
|------------------------------------------|
6. | 2019w8 621.5 521 770 4521 |
7. | 2019w6 622 520 775 4332 |
8. | 2019w9 622 520 769 4638 |
9. | 2019w5 622 518 775 4491 |
10. | 2018w50 622 520 774 3805 |
|------------------------------------------|
11. | 2019w3 623 517 777 5317 |
12. | 2019w4 623.5 518.5 775 4667 |
13. | 2018w49 623.5 520 775 3571 |
14. | 2019w11 624 522 762 4326 |
15. | 2019w10 624 522 766 4913 |
|------------------------------------------|
16. | 2019w12 626.5 523 761 4609 |
17. | 2018w48 627 522 778 3765 |
18. | 2019w14 627.5 529 761 4526 |
19. | 2018w44 628 521 796 3347 |
20. | 2018w47 628 522.5 783.5 4575 |
|------------------------------------------|
21. | 2019w13 628 525 766 6130 |
22. | 2018w46 628 523 788 3747 |
23. | 2019w15 629 530 762 5271 |
24. | 2019w17 629 530 762 4448 |
25. | 2019w18 629 531 762 4764 |
|------------------------------------------|
26. | 2018w45 630 522 789 4525 |
27. | 2019w16 632.5 530.5 764 4688 |
28. | 2018w37 634 528 829 5644 |
29. | 2019w19 636 532 762 5454 |
30. | 2019w30 636.5 533 760 4176 |
|------------------------------------------|
31. | 2018w41 637 528 808 3816 |
32. | 2019w20 638.5 532.5 767.5 5214 |
33. | 2018w42 639 530 807 4829 |
34. | 2018w40 639 528 829 4310 |
35. | 2019w21 639 533 766 4580 |
|------------------------------------------|
36. | 2019w23 639 535 761 4687 |
37. | 2019w22 639 535 761 4445 |
38. | 2019w28 639 532.5 761 4119 |
39. | 2018w36 639 528 838 3590 |
40. | 2018w43 639 528 801 3953 |
|------------------------------------------|
41. | 2019w29 639 532 761 4277 |
42. | 2019w24 640 536 764 5354 |
43. | 2018w39 640 531 839 4395 |
44. | 2019w26 640 535 762 4367 |
45. | 2019w27 640 535 761 4225 |
|------------------------------------------|
46. | 2019w25 640 537 762 4726 |
47. | 2018w38 641 530 846 7837 |
48. | 2018w35 642 537 844 3072 |
49. | 2018w34 652 555 848 3805 |
50. | 2018w33 667 559 867 3631 |
|------------------------------------------|
51. | 2018w32 675 567 880 4011 |
52. | 2018w31 682 575 891 3863 |
53. | 2018w30 684 577 902 3661 |
54. | 2018w29 693 589 922 4167 |
55. | 2018w28 707 592 963 4247 |
|------------------------------------------|
56. | 2018w27 715 598 979 4278 |
57. | 2018w26 733 609 991 4465 |
- From LoyceV's weekly data dumps. - From my converted datasets in the topic: Time Series Analysis on Distributed Merits in the forum (daily, weekly, monthly)
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Interesting history, and I wish I joined in that early days myself  It is very good that we have this merit system, but I also do think that we may need to upgrade it so that genuine activity plays a bigger role in ranking up. We should focus more on rewarding users, rather then banning them, and make unban procedure a bit better. Maybe even adding a small knowledge test/quiz for passing to new rank. I would limit forum access for newbies to only certain parts of forum, and give them some limited freedom there. There is no Newbie Jails for a long period of time, and admin repeatedly wrote that he does not have plans to bring Newbie Jails back. However, there are suggestions from community, including staffs and global moderators that Whitelist procedure should be considered. Whitelist might create new kinds of work burden on forum staffs, that they might not expect. I still think that if there are some kind of community-led clean-up process like more effective reports, Whitelist is not essential thing to implement. Recent waves of spam bots with Yobit-worded posts eliminated very. I do agree that such things make the forum like a land-fill area of spammers, but it does not last for too long, as I saw. |
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This post is very informative, enjoy! Can you afford 100+ bitcoin?
