Looks like the 2017 spike really gave a massive boost. And its just one spot per page. Imagine another one near the bottom, surely the stats are gonna be more interesting.
It's partially wrong. You did not read my posts thoroughly, in that post or in Abstract section of OP. Among 4 indicators: Daily total impressions, Daily total impressions from logged-in users, Daily unique IPs from logged-out users, Daily unique logged-in users. Only the last one (Daily unique logged-in users) reached its all time high back in 2017. For the rest three, their all-time-highs reached in 2018 or 2019. See: The all-time-highs for four indicators: Daily total impressions (374975, in 2018), Daily total impressions from logged-in users (101513, in 2019), Daily unique IPs from logged-out users (39292, in 2018), Daily unique logged-in users (3386, in 2017)
Details over years are there: https://bitcointalk.org/index.php?topic=5213807.msg53490321#msg53490321 |
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Would it be possible to see a graph with ONLY "unique logged in users" vs price (no need to multiply or maybe just 5x) for additional clarity?
I made this one, using the real close price of BTC, without any multiplier. I have not seen it minutes ago, so I will give you that one later. Got trouble with connections in several minutes.  P.S.: Also maybe a zoom in the period Q4 2017-Q1 2018
A quick reminder for you: The BTC price here is the close price of it in some specific days, on which I took data of monthly new registered accounts, as you can see in the thread - Assumed monthly statistics on registered accounts of bitcointalk.org (2009-2019). Consequently, it is not a completely true time-series plot of BTC-price. |
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Converted dataset: +-------------------------------------------+
| date year regacc btccloseprice |
|-------------------------------------------|
1. | 02nov2009 2009 3 . |
2. | 02dec2009 2009 8 . |
3. | 01jan2010 2010 8 . |
4. | 31jan2010 2010 22 . |
5. | 02mar2010 2010 5 . |
|-------------------------------------------|
6. | 01apr2010 2010 22 . |
7. | 01may2010 2010 15 . |
8. | 31may2010 2010 33 . |
9. | 30jun2010 2010 325 . |
10. | 30jul2010 2010 159 . |
|-------------------------------------------|
11. | 29aug2010 2010 148 . |
12. | 28sep2010 2010 190 . |
13. | 28oct2010 2010 204 . |
14. | 27nov2010 2010 383 . |
15. | 27dec2010 2010 384 . |
|-------------------------------------------|
16. | 26jan2011 2011 938 . |
17. | 25feb2011 2011 2202 . |
18. | 27mar2011 2011 2737 . |
19. | 26apr2011 2011 4936 . |
20. | 26may2011 2011 14048 . |
|-------------------------------------------|
21. | 25jun2011 2011 6250 . |
22. | 25jul2011 2011 3903 . |
23. | 24aug2011 2011 2938 . |
24. | 23sep2011 2011 1983 . |
25. | 23oct2011 2011 1965 . |
|-------------------------------------------|
26. | 22nov2011 2011 1835 . |
27. | 22dec2011 2011 1812 . |
28. | 21jan2012 2012 2082 . |
29. | 20feb2012 2012 1901 . |
30. | 21mar2012 2012 2158 . |
|-------------------------------------------|
31. | 20apr2012 2012 1969 . |
32. | 20may2012 2012 2057 . |
33. | 19jun2012 2012 2040 . |
34. | 19jul2012 2012 2145 . |
35. | 18aug2012 2012 2419 . |
|-------------------------------------------|
36. | 17sep2012 2012 2661 . |
37. | 17oct2012 2012 2958 . |
38. | 16nov2012 2012 2763 . |
39. | 16dec2012 2012 2611 . |
40. | 15jan2013 2013 3320 . |
|-------------------------------------------|
41. | 14feb2013 2013 4933 . |
42. | 16mar2013 2013 13816 . |
43. | 15apr2013 2013 18162 . |
44. | 15may2013 2013 11318 115 |
45. | 14jun2013 2013 8095 103 |
|-------------------------------------------|
46. | 14jul2013 2013 6703 96 |
47. | 13aug2013 2013 5505 107 |
48. | 12sep2013 2013 4137 135 |
49. | 12oct2013 2013 5632 134 |
50. | 11nov2013 2013 26804 333 |
|-------------------------------------------|
51. | 11dec2013 2013 28776 958 |
52. | 10jan2014 2014 29576 833 |
53. | 09feb2014 2014 29839 660 |
54. | 11mar2014 2014 22534 623 |
55. | 10apr2014 2014 18065 416 |
|-------------------------------------------|
56. | 10may2014 2014 13071 450 |
57. | 09jun2014 2014 12180 649 |
58. | 09jul2014 2014 10561 626 |
59. | 08aug2014 2014 10925 590 |
60. | 07sep2014 2014 9418 485 |
|-------------------------------------------|
61. | 07oct2014 2014 8218 332 |
62. | 06nov2014 2014 7974 343 |
63. | 06dec2014 2014 8136 376 |
64. | 05jan2015 2015 23256 277 |
65. | 04feb2015 2015 36913 228 |
|-------------------------------------------|
66. | 06mar2015 2015 33500 269 |
67. | 05apr2015 2015 8450 253 |
68. | 05may2015 2015 8577 235 |
69. | 04jun2015 2015 10303 226 |
70. | 04jul2015 2015 11773 256 |
|-------------------------------------------|
71. | 03aug2015 2015 9725 282 |
72. | 02sep2015 2015 7644 228 |
73. | 02oct2015 2015 68601 238 |
74. | 01nov2015 2015 44059 316 |
75. | 01dec2015 2015 37106 379 |
|-------------------------------------------|
76. | 30jan2016 2016 42233 378 |
77. | 29feb2016 2016 24213 438 |
78. | 30mar2016 2016 19336 413 |
79. | 29apr2016 2016 16031 449 |
80. | 29may2016 2016 19935 526 |
|-------------------------------------------|
81. | 28jun2016 2016 12582 651 |
82. | 28jul2016 2016 10646 656 |
83. | 27aug2016 2016 9986 576 |
84. | 26sep2016 2016 9844 607 |
85. | 26oct2016 2016 10718 670 |
|-------------------------------------------|
86. | 25nov2016 2016 10691 738 |
87. | 25dec2016 2016 12429 899 |
88. | 24jan2017 2017 13664 909 |
89. | 23feb2017 2017 13893 1140 |
90. | 25mar2017 2017 15276 924 |
|-------------------------------------------|
91. | 24apr2017 2017 20585 1223 |
92. | 24may2017 2017 31381 2457 |
93. | 23jun2017 2017 35866 2745 |
94. | 23jul2017 2017 40726 2792 |
95. | 22aug2017 2017 45026 4002 |
|-------------------------------------------|
96. | 21sep2017 2017 70477 3858 |
97. | 21oct2017 2017 95568 6080 |
98. | 20nov2017 2017 144762 8014 |
99. | 20dec2017 2017 238433 17132 |
100. | 19jan2018 2018 136872 11818 |
|-------------------------------------------|
101. | 18feb2018 2018 107237 10798 |
102. | 20mar2018 2018 87087 8564 |
103. | 19apr2018 2018 89659 8149 |
104. | 19may2018 2018 83999 8270 |
105. | 18jun2018 2018 72430 6569 |
|-------------------------------------------|
106. | 18jul2018 2018 61360 7338 |
107. | 17aug2018 2018 41451 6441 |
108. | 16sep2018 2018 41516 6464 |
109. | 16oct2018 2018 35335 6551 |
110. | 15nov2018 2018 31502 5675 |
|-------------------------------------------|
111. | 15dec2018 2018 20733 3253 |
112. | 14jan2019 2019 20046 3596 |
113. | 28feb2019 2019 16202 3854 |
114. | 31mar2019 2019 18932 4105 |
115. | 30apr2019 2019 17910 5350 |
|-------------------------------------------|
116. | 30may2019 2019 24472 8319 |
117. | 30jun2019 2019 22357 10817 |
118. | 31jul2019 2019 18913 10085 |
119. | 31aug2019 2019 16452 9630 |
120. | 30sep2019 2019 14561 8294 |
|-------------------------------------------|
121. | 31oct2019 2019 17891 9200 |
122. | 30nov2019 2019 16356 7570 |
123. | 31dec2019 2019 17967 7194 |
+-------------------------------------------+
Over years, the median of monthly new registered accounts is 11318, with the interquartile range is 2661 to 24213. Specially, in the year of 2019, the median and interquartile range are 17939 and 16404 - 19489, respectively. variable | N mean sd p50 p25 p75 min max
-------------+--------------------------------------------------------------------------------
regacc | 123 21856.63 33196.85 11318 2661 24213 3 238433
year10 | 13 146 144.3185 148 22 204 5 384
year11 | 12 3795.583 3560.192 2469.5 1900 4419.5 938 14048
year12 | 12 2313.667 353.35 2151.5 2048.5 2636 1901 2958
year13 | 12 11433.42 8798.91 7399 5219 15989 3320 28776
year14 | 12 15041.42 8092.689 11552.5 8818 20299.5 7974 29839
year15 | 12 24992.25 19299.52 17514.5 9151 37009.5 7644 68601
year16 | 12 16553.67 9350.784 12505.5 10668.5 19635.5 9844 42233
year17 | 12 63804.75 67452.29 38296 17930.5 83022.5 13664 238433
year18 | 12 67431.75 34995.66 66895 38393 88373 20733 136872
year19 | 12 18504.92 2761.404 17938.5 16404 19489 14561 24472
----------------------------------------------------------------------------------------------
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I appreciated your decent time to code the scripts for users but if I was you, I would not going to this one. Users, personally know how many sMerits they have at specific point of time. While if one user is curious how many sMerits left the others have, they might choose to use your scripts and your JSON API for merit data.
I don't say negatively about it but I wonder what is the true reasons to look at the others' unused sMerits (to beg for merits, something like that).
BPIP provided that statistic during a very long period till the day it stopped showing that one. I don't know why Vod decided to stop providing it. As I remembered, BPIP did not provide that statistic before it shown issues with data scraping recent months.
Anyway, thank you for the script and happy new year, @hatshepsut93.