So you have 100+ BTC in cold storage, and most of us assume it is stored in paper wallet as printed private key. In order to access your coins you need to import that private key in some crypto wallet, but you also need some safe storage for such big amounts of coins. My advice to you is to first invest $60+ in hardware wallet, then take a 100% clean device (PC or smarthphone), download and verify Electrum ( https://electrum.org/#home) before install, import your private key/s in that wallet and then send it to hardware wallet. After that you can think how you will sell it, and you do not need to sell all in one transaction. Maybe it's better to wait a while with selling , price will probably go up in next months / next year. |
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Reporters will be able to see their Report history if they report up to 300 in total. You can read more here, if you have intetersts. Remember that if your total report is less than 300, when you click on the link Report history link, you will get the message You cannot use this page
Report History Only users who have reported 300 good reports have access to this page This is probably one of the most useful features related to reporting. Basically, this shows you a history of your reports, and whether they have been marked good, bad or are unhandled. This page can be used for ongoing evaluation of your reporting habits. Use the information on this page to improve the quality of your posts. |
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Human brains are better than bots. Play a few hands & learn how the bots react. If you know the pattern it's easy to beat bots.
Bots build by human, so how bots can beat human. I meant bots made by stupid human can not beat stupid human; and bots made by smart guys can not beat those smart guys. Because bots simply can not beat bots creators and someone whom have the same level of knowledge, skills and experience in tradin to build same bots. |
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sorry for this strange question.
I want to know if there is a way to creat account It can not be Send or Receive merit?..
Locked and perman-banned accounts still be able to received merits, that are what I saw, but I don't know what will happen with nuked accounts. However, I guess nuked accounts are also able to received accounts. They all likely are unable to send their sMerits. |
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I am renting my avatar, personal text, and signature.
- All of them, or part of them, it depends on your deal.
- About me, I don't write a long introduction and cost your time to read it. Please see the screenshot.
Best regards, Tran Dzung
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It will take a little more while to attract rollers, especially high ones. But surely it will come. It is also best to take note of some suggestions on this thread. I hope there is a dev here who collects the suggestions and apply them as they deem necessary. This forum has a sterling track record of promoting dice sites into huge success.
But the way, the highest number of online rollers that I saw was more than 30. For a dice site with barely a week of existence, not to mention the fact that there is a tight competition on this niche market, it already is a great start. More will come.
It always takes time for young sites to catch attention, and grow up with more users, and more bets. The site has some good advantages, at beginning, beautiful user-interface, and good promotions (maybe the team might consider more diversifying promotions, if they have enough funds). There are some complaints about smoothness (lags) of the site on mobile devices. If there are some issues with the site, not users' internet connections, it should be fixed and improve user experience on their mobile devices. I have one point to suggest, the background color of the page for FAQ, Term, should be adjusted a little bit darker. Current color looks a bit bright and a little bit harder to see. |
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ABSTRACT
Intra-day merits:
Notes:
- The part of the asbstract describes figures of intraday merits over the period from 19/2/2018 to 29/7/2019 (truncated dataset);
- Days from 24/1/2018 to 18/2/2018 truncated due to highly potential outliers; and days after 29/7/2019 truncated as well due to incomplete week (the 2019w31);
- Statistics presented in the post are for truncated dataset
(1) Potential outliers are days that have intraday total merits beyond 193 or 1101;
(2) Median of intraday merits over the period is 637;
(3) 50% of observed days have their intra-day merits range from 533 to 760 (the interquartile range);
(4) Friday [in GTM time] is the day over weeks has lowest intraday merits in terms of both median and mean, at 584, and 612, respectively.
(5) Monday [in GTM time] is the day over weeks has highest intraday merits in terms of median and mean, at 682, and 741.
(6) There are 29 potential outliers in total, and only five of them occured in 2019, on 09/1/2019, 14/01/2019, 27/3/2019, 13/5/2019, and 11/6/2019, at 1162, 1128, 1250, 1151, and 1188, respectively.
(7) Minimum and maximum of intraday merits (full dataset) are 313 and 13018, on 11/2/2019 and 24/1/2018, respectively.
Intra-week merits:
Notes:
The part of the abstract use full dataset, only dropped last two days due to incomple week (2019w31).
(1) The median of intra-week merits is 4526;
(2) 50% of observed weeks (79 weeeks in total), have total merits in the range from 4167 to 5271 (the interquaritle range of intra-week merits).
(3) Minimum and maximum of intra-week merits are 3072 and 30960, in 2018w35, and 2018w4, respectively;
(4) Ten potential outliers [beyond 2511 or 6927], all of them occurred in the year 2018.
Intra-month merits:
Notes:
The part of the abstract use full dataset (no day dropped).
(1) The median of intra-month merits is 20408;
(2) 50% of observed months (19 months in total), have total merits in the range from 18149 to 22994 (the interquaritle range of intra-month merits).
(3) Minimum and maximum of intra-month merits are 15443 and 46701, in 2018m12, and 2018m2, respectively;
(4) Three potential outliers [beyond 10882 or 30262], all of them occurred in the year 2018.
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Intra-month merits (from 24/1/2018 to 31/7/2019)There is no days dropped in order to get data for entire month.Converted dataset:. list merit month
+-----------------+
| merit month |
|-----------------|
1. | 41774 2018m1 |
2. | 46701 2018m2 |
3. | 32138 2018m3 |
4. | 23354 2018m4 |
5. | 19644 2018m5 |
|-----------------|
6. | 18802 2018m6 |
7. | 18149 2018m7 |
8. | 16382 2018m8 |
9. | 22312 2018m9 |
10. | 18470 2018m10 |
|-----------------|
11. | 17437 2018m11 |
12. | 15443 2018m12 |
13. | 22994 2019m1 |
14. | 17989 2019m2 |
15. | 21629 2019m3 |
|-----------------|
16. | 20545 2019m4 |
17. | 22068 2019m5 |
18. | 20408 2019m6 |
19. | 18413 2019m7 |
+-----------------+
- 50% of observed months ( 19 months) have total intra-month merits above 20408, whilst the rest 50% of them have total intra-month merits below 20408. 20408is the median - p50. - 50% of observed months have total intra-month merits fluctuated in the range from 18149 to 22994 (the interquartile range, from p25 to p75, in raw statistics below). - Min - max: 15443- 46701. . tabstat merit, s(n mean sd p50 p25 p75 min max)
variable | N mean sd p50 p25 p75 min max
-------------+--------------------------------------------------------------------------------
merit | 19 22876.42 8381.357 20408 18149 22994 15443 46701
----------------------------------------------------------------------------------------------
. di 22994-18149
4845
. di 4845*1.5
7267.5
. di 22994+7267.5
30261.5
. di 18149-7267.5
10881.5
It means that potential outliers are months that have intra-month merits beyond 10882 or 30262. How many months are potential outliers? . count if (merit >= 30262 | merit <= 10882) & merit != .
3
months are outliers, in total. List of those three months: . list merit month if merit >= 30262 | merit <= 10882
+----------------+
| merit month |
|----------------|
1. | 41774 2018m1 |
2. | 46701 2018m2 |
3. | 32138 2018m3 |
+----------------+
All of them occured in the year 2018, during the first three months after merit system activated 
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Intra-week merits (from 24/1/2018 to 29/7/2019)Last two days dropped due to incomplete weeks (2019w31)Converted dataset:. list merit week
+-----------------+
| merit week |
|-----------------|
1. | 30960 2018w4 |
2. | 19979 2018w5 |
3. | 13313 2018w6 |
4. | 11745 2018w7 |