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OP udated with the Abstract section, and I also included the statistics for number of monthly registered accounts. Plot updated as well.It has been shown in these time-series plots in OP, but if you did not recognize it, you can see it in details below with the statistics of each indicator over years (2012 - 2019). As always, I used the medians (p50), not means. Now, let's look at their all time highs, in medians. 1. Daily total impressionsIts all time high is 374975, in 2018, not in 2017. Summary for variables: mimpressions
by categories of: year (Year)
year | N mean sd p50 p25 p75 min max
---------+--------------------------------------------------------------------------------
2012 | 38.0 15088.0 3447.1 15761.3 12433.6 16667.5 6058.1 20716.6
2013 | 40.0 54194.9 24673.3 50380.4 43379.0 63659.3 18206.9 120381.3
2014 | 34.0 135750.9 15362.2 131780.0 124662.3 147388.1 110430.0 162669.1
2015 | 23.0 112016.0 21012.5 111835.7 106363.5 123331.1 40761.9 145381.0
2016 | 34.0 113646.3 9029.7 113654.8 105539.0 121026.2 96311.5 128049.6
2017 | 36.0 226489.9 84789.8 210308.7 153213.9 265930.3 86717.0 440217.4
2018 | 32.0 380478.4 39909.4 374974.9 362659.3 397805.2 271974.4 526107.3
2019 | 32.0 309872.3 47800.9 307333.6 285412.2 339287.3 218751.8 423117.3
---------+--------------------------------------------------------------------------------
Total | 269.0 163724.4 125747.3 123331.1 61236.5 264177.8 6058.1 526107.3
------------------------------------------------------------------------------------------
Its all time high is 101513, in 2019, not in 2017. Summary for variables: mliuser_impressions
by categories of: year (Year)
year | N mean sd p50 p25 p75 min max
---------+--------------------------------------------------------------------------------
2012 | 38.0 4369.7 1183.9 4099.0 3544.8 4951.3 1795.2 7213.2
2013 | 40.0 17249.1 7505.0 18621.3 12892.6 21162.1 3928.5 37228.7
2014 | 34.0 38847.1 13445.2 38291.0 29864.4 46259.9 17464.6 69853.3
2015 | 23.0 15629.7 3771.0 14012.4 13219.1 18919.3 9094.0 24755.5
2016 | 34.0 16152.4 2577.8 15605.4 15011.6 16773.8 13338.2 28292.6
2017 | 36.0 38080.1 18477.7 31572.8 23540.2 53577.1 10015.6 78991.9
2018 | 32.0 92415.7 27127.3 83531.6 73272.6 114457.5 56496.2 143663.0
2019 | 32.0 91759.4 28270.0 101512.3 84289.3 110722.9 17904.0 124806.3
---------+--------------------------------------------------------------------------------
Total | 269.0 38475.7 35797.1 21049.6 14376.6 58683.1 1795.2 143663.0
------------------------------------------------------------------------------------------
Its all time high is 39292, in 2018, not in 2017. Summary for variables: muniqueip
by categories of: year (Year)
year | N mean sd p50 p25 p75 min max
---------+--------------------------------------------------------------------------------
2012 | 38.0 2895.0 668.8 2921.7 2231.9 3390.6 1731.5 4014.4
2013 | 40.0 11746.7 6947.0 9349.3 8079.4 13812.9 3839.3 34218.2
2014 | 34.0 17406.6 5582.9 15729.6 14084.6 20373.0 9942.4 28277.0
2015 | 23.0 8695.0 1598.2 8468.7 7504.4 9820.8 5615.3 11797.0
2016 | 34.0 11067.6 1061.3 10622.5 10350.6 11768.5 9796.0 13983.0
2017 | 36.0 41688.3 25824.5 39291.1 18168.2 49361.3 11145.9 116833.1
2018 | 32.0 35677.8 20870.3 28047.5 20194.1 46479.3 15238.3 100088.1
2019 | 32.0 13512.0 3099.7 13265.3 10809.1 16341.7 8474.1 19462.9
---------+--------------------------------------------------------------------------------
Total | 269.0 17928.8 17796.4 11877.3 8981.7 19462.9 1731.5 116833.1
------------------------------------------------------------------------------------------
Its all time high is 3386, in 2017. Summary for variables: muniqueliusers
by categories of: year (Year)
year | N mean sd p50 p25 p75 min max
---------+--------------------------------------------------------------------------------
2012 | 38.0 382.1 64.4 379.1 328.2 436.2 281.3 573.3
2013 | 40.0 1311.5 543.4 1400.0 867.1 1628.9 394.4 2509.7
2014 | 34.0 2321.5 705.2 2206.3 1872.4 2802.6 1286.6 3811.6
2015 | 23.0 1040.7 345.2 929.3 819.2 1177.9 716.1 2198.8
2016 | 34.0 1407.0 208.0 1423.3 1328.7 1516.8 846.2 1822.0
2017 | 36.0 4005.5 2302.2 3385.8 2036.8 5222.9 1401.8 9920.5
2018 | 32.0 6708.2 2293.6 7054.3 4529.0 8434.4 2675.0 11121.2
2019 | 32.0 1941.9 456.5 1981.7 1521.4 2247.0 1235.9 2905.1
---------+--------------------------------------------------------------------------------
Total | 269.0 2374.3 2251.7 1606.4 1051.9 2566.0 281.3 11121.2
------------------------------------------------------------------------------------------
Comparisons between three periods, with the period 2012-2013 used as a reference group. | ______________________________________ | ____________________________ | _____________ | _____________ | | Indicators | Reference group (2012 - 2013) | 2014 - 2016 * | 2017 - 2019 * | | ______________________________________ | ____________________________ | _____________ | _____________ | | Daily total impressions | 20509 | 120237 (5.9) | 319897 (15.6) | | Daily total impressions from logged-in users | 5754 | 17465 (3) | 75362 (13) | | Daily unique IPs from logged-out users | 4069 | 11229 (2.8 ) | 20178 (5) | | Daily unique logged-in users | 457 | 1471 (2.6) | 3250 (7.1) | | ______________________________________ | ____________________________ | _____________ | _____________ |
Values (Increasing-fold).
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- Public key generated from private key with a one-way process by the elliptic curve multiplication. [1]
- Address generated from public key with another one-way process, by the cryptographic hash function (Double hash ~ SHA - Secure Hash Algorithm, and RIPEMD - RACE Integrity Primitive Evaluation Message Digest). [2]
[2] From that one: you have a Public Key Hash, that will be presented from the Base58Check Encode. |
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Dataset for start-, end-date, and period of each rounds The variable period is calculated by the formula: - (end - start) / 86400.
- 86400 is total seconds per day.
+----------------------------------------+
| round start end period |
|----------------------------------------|
1. | 27 04apr2012 11apr2012 7.1 |
2. | 28 11apr2012 19apr2012 7.3 |
3. | 29 19apr2012 26apr2012 7.7 |
4. | 30 26apr2012 03may2012 7 |
5. | 31 03may2012 10may2012 7.1 |
|----------------------------------------|
6. | 32 10may2012 17may2012 7 |
7. | 33 17may2012 24may2012 7 |
8. | 34 24may2012 31may2012 7 |
9. | 35 31may2012 07jun2012 7 |
10. | 36 07jun2012 15jun2012 7.1 |
|----------------------------------------|
11. | 37 15jun2012 23jun2012 8.9 |
12. | 38 23jun2012 01jul2012 7.1 |
13. | 39 01jul2012 09jul2012 8.2 |
14. | 40 09jul2012 16jul2012 7.6 |
15. | 41 16jul2012 24jul2012 7.2 |
|----------------------------------------|
16. | 42 24jul2012 31jul2012 7 |
17. | 43 31jul2012 07aug2012 7 |
18. | 44 07aug2012 14aug2012 7.9 |
19. | 45 14aug2012 22aug2012 7.2 |
20. | 46 22aug2012 29aug2012 7.1 |
|----------------------------------------|
21. | 47 29aug2012 05sep2012 7.4 |
22. | 48 05sep2012 12sep2012 7 |
23. | 49 12sep2012 20sep2012 7.4 |
24. | 50 20sep2012 27sep2012 7.6 |
25. | 51 27sep2012 06oct2012 8.5 |
|----------------------------------------|
26. | 52 06oct2012 13oct2012 7.5 |
27. | 53 13oct2012 18oct2012 4.8 |
28. | 54 18oct2012 26oct2012 7.6 |
29. | 55 26oct2012 02nov2012 7.1 |
30. | 56 02nov2012 09nov2012 7.5 |
|----------------------------------------|
31. | 57 09nov2012 16nov2012 7.1 |
32. | 58 16nov2012 23nov2012 7.2 |
33. | 59 23nov2012 01dec2012 7.3 |
34. | 60 01dec2012 08dec2012 7.2 |
35. | 61 08dec2012 16dec2012 7.6 |
|----------------------------------------|
36. | 62 16dec2012 23dec2012 7.3 |
37. | 63 23dec2012 31dec2012 7.8 |
38. | 64 31dec2012 07jan2013 7.2 |
39. | 65 07jan2013 14jan2013 7.5 |
40. | 66 14jan2013 21jan2013 7.1 |
|----------------------------------------|
41. | 67 21jan2013 29jan2013 7.9 |
42. | 68 29jan2013 07feb2013 9.1 |
43. | 69 07feb2013 17feb2013 9.2 |
44. | 70 17feb2013 25feb2013 8.7 |
45. | 71 25feb2013 05mar2013 8.1 |
|----------------------------------------|
46. | 72 05mar2013 13mar2013 7.8 |
47. | 73 13mar2013 21mar2013 7.6 |
48. | 74 21mar2013 28mar2013 7 |
49. | 75 28mar2013 05apr2013 7.8 |
50. | 76 05apr2013 12apr2013 7.2 |
|----------------------------------------|
51. | 77 12apr2013 21apr2013 8.8 |
52. | 78 21apr2013 28apr2013 7.5 |
53. | 79 28apr2013 07may2013 9 |
54. | 80 07may2013 17may2013 9.5 |
55. | 81 17may2013 25may2013 8 |
|----------------------------------------|
56. | 82 25may2013 02jun2013 7.9 |
57. | 83 02jun2013 11jun2013 9 |
58. | 84 11jun2013 19jun2013 8.1 |
59. | 85 19jun2013 26jun2013 7.1 |
60. | 86 26jun2013 03jul2013 7.8 |
|----------------------------------------|
61. | 87 03jul2013 12jul2013 8.3 |
62. | 88 12jul2013 20jul2013 8.5 |