5. | 8767 2018w8 |
|-----------------|
6. | 8833 2018w9 |
7. | 7261 2018w10 |
8. | 7317 2018w11 |
9. | 6952 2018w12 |
10. | 6744 2018w13 |
|-----------------|
11. | 6423 2018w14 |
12. | 5494 2018w15 |
13. | 4742 2018w16 |
14. | 4612 2018w17 |
15. | 4965 2018w18 |
|-----------------|
16. | 4766 2018w19 |
17. | 4353 2018w20 |
18. | 3864 2018w21 |
19. | 4194 2018w22 |
20. | 4538 2018w23 |
|-----------------|
21. | 3839 2018w24 |
22. | 4929 2018w25 |
23. | 4465 2018w26 |
24. | 4278 2018w27 |
25. | 4247 2018w28 |
|-----------------|
26. | 4167 2018w29 |
27. | 3661 2018w30 |
28. | 3863 2018w31 |
29. | 4011 2018w32 |
30. | 3631 2018w33 |
|-----------------|
31. | 3805 2018w34 |
32. | 3072 2018w35 |
33. | 3590 2018w36 |
34. | 5644 2018w37 |
35. | 7837 2018w38 |
|-----------------|
36. | 4395 2018w39 |
37. | 4310 2018w40 |
38. | 3816 2018w41 |
39. | 4829 2018w42 |
40. | 3953 2018w43 |
|-----------------|
41. | 3347 2018w44 |
42. | 4525 2018w45 |
43. | 3747 2018w46 |
44. | 4575 2018w47 |
45. | 3765 2018w48 |
|-----------------|
46. | 3571 2018w49 |
47. | 3805 2018w50 |
48. | 3769 2018w51 |
49. | 3338 2018w52 |
50. | 4803 2019w1 |
|-----------------|
51. | 6632 2019w2 |
52. | 5317 2019w3 |
53. | 4667 2019w4 |
54. | 4491 2019w5 |
55. | 4332 2019w6 |
|-----------------|
56. | 4221 2019w7 |
57. | 4521 2019w8 |
58. | 4638 2019w9 |
59. | 4913 2019w10 |
60. | 4326 2019w11 |
|-----------------|
61. | 4609 2019w12 |
62. | 6130 2019w13 |
63. | 4526 2019w14 |
64. | 5271 2019w15 |
65. | 4688 2019w16 |
|-----------------|
66. | 4448 2019w17 |
67. | 4764 2019w18 |
68. | 5454 2019w19 |
69. | 5214 2019w20 |
70. | 4580 2019w21 |
|-----------------|
71. | 4445 2019w22 |
72. | 4687 2019w23 |
73. | 5354 2019w24 |
74. | 4726 2019w25 |
75. | 4367 2019w26 |
|-----------------|
76. | 4225 2019w27 |
77. | 4119 2019w28 |
78. | 4277 2019w29 |
79. | 4176 2019w30 |
+-----------------+
- 50% of observed weeks ( 79 weeks) have total intra-week merits above 4526, whilst the rest 50% of them have total intra-week merits below 4526. 4526 is the median - p50. - 50% of observed weeks have total intra-week merits fluctuated in the range from 4167 to 5271 (the interquartile range, from p25 to p75, in raw statistics below). - Min - max: 3072 - 30960. . tabstat merit, s(n mean sd p50 p25 p75 min max)
variable | N mean sd p50 p25 p75 min max
-------------+--------------------------------------------------------------------------------
merit | 79 5487.684 3753.609 4526 4167 5271 3072 30960
----------------------------------------------------------------------------------------------
. di 5271-4167
1104
. di 1104*1.5
1656
. di 5271+1656
6927
. di 4167-1656
2511
It means that potential outliers are weeks that have intra-week merits beyond 2511 or 6927. How many weeks are potential outliers? . count if (merit >= 6927 | merit < 2511) & merit != .
10
weeks are outliers, in total. List of those ten weeks: . list merit week if merit >=6927 | merit <= 2511
+-----------------+
| merit week |
|-----------------|
1. | 30960 2018w4 |
2. | 19979 2018w5 |
3. | 13313 2018w6 |
4. | 11745 2018w7 |
5. | 8767 2018w8 |
|-----------------|
6. | 8833 2018w9 |
7. | 7261 2018w10 |
8. | 7317 2018w11 |
9. | 6952 2018w12 |
35. | 7837 2018w38 |
+-----------------+
All of them occured in the year 2018.