63. | 89 20jul2013 30jul2013 9.3 |
64. | 90 30jul2013 07aug2013 8.1 |
65. | 91 07aug2013 16aug2013 9.1 |
|----------------------------------------|
66. | 92 16aug2013 24aug2013 7.8 |
67. | 93 24aug2013 01sep2013 8.1 |
68. | 94 01sep2013 09sep2013 8.7 |
69. | 95 09sep2013 18sep2013 8.1 |
70. | 96 18sep2013 26sep2013 8.9 |
|----------------------------------------|
71. | 97 26sep2013 12oct2013 15.7 |
72. | 98 12oct2013 22oct2013 9.5 |
73. | 99 22oct2013 01nov2013 9.9 |
74. | 100 01nov2013 11nov2013 10 |
75. | 101 11nov2013 21nov2013 10 |
|----------------------------------------|
76. | 102 21nov2013 02dec2013 11.1 |
77. | 103 02dec2013 11dec2013 9.1 |
78. | 104 11dec2013 21dec2013 10.5 |
79. | 105 21dec2013 01jan2014 10.5 |
80. | 106 01jan2014 10jan2014 9 |
|----------------------------------------|
81. | 107 10jan2014 20jan2014 9.8 |
82. | 108 20jan2014 29jan2014 9.3 |
83. | 109 29jan2014 08feb2014 9.8 |
84. | 110 08feb2014 16feb2014 8.5 |
85. | 111 16feb2014 25feb2014 8.4 |
|----------------------------------------|
86. | 112 25feb2014 05mar2014 8 |
87. | 113 05mar2014 15mar2014 10 |
88. | 114 15mar2014 25mar2014 10.2 |
89. | 115 25mar2014 05apr2014 10.9 |
90. | 116 05apr2014 17apr2014 12 |
|----------------------------------------|
91. | 117 17apr2014 28apr2014 11 |
92. | 118 28apr2014 10may2014 11.9 |
93. | 119 10may2014 19may2014 9.8 |
94. | 120 19may2014 30may2014 10.1 |
95. | 121 30may2014 10jun2014 11.1 |
|----------------------------------------|
96. | 122 10jun2014 19jun2014 9 |
97. | 123 19jun2014 30jun2014 11 |
98. | 124 30jun2014 10jul2014 10 |
99. | 125 10jul2014 20jul2014 10 |
100. | 126 20jul2014 31jul2014 11 |
|----------------------------------------|
101. | 127 31jul2014 12aug2014 11.9 |
102. | 128 12aug2014 23aug2014 11.2 |
103. | 129 23aug2014 04sep2014 11.9 |
104. | 130 04sep2014 16sep2014 11.8 |
105. | 131 16sep2014 29sep2014 13.1 |
|----------------------------------------|
106. | 132 29sep2014 11oct2014 12 |
107. | 133 11oct2014 21oct2014 10 |
108. | 134 21oct2014 30oct2014 9.8 |
109. | 135 30oct2014 12nov2014 13 |
110. | 136 12nov2014 26nov2014 13.2 |
|----------------------------------------|
111. | 137 26nov2014 09dec2014 13 |
112. | 138 09dec2014 22dec2014 12.8 |
113. | 139 22dec2014 02jan2015 11.2 |
114. | 140 02jan2015 15jan2015 13 |
115. | 141 15jan2015 30jan2015 15.1 |
|----------------------------------------|
116. | 142 30jan2015 17feb2015 17.9 |
117. | 143 17feb2015 28feb2015 11 |
118. | 144 28feb2015 10mar2015 10 |
119. | 145 10mar2015 25mar2015 15.1 |
120. | 146 25mar2015 07apr2015 12.9 |
|----------------------------------------|
121. | 147 07apr2015 22apr2015 15.7 |
122. | 148 22apr2015 12may2015 19.8 |
123. | 149 12may2015 25may2015 13 |
124. | 149.5 25may2015 29may2015 3.5 |
125. | 150 29may2015 18jun2015 20.1 |
|----------------------------------------|
126. | 151 18jun2015 06jul2015 18.5 |
127. | 152 06jul2015 20jul2015 14.1 |
128. | 153 20jul2015 06aug2015 16.4 |
129. | 154 06aug2015 22aug2015 16.6 |
130. | 155 22aug2015 06sep2015 14.4 |
|----------------------------------------|
131. | 156 06sep2015 23sep2015 17 |
132. | 157 23sep2015 13oct2015 20.8 |
133. | 158 13oct2015 05nov2015 22.3 |
134. | 159 05nov2015 20nov2015 15.6 |
135. | 160 20nov2015 15dec2015 24.4 |
|----------------------------------------|
136. | 161 15dec2015 07jan2016 23.5 |
137. | 162 07jan2016 29jan2016 22.2 |
138. | 163 29jan2016 18feb2016 19.1 |
139. | 164 18feb2016 04mar2016 15.6 |
140. | 165 04mar2016 18mar2016 14 |
|----------------------------------------|
141. | 166 18mar2016 28mar2016 10 |
142. | 167 28mar2016 08apr2016 11.1 |
143. | 168 08apr2016 19apr2016 10.3 |
144. | 169 19apr2016 28apr2016 9.1 |
145. | 170 28apr2016 07may2016 8.9 |
|----------------------------------------|
146. | 171 07may2016 16may2016 9 |
147. | 172 16may2016 25may2016 9.5 |
148. | 173 25may2016 06jun2016 11.7 |
149. | 174 06jun2016 15jun2016 8.8 |
150. | 175 15jun2016 27jun2016 12.5 |
|----------------------------------------|
151. | 176 27jun2016 05jul2016 8.2 |
152. | 177 05jul2016 15jul2016 9.8 |
153. | 178 15jul2016 24jul2016 8.4 |
154. | 179 24jul2016 03aug2016 9.9 |
155. | 180 03aug2016 11aug2016 8.4 |
|----------------------------------------|
156. | 181 11aug2016 19aug2016 8.1 |
157. | 182 19aug2016 29aug2016 9.5 |
158. | 183 29aug2016 08sep2016 10.5 |
159. | 184 08sep2016 19sep2016 11.1 |
160. | 185 19sep2016 28sep2016 9.1 |
|----------------------------------------|
161. | 186 28sep2016 08oct2016 9.9 |
162. | 187 08oct2016 18oct2016 9.4 |
163. | 188 18oct2016 26oct2016 8.8 |
164. | 189 26oct2016 10nov2016 14.2 |
165. | 190 10nov2016 22nov2016 12.6 |
|----------------------------------------|
166. | 191 22nov2016 02dec2016 10.1 |
167. | 192 02dec2016 12dec2016 9.7 |
168. | 193 12dec2016 19dec2016 7.3 |
169. | 194 19dec2016 30dec2016 11 |
170. | 195 30dec2016 09jan2017 9.9 |
|----------------------------------------|
171. | 196 09jan2017 19jan2017 10.1 |
172. | 197 19jan2017 30jan2017 10.2 |
173. | 198 30jan2017 09feb2017 10 |
174. | 199 09feb2017 19feb2017 10.9 |
175. | 200 19feb2017 02mar2017 10.9 |
|----------------------------------------|
176. | 201 02mar2017 11mar2017 9.1 |
177. | 202 11mar2017 22mar2017 11 |
178. | 203 22mar2017 03apr2017 11.8 |
179. | 204 03apr2017 13apr2017 10 |
180. | 205 13apr2017 23apr2017 9.4 |
|----------------------------------------|
181. | 206 23apr2017 02may2017 9.6 |
182. | 207 02may2017 13may2017 10.4 |
183. | 208 13may2017 23may2017 10.5 |
184. | 209 23may2017 01jun2017 9.2 |
185. | 210 01jun2017 10jun2017 9 |
|----------------------------------------|
186. | 211 10jun2017 20jun2017 9.9 |
187. | 212 20jun2017 30jun2017 10 |
188. | 213 30jun2017 09jul2017 8.9 |
189. | 214 09jul2017 18jul2017 9.1 |
190. | 215 18jul2017 28jul2017 9.4 |
|----------------------------------------|
191. | 216 28jul2017 09aug2017 12.7 |
192. | 217 09aug2017 19aug2017 9.9 |
193. | 218 19aug2017 29aug2017 9.9 |
194. | 219 29aug2017 07sep2017 9.2 |
195. | 220 07sep2017 18sep2017 11 |
|----------------------------------------|
196. | 221 18sep2017 27sep2017 8.2 |
197. | 222 27sep2017 06oct2017 9.9 |
198. | 223 06oct2017 17oct2017 10.8 |
199. | 224 17oct2017 26oct2017 9.1 |
200. | 225 26oct2017 09nov2017 13.2 |
|----------------------------------------|
201. | 226 09nov2017 17nov2017 8.6 |
202. | 227 17nov2017 30nov2017 12.7 |
203. | 228 30nov2017 09dec2017 9.5 |
204. | 229 09dec2017 20dec2017 11 |
205. | 230 20dec2017 31dec2017 11 |
|----------------------------------------|
206. | 231 31dec2017 11jan2018 11 |
207. | 232 11jan2018 23jan2018 11.4 |
208. | 233 23jan2018 02feb2018 10.6 |
209. | 234 02feb2018 14feb2018 12 |
210. | 235 14feb2018 27feb2018 12.4 |
|----------------------------------------|
211. | 236 27feb2018 09mar2018 10.7 |
212. | 237 09mar2018 21mar2018 11.9 |
213. | 238 21mar2018 31mar2018 10 |
214. | 239 31mar2018 11apr2018 11 |
215. | 240 11apr2018 25apr2018 14 |
|----------------------------------------|
216. | 241 25apr2018 06may2018 10.3 |
217. | 242 06may2018 16may2018 10.2 |
218. | 243 16may2018 26may2018 10.7 |
219. | 244 26may2018 06jun2018 10.8 |
220. | 245 06jun2018 16jun2018 10 |
|----------------------------------------|
221. | 246 19jun2018 27jun2018 7.2 |
222. | 247 27jun2018 08jul2018 11.1 |
223. | 248 08jul2018 18jul2018 10.7 |
224. | 249 18jul2018 29jul2018 10.3 |
225. | 250 29jul2018 11aug2018 13 |
|----------------------------------------|
226. | 251 11aug2018 22aug2018 11.7 |
227. | 252 22aug2018 03sep2018 12 |
228. | 253 03sep2018 14sep2018 11 |
229. | 254 14sep2018 26sep2018 12.3 |
230. | 255 26sep2018 09oct2018 12.1 |
|----------------------------------------|
231. | 256 09oct2018 21oct2018 12.4 |
232. | 257 21oct2018 31oct2018 10 |
233. | 258 31oct2018 10nov2018 10.1 |
234. | 259 10nov2018 21nov2018 11.2 |
235. | 260 21nov2018 01dec2018 9.9 |
|----------------------------------------|
236. | 261 01dec2018 11dec2018 10.3 |
237. | 262 11dec2018 22dec2018 10.6 |
238. | 263 22dec2018 04jan2019 12.2 |
239. | 264 04jan2019 14jan2019 10.8 |
240. | 265 14jan2019 24jan2019 10 |
|----------------------------------------|
241. | 266 24jan2019 04feb2019 11 |
242. | 267 04feb2019 15feb2019 11.1 |
243. | 268 15feb2019 27feb2019 11.9 |
244. | 269 27feb2019 10mar2019 10.3 |
245. | 270 10mar2019 20mar2019 10.5 |
|----------------------------------------|
246. | 271 20mar2019 30mar2019 10.2 |
247. | 272 30mar2019 10apr2019 11.1 |
248. | 273 10apr2019 21apr2019 10.2 |
249. | 274 21apr2019 01may2019 10.7 |
250. | 275 01may2019 12may2019 10.2 |
|----------------------------------------|
251. | 276 12may2019 22may2019 10.6 |
252. | 277 22may2019 03jun2019 12 |
253. | 278 03jun2019 15jun2019 11.5 |
254. | 279 15jun2019 26jun2019 11.7 |
255. | 280 26jun2019 09jul2019 12.3 |
|----------------------------------------|
256. | 281 09jul2019 19jul2019 10.5 |
257. | 282 19jul2019 31jul2019 11.9 |
258. | 283 31jul2019 11aug2019 11.1 |
259. | 284 11aug2019 22aug2019 10.9 |
260. | 285 22aug2019 02sep2019 11.2 |
|----------------------------------------|
261. | 286 02sep2019 13sep2019 11.1 |
262. | 287 13sep2019 24sep2019 11.1 |
263. | 288 24sep2019 05oct2019 10.9 |
264. | 289 05oct2019 16oct2019 11.1 |
265. | 290 16oct2019 27oct2019 10.7 |
|----------------------------------------|
266. | 291 27oct2019 07nov2019 11 |
267. | 291.3 07nov2019 18nov2019 10.9 |
268. | 291.6 18nov2019 29nov2019 11.2 |
269. | 292 29nov2019 10dec2019 11.1 |
270. | 293 10dec2019 22dec2019 11.1 |
+----------------------------------------+
|
|
|
|
Converted dataset:* Stats are means of all slots in each rounds.. list round mimpressions mliuser_impressions muniqueip muniqueliusers, abb(30)
+-------------------------------------------------------------------------+
| round mimpressions mliuser_impressions muniqueip muniqueliusers |
|-------------------------------------------------------------------------|
1. | 27 10396.15 3607.76 1916.57 293.34 |
2. | 28 9327.17 3482.07 1910.51 291.33 |
3. | 29 10140.64 3324.5 1936.89 281.31 |
4. | 30 10825.75 3340.91 2008.36 304.85 |
5. | 31 10017.87 3544.83 2029.62 304.41 |
|-------------------------------------------------------------------------|
6. | 32 12076.05 3981.47 2704.15 328.28 |
7. | 33 11542.58 3838.12 2168.8 324.34 |
8. | 34 12433.63 3840.39 2450.02 328.13 |
9. | 35 11329.86 3879.17 2113.89 332.21 |
10. | 36 14666.46 4280.32 2230.75 337.85 |
|-------------------------------------------------------------------------|
11. | 37 14850.75 4951.34 2272.89 307.78 |
12. | 38 14695.52 4627.15 2307.02 358.06 |
13. | 39 14196.71 4506.88 2231.86 324.53 |
14. | 40 16064.9 4518.68 2754.97 328.18 |
15. | 41 14792.36 4583 2829.13 346.71 |
|-------------------------------------------------------------------------|
16. | 42 16165.22 5352.38 2743.43 362.37 |
17. | 43 16295.73 5277.55 2906.71 393.46 |
18. | 44 16207.14 4609.32 2936.67 367.43 |
19. | 45 20716.63 7213.18 3671.68 453.64 |
20. | 46 20563.31 7068.85 3551.15 451 |
|-------------------------------------------------------------------------|
21. | 47 19035.63 6371.32 3564.73 436.84 |
22. | 48 20454.73 6812.13 3925.71 470.14 |
23. | 49 17991.77 5735.89 3402.14 441.93 |
24. | 50 20337.76 5640.11 3365.37 434.02 |
25. | 51 17815.61 5409.98 3390.65 408.46 |
|-------------------------------------------------------------------------|
26. | 52 6058.073 1795.2 1731.457 348.27 |
27. | 53 16587.74 4216.55 3610.8 573.33 |
28. | 54 16548.53 4314.92 3351.47 436.19 |
29. | 55 15694.12 3803.23 3179.16 436.46 |
30. | 56 14084.4 3386.01 3148.49 397.88 |
|-------------------------------------------------------------------------|
31. | 57 14897.69 3447.26 3253.61 411.99 |
32. | 58 16300 3677.55 3387.34 424.49 |
33. | 59 18029.75 4316.92 3761.98 456.22 |
34. | 60 16667.5 3965 4014.4 450.64 |
35. | 61 15969.57 3930.26 3915.45 420.34 |
|-------------------------------------------------------------------------|
36. | 62 14623.54 3469.21 3241.83 408.56 |
37. | 63 15828.52 2798.63 2868.86 355.09 |
38. | 64 19114.82 3128.87 3222.25 390.78 |
39. | 65 18842.03 3928.5 4253.5 416.17 |
40. | 66 18206.87 4446.34 3839.29 456.63 |
|-------------------------------------------------------------------------|
41. | 67 20130.95 5182.08 4123.23 465.33 |
42. | 68 21284.1 5113.28 4392.51 399.44 |
43. | 69 20933.36 4972.05 4444.95 394.35 |
44. | 70 22315.17 5772.17 5110.03 499.14 |
45. | 71 26966.28 6945.22 5569.49 598.73 |
|-------------------------------------------------------------------------|
46. | 72 36384.69 9049.06 7418.74 715.28 |
47. | 73 36374 8633.24 7652.79 758.43 |
48. | 75 63297.95 14973.29 17017.29 1156.62 |
49. | 76 96069.47 20083.79 24558.49 1615.48 |
50. | 77 73012.48 19771.29 18643.45 1511.16 |
|-------------------------------------------------------------------------|
51. | 78 64985.74 19692.11 14673.1 1656.7 |
52. | 79 67227.58 23913.91 13918.63 1581.31 |
53. | 80 67077.76 28176.62 12626.57 1678.32 |
54. | 81 59370.51 23886.62 11615.14 1635.54 |
55. | 82 56211.67 21901.3 11923.18 1639.61 |
|-------------------------------------------------------------------------|
56. | 83 58152.08 23082.32 11620.51 2509.68 |
57. | 84 52437.75 21049.61 10528.52 1551.88 |
58. | 85 43849.17 20546.61 9870.15 1689.05 |
59. | 86 50788.66 19997.83 10211.88 1578.9 |
60. | 87 52870.88 19105.06 9382.34 1444.1 |
|-------------------------------------------------------------------------|
61. | 88 48941.07 17920.62 8693.01 1371.31 |
62. | 89 47392.84 18210.32 8745.56 1286.69 |
63. | 90 44569.15 17932.71 8876.8 1392.73 |
64. | 91 48274.6 18944.45 8981.67 1301.85 |
65. | 92 49972.16 18491.47 9316.25 1433.77 |
|-------------------------------------------------------------------------|
66. | 93 49814.09 19154.5 9253.43 1440.28 |
67. | 94 48752.04 18638.16 8981.9 1384.23 |
68. | 95 48101.89 18092.44 8759.78 1407.36 |
69. | 96 54504.56 21274.66 8506.02 1304.46 |
70. | 97 42908.79 12112.66 6320.05 775.32 |
|-------------------------------------------------------------------------|
71. | 98 54876.27 13672.54 9089.29 958.8 |
72. | 99 49506.06 14915.62 10380.83 1056.76 |
73. | 100 64020.66 18604.5 13707.2 1299.34 |
74. | 101 82053.77 24077.28 19767.71 1622.27 |
75. | 102 111627.1 27074.75 30121.49 1985.26 |
|-------------------------------------------------------------------------|
76. | 103 120381.3 26686.47 34218.23 2135.82 |
77. | 104 61236.46 16708.63 19692.48 1971.38 |
78. | 105 114074.9 37228.74 23062.74 2381.57 |
79. | 106 130248.2 46259.9 26271.68 2913.16 |
80. | 107 116613.3 43553.71 23889.91 2802.56 |
|-------------------------------------------------------------------------|
81. | 108 130868 49589.68 27148.62 3226.39 |
82. | 109 139058.3 54396.15 26759.18 3237.56 |
83. | 110 139108.8 52377.86 28056.06 3618.43 |
84. | 111 136637.7 52623.01 27165.78 3601.96 |
85. | 112 161643.4 62128.49 28277.02 3811.62 |
|-------------------------------------------------------------------------|
86. | 113 161728.8 69853.28 23844.28 3395.09 |
87. | 114 147629.4 65030.97 20372.99 3105.5 |
88. | 115 126627.2 55810.72 19011.89 2737.18 |
89. | 116 112479.1 38519.34 15961.08 2290.46 |
90. | 117 110430 32439.37 15901.74 1872.39 |
|-------------------------------------------------------------------------|
91. | 118 121486.5 38062.67 14990.38 1953.21 |
92. | 119 118725.5 38974.36 15018.76 2316.55 |
93. | 120 137454.3 44638.31 16550.29 2366.4 |
94. | 121 131806.7 42386.35 16299.87 2206.86 |
95. | 122 129479.8 41699.36 17113.16 2515.35 |
|-------------------------------------------------------------------------|
96. | 123 120696.5 40018.67 14889.64 2194.56 |
97. | 124 135314.3 38958.39 15734.9 2358.95 |
98. | 125 152765.8 37786.87 15645.72 2264.28 |
99. | 126 160564.3 37808.64 15824.18 2083.25 |
100. | 127 147388.1 34364.11 14079.21 1962.65 |
|-------------------------------------------------------------------------|
101. | 128 157491.2 36339.47 14461.51 2050.7 |
102. | 129 162669.1 30337.78 15724.32 1884.46 |
103. | 130 161975.4 31243.81 14573.09 1906.91 |
104. | 131 147166.5 29864.38 15067.33 1733.99 |
105. | 132 135172.1 27277.18 14084.56 1745.9 |
|-------------------------------------------------------------------------|
106. | 133 131753.4 23564.31 12605.09 1758.33 |
107. | 134 128383.3 23693.82 12151.24 1555.67 |
108. | 135 129741.4 22990.06 11685.81 1318.91 |
109. | 136 124662.3 21118.32 11142.02 1311.8 |
110. | 137 122142.8 19526.88 10460.19 1286.62 |
|-------------------------------------------------------------------------|
111. | 138 124876.6 20099.66 11120.51 1337.24 |
112. | 139 120742.7 17464.57 9942.37 2205.81 |
113. | 140 111835.7 24755.51 11797.05 1415.05 |
114. | 141 40761.88 9093.98 5615.32 886.35 |
115. | 142 97221.18 18171.97 9972.141 1051.92 |
|-------------------------------------------------------------------------|
116. | 143 132697.3 20188.15 10935.69 1444.37 |
117. | 144 132716.3 20790.19 10619.58 1527.4 |
118. | 145 145381 19757.93 9820.77 1177.87 |
119. | 146 145249.5 18919.34 9170 1252.94 |
120. | 147 123331.1 20603.46 9146.15 1080.79 |
|-------------------------------------------------------------------------|
121. | 148 126740.7 18554.71 8286.47 897.27 |
122. | 149 87466.23 12275.86 6681.34 1011.45 |
123. | 149.5 109871.8 13888.85 11568.68 2198.78 |
124. | 150 110968.8 13372.98 7685.43 743.5 |
125. | 151 112167.5 13752.41 7504.42 819.19 |
|-------------------------------------------------------------------------|
126. | 152 106363.5 14012.39 8468.66 1010.56 |
127. | 153 103017.5 13393.28 7755.94 873.83 |
128. | 154 111646.5 14138.29 7762.23 883.03 |
129. | 155 118249.4 14441.79 7490.34 959.05 |
130. | 156 112985.4 14376.57 7294.27 847.7 |
|-------------------------------------------------------------------------|