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Medians and means of intra-day merits over days of weeks.Colors: - Green: highest.- Red: Lowest.- In median, the highest days are Monday, Thursday, and Wednesday at 682, 673, and 666, respectively; whislt the lowest days are Friday, Sunday, and Saturday at 584, 609, and 612, respectively. - In means, the highest days are Monday, Wednesday, and Tuesday, at 741, 710, and 703, respectively; whilst the lowest days are Friday, Saturday, and Sunday, at 612, 627, and 682, respectively. - Monday has still been the highest day in terms of median and mean of intra-day merits over weeks, in contrast Friday is the lowest days in terms of median, and mean of intra-day merits over weeks. Calendar day is in GMT time.To take away all doubt: the first Merit was this one: 1516831941 1 2818066.msg28853325 35 877396 Use EpochConverter to convert 1516831941 (Unix Time) to GMT: Wednesday 24 January 2018 22:12:21. . tabstat merit, s(n mean sd p50 p25 p75 min max) format(%9.1f) by(dofw)
Summary for variables: merit
by categories of: dofw
dofw | N mean sd p50 p25 p75 min max
----------+--------------------------------------------------------------------------------
Sunday | 75.0 681.7 285.8 609.0 512.0 784.0 394.0 2464.0
Monday | 76.0 740.4 262.7 681.5 575.0 806.0 313.0 1863.0
Tuesday | 75.0 702.1 203.3 660.0 592.0 759.0 384.0 1327.0
Wednesday | 75.0 709.6 202.8 666.0 563.0 762.0 416.0 1271.0
Thursday | 75.0 685.2 199.6 673.0 531.0 785.0 348.0 1335.0
Friday | 75.0 611.7 193.7 584.0 510.0 651.0 349.0 1706.0
Saturday | 75.0 626.5 198.2 612.0 483.0 692.0 317.0 1410.0
----------+--------------------------------------------------------------------------------
Total | 526.0 679.7 226.4 636.5 533.0 760.0 313.0 2464.0
-------------------------------------------------------------------------------------------
Outliers displayed as red circles. Outliers non-displayed.
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During the period from 24/1/2018 to 29/7/2019, the minimum and maximum of intra-day merits are 313 and 13018, on 24/12/2018 and 24/1/2018, respectively. List of the top 50-highest day in terms of intra-day merits: . list merit id date dofw day month2 year week month
+-------------------------------------------------------------------------------+
| merit id date dofw day month2 year week month |
|-------------------------------------------------------------------------------|
1. | 13018 1 24jan2018 Wednesday 24 1 2018 2018w4 2018m1 |
2. | 6762 2 25jan2018 Thursday 25 1 2018 2018w4 2018m1 |
3. | 4500 3 26jan2018 Friday 26 1 2018 2018w4 2018m1 |
4. | 4193 7 30jan2018 Tuesday 30 1 2018 2018w5 2018m1 |
5. | 3800 6 29jan2018 Monday 29 1 2018 2018w5 2018m1 |
|-------------------------------------------------------------------------------|
6. | 3490 4 27jan2018 Saturday 27 1 2018 2018w4 2018m1 |
7. | 3190 5 28jan2018 Sunday 28 1 2018 2018w4 2018m1 |
8. | 2821 8 31jan2018 Wednesday 31 1 2018 2018w5 2018m1 |
9. | 2569 10 02feb2018 Friday 2 2 2018 2018w5 2018m2 |
10. | 2546 9 01feb2018 Thursday 1 2 2018 2018w5 2018m2 |
|-------------------------------------------------------------------------------|
11. | 2514 22 14feb2018 Wednesday 14 2 2018 2018w7 2018m2 |
12. | 2464 236 16sep2018 Sunday 16 9 2018 2018w37 2018m9 |
13. | 2310 14 06feb2018 Tuesday 6 2 2018 2018w6 2018m2 |
14. | 2182 12 04feb2018 Sunday 4 2 2018 2018w5 2018m2 |