131. | 157 114930.1 13219.1 6920.8 726.19 |
132. | 158 116444.9 13927.3 8007.74 743.35 |
133. | 159 110046 12316.04 9266.58 929.27 |
134. | 160 98248.79 12665.5 8554.91 716.09 |
135. | 161 108026.3 12868.57 9660.5 740.41 |
|-------------------------------------------------------------------------|
136. | 162 120237 15477.06 10624.03 846.2 |
137. | 163 117220.3 15011.64 10060.33 914.62 |
138. | 164 122911.8 15641.31 10379.95 1041.95 |
139. | 165 104238.3 15603.23 10426.96 1096.96 |
140. | 166 105539 15628.03 11284.46 1342.19 |
|-------------------------------------------------------------------------|
141. | 167 110085.2 16262.36 9938.21 1291.91 |
142. | 168 110620.4 16862.07 10008.43 1357.23 |
143. | 169 101689.7 16663.9 10303.82 1472.26 |
144. | 170 99180.14 15168.35 10350.57 1426.08 |
145. | 171 103872.3 14443.57 10620.94 1408.75 |
|-------------------------------------------------------------------------|
146. | 172 102438.4 17082.37 10352.2 1420.61 |
147. | 173 109991.7 18101.85 10503 1328.73 |
148. | 174 127533.4 18900.05 13274.88 1672.16 |
149. | 175 123635 19960.94 12210.46 1374.4 |
150. | 176 118887.2 16802.19 11877.3 1710.89 |
|-------------------------------------------------------------------------|
151. | 177 112984.2 16098.36 10525.58 1491.69 |
152. | 178 125313.1 14943.63 9795.98 1530.64 |
153. | 179 128049.6 15049.24 10253.72 1400.85 |
154. | 180 118997.1 15106.11 11228.47 1666.79 |
155. | 181 111764 14747.32 11349.65 1565.22 |
|-------------------------------------------------------------------------|
156. | 182 115268 16773.77 10624.55 1427.3 |
157. | 183 123113.7 28292.58 10480.75 1405.35 |
158. | 184 113827.7 13553.08 9934.51 1323.7 |
159. | 185 107646.2 13338.18 10414.77 1474.03 |
160. | 186 97576.23 13396.87 10027.89 1385.2 |
|-------------------------------------------------------------------------|
161. | 187 104300.2 14133.81 10767.64 1470.44 |
162. | 188 111111.4 14726.37 11758.52 1551.52 |
163. | 189 96311.53 15489.41 11308.85 1202.99 |
164. | 190 124919 16953.85 11768.45 1307.89 |
165. | 191 121026.2 16467.96 12330.31 1516.78 |
|-------------------------------------------------------------------------|
166. | 192 119123.6 15071.75 12719.88 1515.43 |
167. | 193 113481.8 15574.8 12670.26 1822.03 |
168. | 194 119518.6 15607.62 12138.82 1457.47 |
169. | 195 121562.8 16248.43 13983.03 1616.85 |
170. | 196 119880.8 16172.66 13428.56 1582 |
|-------------------------------------------------------------------------|
171. | 197 124087.6 17678.33 14303.09 1606.44 |
172. | 198 134646.9 19650.49 15422.5 1709.3 |
173. | 199 144489.3 19333.02 15099.32 1610.67 |
174. | 200 86717.01 10015.55 11145.92 1401.785 |
175. | 201 164139.5 19462.43 17532.81 1888.02 |
|-------------------------------------------------------------------------|
176. | 202 153114.8 20839.38 18161.05 1817.45 |
177. | 203 149551.7 19931.19 17024.18 1748.66 |
178. | 204 150756.3 25852.33 18175.38 1974.74 |
179. | 205 152086.5 26705.68 17841.71 2098.77 |
180. | 206 153313 22900.15 19551.52 2234.77 |
|-------------------------------------------------------------------------|
181. | 207 165989.5 24180.18 22795.35 2286.81 |
182. | 208 170968.7 24441.83 26642.05 2416.75 |
183. | 209 190589.3 26649.17 34105.28 2896.55 |
184. | 210 210983.7 29783.82 38206.55 3197.91 |
185. | 211 209633.8 31533.68 43444.91 3224.79 |
|-------------------------------------------------------------------------|
186. | 212 200669.3 31302.43 43084.6 3274.63 |
187. | 213 185648.6 29196.76 39170.05 3474.82 |
188. | 214 203014.5 31611.89 38305.14 3579.74 |
189. | 215 222843.5 34887.28 37696.27 3630.49 |
190. | 216 226129.4 37899.3 39412.24 3296.75 |
|-------------------------------------------------------------------------|
191. | 217 240297.4 37901.2 43376.75 3968.85 |
192. | 218 258580.9 40301.65 48536.11 4183.75 |
193. | 219 249940.4 43371.47 50186.57 4633.08 |
194. | 220 257036.2 42450.4 42782.84 4076.34 |
195. | 221 267682.7 49909.51 42792.97 4993.68 |
|-------------------------------------------------------------------------|
196. | 222 261592.6 49414.35 43622.66 5008.1 |
197. | 223 264177.8 57244.71 46540.47 5437.65 |
198. | 224 303197.1 57818.07 62941.86 6582.47 |
199. | 225 314465.1 65211.05 54905.86 5731.15 |
200. | 226 327698.7 66672.67 63412.23 7623.04 |
|-------------------------------------------------------------------------|
201. | 227 337132.3 64189.38 65493.77 6462.21 |
202. | 228 353303.3 67031.66 88037.62 8332.92 |
203. | 229 375048.2 65931.84 99364.53 8207.67 |
204. | 230 384012.2 64416.77 91401.26 8084.18 |
205. | 231 440217.4 78991.86 116833.1 9920.479 |
|-------------------------------------------------------------------------|
206. | 232 444917.9 83608.33 100088.1 10147.65 |
207. | 233 400508 85624.48 84119.49 10058.35 |
208. | 234 400906.1 80080.25 68905.79 8819.27 |
209. | 235 350520.7 78158.12 61031.71 8386.37 |
210. | 236 369802.9 81887.58 60038.04 9113.96 |
|-------------------------------------------------------------------------|
211. | 237 347646.9 81321.59 50331.32 8142.42 |
212. | 238 271974.4 78709.44 46175.32 8809.23 |
213. | 239 375000.2 83559.04 48208 8321.98 |
214. | 240 355274.3 74244.97 42710.33 7027.27 |
215. | 241 377917.7 69888.03 46783.2 8075.64 |
|-------------------------------------------------------------------------|
216. | 242 394545.6 72300.14 45303.34 8495.01 |
217. | 243 405402.8 78227.44 31219.92 8482.39 |
218. | 244 374949.6 69086.28 29777.1 8101.86 |
219. | 245 374077.2 64213.39 28880.03 8348.24 |
220. | 246 526107.3 85532.73 37797.65 11121.24 |
|-------------------------------------------------------------------------|
221. | 247 392151.2 57107.84 24900.56 7211.37 |
222. | 248 353164 56496.2 25883.25 7081.23 |
223. | 249 363392.1 59189.3 27214.98 6879.67 |
224. | 250 401658.4 62557.86 29479.02 5964.86 |
225. | 251 384710.1 90854.92 24060.85 5699.79 |
|-------------------------------------------------------------------------|
226. | 252 369258.3 109407.1 20206.56 5373.21 |
227. | 253 389426.3 119507.9 20460.26 5471.21 |
228. | 254 341095.7 83504.26 20181.55 4779.87 |
229. | 255 366577.6 103295.5 20407.67 4357.64 |
230. | 256 410160.6 141941.6 22609.81 4270.39 |
|-------------------------------------------------------------------------|
231. | 257 395102.4 143663 20174.47 4621.92 |
232. | 258 405572.8 140677.6 19293.15 4436.01 |
233. | 259 393714.6 142440.5 18401.69 4003.18 |
234. | 260 373496 128386.2 17865.4 3827.52 |
235. | 261 361926.6 124601.1 16983.81 3473.51 |
|-------------------------------------------------------------------------|
236. | 262 340213.3 120962.3 15238.28 3086.08 |
237. | 263 364137.6 106266.5 16958.74 2675.04 |
238. | 264 343686.1 118686.5 16610.11 2905.1 |
239. | 265 368792.6 99783.42 17614.41 2902.07 |
240. | 266 301084.5 84122.09 19462.91 2566 |
|-------------------------------------------------------------------------|
241. | 267 248086 44463.62 16248.2 2466.69 |
242. | 268 341440.1 90938.14 16435.15 2315.68 |
243. | 269 295101.9 90434.84 15402.42 2304.16 |
244. | 270 307412.2 93506.88 15779.48 2247.73 |
245. | 271 336184.8 100595.3 15849.19 2246.18 |
|-------------------------------------------------------------------------|
246. | 272 359970.9 103140.9 17268.29 2239.04 |
247. | 273 337873.1 100488.5 16592.09 2176.95 |
248. | 274 336661.1 106726 18052.01 2137.72 |
249. | 275 343342.7 106282 15780.76 2179.83 |
250. | 276 409292.1 112939 17446.72 2354.02 |
|-------------------------------------------------------------------------|
251. | 277 423117.3 114442 13825.97 2111.12 |
252. | 278 325328.6 111911 12801.78 1930.99 |
253. | 279 340701.6 124806.3 13964.51 2048.44 |
254. | 280 305277.3 102429.3 13209.62 1921.22 |
255. | 281 337179.8 103565.1 13320.96 2032.47 |
|-------------------------------------------------------------------------|
256. | 282 313884.7 122089.8 11121.37 1766.48 |
257. | 283 300250.2 107787.2 11451.39 1752.57 |
258. | 284 297896.1 109534.8 10743.18 1690.39 |
259. | 285 290406.9 107004.4 11825.32 1621.13 |
260. | 286 311072.3 116003.5 11383.78 1580.78 |
|-------------------------------------------------------------------------|
261. | 287 256432.3 76478.43 10261.56 1511.07 |
262. | 288 307255.1 112470.2 10875.12 1531.82 |
263. | 289 229093.8 17903.98 9715.57 1433.98 |
264. | 290 275764.8 84456.51 10600.02 1455.32 |
265. | 291 292228.8 92419.04 11177.19 1443.64 |
|-------------------------------------------------------------------------|
266. | 291.3 255976.3 64461.38 9557.34 1337.13 |
267. | 291.6 280417.4 58683.05 9979.15 1368.19 |
268. | 292 225950.9 25770.32 9553.12 1327.45 |
269. | 293 218751.8 31976.96 8474.109 1235.89 |
+-------------------------------------------------------------------------+
|
|
|
|
The forum celebrated its 10 th anniversary weeks ago, and today I am going to give you the statistics on four indicators of the forum ads.
Updates will be made in new posts, each 6-months.
ABSTRACT- The all-time-highs for four indicators: Daily total impressions (374975, in 2018), Daily total impressions from logged-in users (101513, in 2019), Daily unique IPs from logged-out users (39292, in 2018), Daily unique logged-in users (3386, in 2017) (Details)
- There are 270 rounds in total (from 4/4/2012 to 22/12/2019), but I used only 269 rounds for the analysis (round 74 is missing or data-error).
- Statistics for period of each round: median (10 days); min (3.5 days); max (24.4 days).
- There are three periods, in which 4 indicators changed dramatically: 2012- 2013; 2014 - 2016; and 2017 - 2019.
- With the period 2012 - 2013 as a reference group, we have the increasing-times of each indicators for the rest two periods as follow (Details):
- Daily total impressions: 2014 - 2016 (5.9-fold), 2017 - 2019 (15.6-fold).
- Daily total impressions from logged-in users: 2014 - 2016 (3-fold), 2017 - 2019 (13-fold).
- Daily unique IPs from logged-out users: 2014 - 2016 (2.8-fold), 2017 - 2019 (5-fold).
- Daily unique logged-in users: 2014 - 2016 (2.6-fold), 2017 - 2019 (7.1-fold).
- Each month (in median), there are about 11300 new accounts registered.
Data:Time-series plots:I added BTC close price to these plots, but I used its close price * 10 or 20 (see the note below each plots) in order to have better visual presentation on plots. A reminder for you: these red vertical lines are days on which the merit system kicked-off (24/1/2018), and the enhanced merit system activated (17/9/2018). For all 4 indicators + monthly registered accounts: Then, I splited them into 2 parts, with each set of 2 indicators presented in the same plots. Statistics:There are 270 rounds of ads from 4/4/2012 (round 27) to 22/12/2019 (round 293). I decided to drop round 26 (incomplete) and round 74 (likely missing or error data). So, finally, we have 269 rounds in total. How long each round usually lasts? 10 days in median. Min and max are 3.5 and 24.4 days, respectively. variable | N mean sd p50 p25 p75 min max
-------------+--------------------------------------------------------------------------------
period | 269.0 10.4 2.9 10.0 8.5 11.1 3.5 24.4
----------------------------------------------------------------------------------------------
variable | N mean sd p50 p25 p75 min max
-------------+--------------------------------------------------------------------------------
mimpressions | 269.0 163724.4 125747.3 123331.1 61236.5 264177.8 6058.1 526107.3
mliuser_im~s | 269.0 38475.7 35797.1 21049.6 14376.6 58683.1 1795.2 143663.0
muniqueip | 269.0 17928.8 17796.4 11877.3 8981.7 19462.9 1731.5 116833.1
muniqueliu~s | 269.0 2374.3 2251.7 1606.4 1051.9 2566.0 281.3 11121.2
regacc | 123.0 21856.6 33196.9 11318.0 2661.0 24213.0 3.0 238433.0
----------------------------------------------------------------------------------------------
The plots show that there are some different periods, in which stats changed dramatically. From that findings, I categorised the period into three parts: period_grp | Freq. Percent Cum.
------------+-----------------------------------
2012 - 2013 | 78 29.00 29.00
2014 - 2016 | 91 33.83 62.83
2017 - 2019 | 100 37.17 100.00
------------+-----------------------------------
Total | 269 100.00
Now, let's see how stats for each indicator changed over years. 1. Daily total impressions period_grp | N mean sd p50 p25 p75 min max
------------+--------------------------------------------------------------------------------
2012 - 2013 | 78.0 35142.8 26478.3 20509.0 15828.5 50788.7 6058.1 120381.3
2014 - 2016 | 91.0 121493.1 18637.8 120237.0 110620.4 130868.0 40761.9 162669.1
2017 - 2019 | 100.0 302448.6 88542.9 319896.9 244191.7 369530.6 86717.0 526107.3
------------+--------------------------------------------------------------------------------
Total | 269.0 163724.4 125747.3 123331.1 61236.5 264177.8 6058.1 526107.3
---------------------------------------------------------------------------------------------
Summary for variables: mliuser_impressions
by categories of: period_grp
period_grp | N mean sd p50 p25 p75 min max
------------+--------------------------------------------------------------------------------
2012 - 2013 | 78.0 10974.5 8437.0 5754.0 3981.5 18638.2 1795.2 37228.7
2014 - 2016 | 91.0 24499.6 14013.9 17464.6 14943.6 32439.4 9094.0 69853.3
2017 - 2019 | 100.0 72644.9 35780.9 75361.7 39101.4 103218.2 10015.6 143663.0
------------+--------------------------------------------------------------------------------
Total | 269.0 38475.7 35797.1 21049.6 14376.6 58683.1 1795.2 143663.0
---------------------------------------------------------------------------------------------
Summary for variables: muniqueip
by categories of: period_grp
period_grp | N mean sd p50 p25 p75 min max
------------+--------------------------------------------------------------------------------
2012 - 2013 | 78.0 7434.3 6670.0 4068.8 2936.7 9382.3 1731.5 34218.2
2014 - 2016 | 91.0 12836.3 5091.3 11228.5 9972.1 14889.6 5615.3 28277.0
2017 - 2019 | 100.0 30748.5 22860.0 20178.0 15412.5 42938.8 8474.1 116833.1
------------+--------------------------------------------------------------------------------
Total | 269.0 17928.8 17796.4 11877.3 8981.7 19462.9 1731.5 116833.1
---------------------------------------------------------------------------------------------
Summary for variables: muniqueliusers
by categories of: period_grp
period_grp | N mean sd p50 p25 p75 min max
------------+--------------------------------------------------------------------------------
2012 - 2013 | 78.0 858.7 608.4 456.4 390.8 1407.4 281.3 2509.7
2014 - 2016 | 91.0 1656.1 717.5 1470.4 1203.0 1962.7 716.1 3811.6
2017 - 2019 | 100.0 4210.0 2698.4 3249.7 2003.6 6213.5 1235.9 11121.2
------------+--------------------------------------------------------------------------------
Total | 269.0 2374.3 2251.7 1606.4 1051.9 2566.0 281.3 11121.2
---------------------------------------------------------------------------------------------
They are raw statistics, but you can see that all indicators have stats increased exponentially (2 to 4.3 times) over years, between three periods (2012 - 2013, 2014 - 2016, and 2017 - 2019). As always, for an overview, I would like to look at the medians (p50), not means.
My idea to create my thread came from this one: [Chart] Bitcointalk statistics on impression counts for ads for a quite some time (months) ago. Honestly I was too lazy to do it but now I made it and hope that my thread adds some additional details, and expands the thread of Coin-1 a little bit. |
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Update: (on 2019w51)
ABSTRACT- Total merits distributed on 2019w51 is 6194.
- Compare to 4521 (the median of weekly merits on 2019w46 - 6 weeks ago), the percentage of last week merits increases 37%.
- The last week ranked at 16th position over 100 weeks.