15. | 2143 16 08feb2018 Thursday 8 2 2018 2018w6 2018m2 |
|-------------------------------------------------------------------------------|
16. | 2142 15 07feb2018 Wednesday 7 2 2018 2018w6 2018m2 |
17. | 2078 13 05feb2018 Monday 5 2 2018 2018w6 2018m2 |
18. | 1992 23 15feb2018 Thursday 15 2 2018 2018w7 2018m2 |
19. | 1868 11 03feb2018 Saturday 3 2 2018 2018w5 2018m2 |
20. | 1863 237 17sep2018 Monday 17 9 2018 2018w38 2018m9 |
|-------------------------------------------------------------------------------|
21. | 1748 18 10feb2018 Saturday 10 2 2018 2018w6 2018m2 |
22. | 1706 38 02mar2018 Friday 2 3 2018 2018w9 2018m3 |
23. | 1618 25 17feb2018 Saturday 17 2 2018 2018w7 2018m2 |
24. | 1580 21 13feb2018 Tuesday 13 2 2018 2018w7 2018m2 |
25. | 1449 17 09feb2018 Friday 9 2 2018 2018w6 2018m2 |
|-------------------------------------------------------------------------------|
26. | 1443 19 11feb2018 Sunday 11 2 2018 2018w6 2018m2 |
27. | 1416 24 16feb2018 Friday 16 2 2018 2018w7 2018m2 |
28. | 1410 32 24feb2018 Saturday 24 2 2018 2018w8 2018m2 |
29. | 1404 27 19feb2018 Monday 19 2 2018 2018w8 2018m2 |
30. | 1392 34 26feb2018 Monday 26 2 2018 2018w9 2018m2 |
|-------------------------------------------------------------------------------|
31. | 1355 48 12mar2018 Monday 12 3 2018 2018w11 2018m3 |
32. | 1335 37 01mar2018 Thursday 1 3 2018 2018w9 2018m3 |
33. | 1332 20 12feb2018 Monday 12 2 2018 2018w7 2018m2 |
34. | 1327 35 27feb2018 Tuesday 27 2 2018 2018w9 2018m2 |
35. | 1324 56 20mar2018 Tuesday 20 3 2018 2018w12 2018m3 |
|-------------------------------------------------------------------------------|
36. | 1295 238 18sep2018 Tuesday 18 9 2018 2018w38 2018m9 |
37. | 1293 26 18feb2018 Sunday 18 2 2018 2018w7 2018m2 |
38. | 1280 30 22feb2018 Thursday 22 2 2018 2018w8 2018m2 |
39. | 1271 239 19sep2018 Wednesday 19 9 2018 2018w38 2018m9 |
40. | 1268 29 21feb2018 Wednesday 21 2 2018 2018w8 2018m2 |
|-------------------------------------------------------------------------------|
41. | 1258 68 01apr2018 Sunday 1 4 2018 2018w13 2018m4 |
42. | 1250 428 27mar2019 Wednesday 27 3 2019 2019w13 2019m3 |
43. | 1246 41 05mar2018 Monday 5 3 2018 2018w10 2018m3 |
44. | 1229 57 21mar2018 Wednesday 21 3 2018 2018w12 2018m3 |
45. | 1188 504 11jun2019 Tuesday 11 6 2019 2019w24 2019m6 |
|-------------------------------------------------------------------------------|
46. | 1187 33 25feb2018 Sunday 25 2 2018 2018w8 2018m2 |
47. | 1170 28 20feb2018 Tuesday 20 2 2018 2018w8 2018m2 |
48. | 1162 351 09jan2019 Wednesday 9 1 2019 2019w2 2019m1 |
49. | 1160 50 14mar2018 Wednesday 14 3 2018 2018w11 2018m3 |
50. | 1151 475 13may2019 Monday 13 5 2019 2019w19 2019m5 |
List of the top 50-lowest days in terms of intra-day merits: . list merit id date dofw day month2 year week month
+-------------------------------------------------------------------------------+
| merit id date dofw day month2 year week month |
|-------------------------------------------------------------------------------|
1. | 313 335 24dec2018 Monday 24 12 2018 2018w52 2018m12 |
2. | 317 333 22dec2018 Saturday 22 12 2018 2018w51 2018m12 |
3. | 344 340 29dec2018 Saturday 29 12 2018 2018w52 2018m12 |
4. | 348 298 17nov2018 Saturday 17 11 2018 2018w46 2018m11 |
5. | 348 338 27dec2018 Thursday 27 12 2018 2018w52 2018m12 |
|-------------------------------------------------------------------------------|