- Total distributed merits: 6194 (see)
- Median of weekly merits before the 2019w46 (when theymos began to dump massive merits): 4521
What does it means, guys? . di (6194-4521)/4521*100
37.005087
It means that on the last week - 2019w51 - the forum community sent 1673 more merits than they usually did in previous weeks (at 4521, the weekly median). In percentage, there is about 37 % increase compares to median of weekly merits, took at 2019w46 (6 weeks ago). In terms of rank for intra-week merits, the last week ranked at 16th position, that is not impressive. +------------------------------+
| weeklyrank merit week |
|------------------------------|
1. | 1 30960 2018w4 |
2. | 2 19979 2018w5 |
3. | 3 17685 2019w47 |
4. | 4 14251 2019w46 |
5. | 5 13313 2018w6 |
|------------------------------|
6. | 6 11745 2018w7 |
7. | 7 8833 2018w9 |
8. | 8 8767 2018w8 |
9. | 9 7837 2018w38 |
10. | 10 7317 2018w11 |
|------------------------------|
11. | 11 7261 2018w10 |
12. | 12 6952 2018w12 |
13. | 13 6744 2018w13 |
14. | 14 6632 2019w2 |
15. | 15 6423 2018w14 |
|------------------------------|
16. | 16 6194 2019w51 |
17. | 17 6130 2019w13 |
18. | 18 5907 2019w48 |
19. | 19 5644 2018w37 |
20. | 20 5542 2019w42 |
|------------------------------|
21. | 21 5494 2018w15 |
22. | 22 5454 2019w19 |
23. | 23 5354 2019w24 |
24. | 24 5317 2019w3 |
25. | 25 5271 2019w15 |
|------------------------------|
26. | 26 5214 2019w20 |
27. | 27 5186 2019w50 |
28. | 28 4975 2019w43 |
29. | 29 4965 2018w18 |
30. | 30 4929 2018w25 |
|------------------------------|
31. | 31 4913 2019w10 |
32. | 32 4829 2018w42 |
33. | 33 4803 2019w1 |
34. | 34 4766 2018w19 |
35. | 35 4764 2019w18 |
|------------------------------|
36. | 36 4742 2018w16 |
37. | 37 4735 2019w45 |
38. | 38 4730 2019w44 |
39. | 39 4726 2019w25 |
40. | 40 4688 2019w16 |
|------------------------------|
41. | 41 4687 2019w23 |
42. | 42 4667 2019w4 |
43. | 43 4638 2019w9 |
44. | 44 4612 2018w17 |
45. | 45 4609 2019w12 |
|------------------------------|
46. | 46 4580 2019w21 |
47. | 47 4575 2018w47 |
48. | 48 4565 2019w41 |
49. | 49 4538 2018w23 |
50. | 50 4526 2019w14 |
|------------------------------|
51. | 51 4525 2018w45 |
52. | 52 4524 2019w49 |
53. | 53 4521 2019w8 |
54. | 54 4520 2019w38 |
55. | 55 4491 2019w5 |
|------------------------------|
56. | 56 4465 2018w26 |
57. | 57 4448 2019w17 |
58. | 58 4445 2019w22 |
59. | 59 4395 2018w39 |
60. | 60 4367 2019w26 |
|------------------------------|
61. | 61 4357 2019w40 |
62. | 62 4353 2018w20 |
63. | 63 4332 2019w6 |
64. | 64 4326 2019w11 |
65. | 65 4318 2019w39 |
|------------------------------|
66. | 66 4310 2018w40 |
67. | 67 4278 2018w27 |
68. | 68 4277 2019w29 |
69. | 69 4247 2018w28 |
70. | 70 4236 2019w33 |
|------------------------------|
71. | 71 4225 2019w27 |
72. | 72 4221 2019w7 |
73. | 73 4194 2018w22 |
74. | 74 4176 2019w30 |
75. | 75 4167 2018w29 |
|------------------------------|
76. | 76 4119 2019w28 |
77. | 77 4043 2019w37 |
78. | 78 4011 2018w32 |
79. | 79 3953 2018w43 |
80. | 80 3864 2018w21 |
|------------------------------|
81. | 81 3863 2018w31 |
82. | 82 3839 2018w24 |
83. | 83 3816 2018w41 |
84. | 84 3809 2019w36 |
85. | 85 3805 2018w34 |
|------------------------------|
86. | 86 3805 2018w50 |
87. | 87 3769 2018w51 |
88. | 88 3765 2018w48 |
89. | 89 3747 2018w46 |
90. | 90 3661 2018w30 |
|------------------------------|
91. | 91 3631 2018w33 |
92. | 92 3622 2019w34 |
93. | 93 3590 2018w36 |
94. | 94 3571 2018w49 |
95. | 95 3549 2019w31 |
|------------------------------|
96. | 96 3540 2019w35 |
97. | 97 3347 2018w44 |
98. | 98 3338 2018w52 |
99. | 99 3207 2019w32 |
100. | 100 3072 2018w35 |
+------------------------------+
As predicted, people, including merit sources, gave away more sMerits again when their sMerits refilled after 30 days but the 37% increase is quite impressive, in my opinion, compared to the median of weekly merits 6 weeks ago, and compared to the percentage of increases in monthly sMerits for each merit sources. However, the 37% increases include all users in the forum, not only restricted to merit sources; and the increases likely come from at least two sides: - Merit sources' activities
- Normal users who have more actively used their sMerits with the Christmas and New year event.
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ABSTRACT 2019w51Data is the full dataset since 24/1/2018, and only dropped last two days belong to incomplete week - 2019w52. Details on days dropped, please see above posts.
Intra-day merits:(1) Potential outliers are days that have intraday total merits beyond 180 or 1140; (2) Median of intraday merits over the period is 644; (3) 50% of observed days have their intra-day merits range from 540 to 780 (the interquartile range); (4) In GTM time. In medians, the highest and lowest days are Monday and Friday, respectively; whilst the highest and lowest days in means are Wednesday and Saturday, respectively. See here. (5) There are 63 potential outliers (beyond 180 or 1140) in total, and only 16 of them occured in 2019. ( see details). (6) Minimum and maximum of intraday merits (full dataset) are 295, and 13018, on 03/8/2019 and 24/1/2018, respectively.
Intra-week merits:100 weeks in total. (1) The median of intra-week merits is 4525; (2) 50% of observed weeks ( 100 weeks in total), have total merits in the range from 4143 to 5243 (the interquartile range of intra-week merits). (3) Minimum and maximum of intra-week merits are 3072 and 30960, in 2018w35, and 2018w4, respectively; (4) 12 potential outliers [beyond 2477 or 6857], only 2 of them occurred in the year 2019, on 2019w46 ( 14251), and 2019w47 ( 17685).
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Intra-week merits (from 24/1/2018 to 23/12/2019)Last two days dropped due to incomplete weeks (2019w52)Converted dataset: +-----------------+
| 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 |
80. | 3549 2019w31 |
|-----------------|
81. | 3207 2019w32 |
82. | 4236 2019w33 |
83. | 3622 2019w34 |
84. | 3540 2019w35 |
85. | 3809 2019w36 |
|-----------------|
86. | 4043 2019w37 |
87. | 4520 2019w38 |
88. | 4318 2019w39 |
89. | 4357 2019w40 |
90. | 4565 2019w41 |
|-----------------|
91. | 5542 2019w42 |
92. | 4975 2019w43 |
93. | 4730 2019w44 |
94. | 4735 2019w45 |
95. | 14251 2019w46 |
|-----------------|
96. | 17685 2019w47 |
97. | 5907 2019w48 |
98. | 4524 2019w49 |
99. | 5186 2019w50 |
100. | 6194 2019w51 |
+-----------------+
- 50% of observed weeks ( 99 weeks) have total intra-week merits above 4525, whilst the rest 50% of them have total intra-week merits below 4525. 4525 is the median - p50. - 50% of observed weeks have total intra-week merits fluctuated in the range from 4143 to 5243 (the interquartile range, from p25 to p75, in raw statistics below). - Min - max: 3072 - 30960. variable | N mean sd p50 p25 p75 min max
-------------+--------------------------------------------------------------------------------
merit | 100.0 5510.2 3699.2 4525.5 4143.0 5242.5 3072.0 30960.0
----------------------------------------------------------------------------------------------
. di 5242.5-4143
1099.5
. di 1099.5*1.5
1649.25
. di 5242.5+1649.25
6891.75
. di 4143-1649.25
2493.75
It means that potential outliers are weeks that have intra-week merits beyond 2494 or 6892. How many weeks are potential outliers? . count if (merit >= 6892 | merit < 2494) & merit != .
12
weeks are outliers, in total. List of those 12 weeks: +-----------------+
| 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 |
|-----------------|
95. | 14251 2019w46 |
96. | 17685 2019w47 |
+-----------------+
Most of them occured in the year 2018, and there is only two outliers week occured in 2019, in 2019w46 (14251), 2019w47 ( 17685).  List of weeks in descending weekly meritsThe last week stays at the 16th position, among 100 weeks. +------------------------------+
| weeklyrank merit week |
|------------------------------|
1. | 1 30960 2018w4 |
2. | 2 19979 2018w5 |
3. | 3 17685 2019w47 |
4. | 4 14251 2019w46 |
5. | 5 13313 2018w6 |
|------------------------------|
6. | 6 11745 2018w7 |
7. | 7 8833 2018w9 |
8. | 8 8767 2018w8 |
9. | 9 7837 2018w38 |
10. | 10 7317 2018w11 |
|------------------------------|
11. | 11 7261 2018w10 |
12. | 12 6952 2018w12 |
13. | 13 6744 2018w13 |
14. | 14 6632 2019w2 |
15. | 15 6423 2018w14 |
|------------------------------|
16. | 16 6194 2019w51 |
17. | 17 6130 2019w13 |
18. | 18 5907 2019w48 |
19. | 19 5644 2018w37 |
20. | 20 5542 2019w42 |
|------------------------------|
21. | 21 5494 2018w15 |
22. | 22 5454 2019w19 |
23. | 23 5354 2019w24 |
24. | 24 5317 2019w3 |
25. | 25 5271 2019w15 |
|------------------------------|
26. | 26 5214 2019w20 |
27. | 27 5186 2019w50 |
28. | 28 4975 2019w43 |
29. | 29 4965 2018w18 |
30. | 30 4929 2018w25 |
|------------------------------|
31. | 31 4913 2019w10 |
32. | 32 4829 2018w42 |
33. | 33 4803 2019w1 |
34. | 34 4766 2018w19 |
35. | 35 4764 2019w18 |
|------------------------------|
36. | 36 4742 2018w16 |
37. | 37 4735 2019w45 |
38. | 38 4730 2019w44 |
39. | 39 4726 2019w25 |
40. | 40 4688 2019w16 |
|------------------------------|
41. | 41 4687 2019w23 |
42. | 42 4667 2019w4 |
43. | 43 4638 2019w9 |
44. | 44 4612 2018w17 |
45. | 45 4609 2019w12 |
|------------------------------|
46. | 46 4580 2019w21 |
47. | 47 4575 2018w47 |
48. | 48 4565 2019w41 |
49. | 49 4538 2018w23 |
50. | 50 4526 2019w14 |
|------------------------------|
51. | 51 4525 2018w45 |
52. | 52 4524 2019w49 |
53. | 53 4521 2019w8 |
54. | 54 4520 2019w38 |
55. | 55 4491 2019w5 |
|------------------------------|
56. | 56 4465 2018w26 |
57. | 57 4448 2019w17 |
58. | 58 4445 2019w22 |
59. | 59 4395 2018w39 |
60. | 60 4367 2019w26 |
|------------------------------|
61. | 61 4357 2019w40 |
62. | 62 4353 2018w20 |
63. | 63 4332 2019w6 |