6. | 349 304 23nov2018 Friday 23 11 2018 2018w47 2018m11 |
7. | 371 122 25may2018 Friday 25 5 2018 2018w21 2018m5 |
8. | 377 191 02aug2018 Thursday 2 8 2018 2018w31 2018m8 |
9. | 377 342 31dec2018 Monday 31 12 2018 2018w52 2018m12 |
10. | 379 326 15dec2018 Saturday 15 12 2018 2018w50 2018m12 |
|-------------------------------------------------------------------------------|
11. | 380 220 31aug2018 Friday 31 8 2018 2018w35 2018m8 |
12. | 384 217 28aug2018 Tuesday 28 8 2018 2018w35 2018m8 |
13. | 386 214 25aug2018 Saturday 25 8 2018 2018w34 2018m8 |
14. | 387 339 28dec2018 Friday 28 12 2018 2018w52 2018m12 |
15. | 394 341 30dec2018 Sunday 30 12 2018 2018w52 2018m12 |
|-------------------------------------------------------------------------------|
16. | 395 345 03jan2019 Thursday 3 1 2019 2019w1 2019m1 |
17. | 395 529 06jul2019 Saturday 6 7 2019 2019w27 2019m7 |
18. | 396 228 08sep2018 Saturday 8 9 2018 2018w36 2018m9 |
19. | 398 320 09dec2018 Sunday 9 12 2018 2018w49 2018m12 |
20. | 400 262 12oct2018 Friday 12 10 2018 2018w41 2018m10 |
|-------------------------------------------------------------------------------|
21. | 403 329 18dec2018 Tuesday 18 12 2018 2018w51 2018m12 |
22. | 406 287 06nov2018 Tuesday 6 11 2018 2018w45 2018m11 |
23. | 413 403 02mar2019 Saturday 2 3 2019 2019w9 2019m3 |
24. | 413 222 02sep2018 Sunday 2 9 2018 2018w35 2018m9 |
25. | 414 527 04jul2019 Thursday 4 7 2019 2019w27 2019m7 |
|-------------------------------------------------------------------------------|
26. | 416 278 28oct2018 Sunday 28 10 2018 2018w43 2018m10 |
27. | 416 533 10jul2019 Wednesday 10 7 2019 2019w28 2019m7 |
28. | 417 109 12may2018 Saturday 12 5 2018 2018w19 2018m5 |
29. | 419 186 28jul2018 Saturday 28 7 2018 2018w30 2018m7 |
30. | 421 187 29jul2018 Sunday 29 7 2018 2018w30 2018m7 |
|-------------------------------------------------------------------------------|
31. | 422 192 03aug2018 Friday 3 8 2018 2018w31 2018m8 |
32. | 425 276 26oct2018 Friday 26 10 2018 2018w43 2018m10 |
33. | 427 140 12jun2018 Tuesday 12 6 2018 2018w24 2018m6 |
34. | 427 277 27oct2018 Saturday 27 10 2018 2018w43 2018m10 |
35. | 429 418 17mar2019 Sunday 17 3 2019 2019w11 2019m3 |
|-------------------------------------------------------------------------------|
36. | 429 313 02dec2018 Sunday 2 12 2018 2018w48 2018m12 |
37. | 431 264 14oct2018 Sunday 14 10 2018 2018w41 2018m10 |
38. | 431 284 03nov2018 Saturday 3 11 2018 2018w44 2018m11 |
39. | 433 221 01sep2018 Saturday 1 9 2018 2018w35 2018m9 |
40. | 433 208 19aug2018 Sunday 19 8 2018 2018w33 2018m8 |
|-------------------------------------------------------------------------------|
41. | 434 282 01nov2018 Thursday 1 11 2018 2018w44 2018m11 |
42. | 436 190 01aug2018 Wednesday 1 8 2018 2018w31 2018m8 |
43. | 436 154 26jun2018 Tuesday 26 6 2018 2018w26 2018m6 |
44. | 442 521 28jun2019 Friday 28 6 2019 2019w26 2019m6 |
45. | 446 143 15jun2018 Friday 15 6 2018 2018w24 2018m6 |
|-------------------------------------------------------------------------------|
46. | 446 182 24jul2018 Tuesday 24 7 2018 2018w30 2018m7 |
47. | 451 373 31jan2019 Thursday 31 1 2019 2019w5 2019m1 |
48. | 452 206 17aug2018 Friday 17 8 2018 2018w33 2018m8 |
49. | 455 283 02nov2018 Friday 2 11 2018 2018w44 2018m11 |
50. | 456 167 09jul2018 Monday 9 7 2018 2018w28 2018m7 |
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