64. | 64 4326 2019w11 |
65. | 65 4318 2019w39 |
|------------------------------|
66. | 66 4310 2018w40 |
67. | 67 4278 2018w27 |
68. | 68 4277 2019w29 |
69. | 69 4247 2018w28 |
70. | 70 4236 2019w33 |
|------------------------------|
71. | 71 4225 2019w27 |
72. | 72 4221 2019w7 |
73. | 73 4194 2018w22 |
74. | 74 4176 2019w30 |
75. | 75 4167 2018w29 |
|------------------------------|
76. | 76 4119 2019w28 |
77. | 77 4043 2019w37 |
78. | 78 4011 2018w32 |
79. | 79 3953 2018w43 |
80. | 80 3864 2018w21 |
|------------------------------|
81. | 81 3863 2018w31 |
82. | 82 3839 2018w24 |
83. | 83 3816 2018w41 |
84. | 84 3809 2019w36 |
85. | 85 3805 2018w34 |
|------------------------------|
86. | 86 3805 2018w50 |
87. | 87 3769 2018w51 |
88. | 88 3765 2018w48 |
89. | 89 3747 2018w46 |
90. | 90 3661 2018w30 |
|------------------------------|
91. | 91 3631 2018w33 |
92. | 92 3622 2019w34 |
93. | 93 3590 2018w36 |
94. | 94 3571 2018w49 |
95. | 95 3549 2019w31 |
|------------------------------|
96. | 96 3540 2019w35 |
97. | 97 3347 2018w44 |
98. | 98 3338 2018w52 |
99. | 99 3207 2019w32 |
100. | 100 3072 2018w35 |
+------------------------------+
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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 688, 675, and 669, respectively; whislt the lowest days are Friday, Saturday, and Sunday at 596, 615, and 626, respectively. - In means, the highest days are Wednesday, Thursday, and Monday at 929, 856, and 816, respectively; whilst the lowest days are Saturday, Friday, and Sunday, at 695, 705, and 754, respectively. 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. Summary for variables: merit
by categories of: dofw
dofw | N mean sd p50 p25 p75 min max
----------+--------------------------------------------------------------------------------
Sunday | 100.0 753.3 453.8 626.0 520.0 801.0 394.0 3190.0
Monday | 100.0 815.7 519.8 688.0 576.5 875.0 313.0 3854.0
Tuesday | 99.0 765.6 460.4 660.0 592.0 769.0 384.0 4193.0
Wednesday | 100.0 928.3 1353.5 668.5 566.5 790.0 394.0 13018.0
Thursday | 100.0 855.4 842.6 675.0 552.0 812.0 348.0 6762.0
Friday | 100.0 704.6 497.6 596.0 509.0 707.5 349.0 4500.0
Saturday | 100.0 694.8 402.2 614.5 497.0 723.5 295.0 3490.0
----------+--------------------------------------------------------------------------------
Total | 699.0 788.3 722.5 644.0 540.0 780.0 295.0 13018.0
-------------------------------------------------------------------------------------------
Outliers displayed as red circles. Outliers non-displayed. Details on ranks:In medians +--------------------------------------------------------------------------+
| rankmedian dofw median mean p25 p75 min max |
|--------------------------------------------------------------------------|
1. | 1 Monday 688 815.68 576.5 875 313 3854 |
2. | 2 Thursday 675 855.44 552 812 348 6762 |
3. | 3 Wednesday 668.5 928.32 566.5 790 394 13018 |
4. | 4 Tuesday 660 765.6263 592 769 384 4193 |
5. | 5 Sunday 626 753.32 520 801 394 3190 |
|--------------------------------------------------------------------------|
6. | 6 Saturday 614.5 694.84 497 723.5 295 3490 |
7. | 7 Friday 596 704.65 509 707.5 349 4500 |
+--------------------------------------------------------------------------+
In means +------------------------------------------------------------------------+
| rankmean dofw mean median p25 p75 min max |
|------------------------------------------------------------------------|
1. | 1 Wednesday 928.32 668.5 566.5 790 394 13018 |
2. | 2 Thursday 855.44 675 552 812 348 6762 |
3. | 3 Monday 815.68 688 576.5 875 313 3854 |
4. | 4 Tuesday 765.6263 660 592 769 384 4193 |
5. | 5 Sunday 753.32 626 520 801 394 3190 |
|------------------------------------------------------------------------|
6. | 6 Friday 704.65 596 509 707.5 349 4500 |
7. | 7 Saturday 694.84 614.5 497 723.5 295 3490 |
+------------------------------------------------------------------------+
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During the period from 24/1/2018 to 23/12/2019 (last two days dropped due to incomplete week), the minimum and maximum of intra-day merit are 295 and 13018, on 03/8/2019 and 24/1/2018, respectively. List of the top 50-highest day in terms of intra-day merits: +-------------------------------------------------------------------------------+
| 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. | 5412 667 21nov2019 Thursday 21 11 2019 2019w47 2019m11 |
4. | 5275 666 20nov2019 Wednesday 20 11 2019 2019w47 2019m11 |
5. | 4500 3 26jan2018 Friday 26 1 2018 2018w4 2018m1 |
|-------------------------------------------------------------------------------|
6. | 4193 7 30jan2018 Tuesday 30 1 2018 2018w5 2018m1 |
7. | 3854 664 18nov2019 Monday 18 11 2019 2019w46 2019m11 |
8. | 3800 6 29jan2018 Monday 29 1 2018 2018w5 2018m1 |
9. | 3490 4 27jan2018 Saturday 27 1 2018 2018w4 2018m1 |
10. | 3190 5 28jan2018 Sunday 28 1 2018 2018w4 2018m1 |
|-------------------------------------------------------------------------------|
11. | 2821 8 31jan2018 Wednesday 31 1 2018 2018w5 2018m1 |
12. | 2753 663 17nov2019 Sunday 17 11 2019 2019w46 2019m11 |
13. | 2569 10 02feb2018 Friday 2 2 2018 2018w5 2018m2 |
14. | 2546 9 01feb2018 Thursday 1 2 2018 2018w5 2018m2 |
15. | 2514 22 14feb2018 Wednesday 14 2 2018 2018w7 2018m2 |
|-------------------------------------------------------------------------------|
16. | 2510 660 14nov2019 Thursday 14 11 2019 2019w46 2019m11 |
17. | 2464 236 16sep2018 Sunday 16 9 2018 2018w37 2018m9 |
18. | 2310 14 06feb2018 Tuesday 6 2 2018 2018w6 2018m2 |
19. | 2182 665 19nov2019 Tuesday 19 11 2019 2019w47 2019m11 |
20. | 2182 12 04feb2018 Sunday 4 2 2018 2018w5 2018m2 |
|-------------------------------------------------------------------------------|
21. | 2143 16 08feb2018 Thursday 8 2 2018 2018w6 2018m2 |
22. | 2142 15 07feb2018 Wednesday 7 2 2018 2018w6 2018m2 |
23. | 2078 13 05feb2018 Monday 5 2 2018 2018w6 2018m2 |
24. | 1992 23 15feb2018 Thursday 15 2 2018 2018w7 2018m2 |
25. | 1868 11 03feb2018 Saturday 3 2 2018 2018w5 2018m2 |
|-------------------------------------------------------------------------------|
26. | 1863 237 17sep2018 Monday 17 9 2018 2018w38 2018m9 |
27. | 1748 18 10feb2018 Saturday 10 2 2018 2018w6 2018m2 |
28. | 1706 38 02mar2018 Friday 2 3 2018 2018w9 2018m3 |
29. | 1660 668 22nov2019 Friday 22 11 2019 2019w47 2019m11 |
30. | 1618 25 17feb2018 Saturday 17 2 2018 2018w7 2018m2 |
|-------------------------------------------------------------------------------|
31. | 1580 21 13feb2018 Tuesday 13 2 2018 2018w7 2018m2 |
32. | 1542 661 15nov2019 Friday 15 11 2019 2019w46 2019m11 |
33. | 1476 659 13nov2019 Wednesday 13 11 2019 2019w46 2019m11 |
34. | 1466 677 01dec2019 Sunday 1 12 2019 2019w48 2019m12 |
35. | 1449 17 09feb2018 Friday 9 2 2018 2018w6 2018m2 |
|-------------------------------------------------------------------------------|
36. | 1443 19 11feb2018 Sunday 11 2 2018 2018w6 2018m2 |
37. | 1441 662 16nov2019 Saturday 16 11 2019 2019w46 2019m11 |
38. | 1416 24 16feb2018 Friday 16 2 2018 2018w7 2018m2 |
39. | 1410 32 24feb2018 Saturday 24 2 2018 2018w8 2018m2 |
40. | 1404 27 19feb2018 Monday 19 2 2018 2018w8 2018m2 |
|-------------------------------------------------------------------------------|
41. | 1392 34 26feb2018 Monday 26 2 2018 2018w9 2018m2 |
42. | 1355 48 12mar2018 Monday 12 3 2018 2018w11 2018m3 |
43. | 1335 37 01mar2018 Thursday 1 3 2018 2018w9 2018m3 |
44. | 1332 20 12feb2018 Monday 12 2 2018 2018w7 2018m2 |
45. | 1327 35 27feb2018 Tuesday 27 2 2018 2018w9 2018m2 |
|-------------------------------------------------------------------------------|
46. | 1324 56 20mar2018 Tuesday 20 3 2018 2018w12 2018m3 |
47. | 1295 238 18sep2018 Tuesday 18 9 2018 2018w38 2018m9 |
48. | 1293 26 18feb2018 Sunday 18 2 2018 2018w7 2018m2 |
49. | 1280 30 22feb2018 Thursday 22 2 2018 2018w8 2018m2 |
50. | 1271 239 19sep2018 Wednesday 19 9 2018 2018w38 2018m9 |
|-------------------------------------------------------------------------------|
List of the top 50-lowest days in terms of intra-day merits: +-------------------------------------------------------------------------------+
| merit id date dofw day month2 year week month |
|-------------------------------------------------------------------------------|
1. | 295 557 03aug2019 Saturday 3 8 2019 2019w31 2019m8 |
2. | 313 335 24dec2018 Monday 24 12 2018 2018w52 2018m12 |
3. | 317 333 22dec2018 Saturday 22 12 2018 2018w51 2018m12 |
4. | 328 564 10aug2019 Saturday 10 8 2019 2019w32 2019m8 |
5. | 344 340 29dec2018 Saturday 29 12 2018 2018w52 2018m12 |
|-------------------------------------------------------------------------------|
6. | 348 298 17nov2018 Saturday 17 11 2018 2018w46 2018m11 |
7. | 348 338 27dec2018 Thursday 27 12 2018 2018w52 2018m12 |
8. | 349 304 23nov2018 Friday 23 11 2018 2018w47 2018m11 |
9. | 368 566 12aug2019 Monday 12 8 2019 2019w32 2019m8 |
10. | 371 122 25may2018 Friday 25 5 2018 2018w21 2018m5 |
|-------------------------------------------------------------------------------|
11. | 377 191 02aug2018 Thursday 2 8 2018 2018w31 2018m8 |
12. | 377 342 31dec2018 Monday 31 12 2018 2018w52 2018m12 |
13. | 379 326 15dec2018 Saturday 15 12 2018 2018w50 2018m12 |
14. | 380 220 31aug2018 Friday 31 8 2018 2018w35 2018m8 |
15. | 382 599 14sep2019 Saturday 14 9 2019 2019w37 2019m9 |
|-------------------------------------------------------------------------------|
16. | 384 217 28aug2018 Tuesday 28 8 2018 2018w35 2018m8 |
17. | 386 214 25aug2018 Saturday 25 8 2018 2018w34 2018m8 |
18. | 387 339 28dec2018 Friday 28 12 2018 2018w52 2018m12 |
19. | 394 341 30dec2018 Sunday 30 12 2018 2018w52 2018m12 |
20. | 394 568 14aug2019 Wednesday 14 8 2019 2019w33 2019m8 |
|-------------------------------------------------------------------------------|
21. | 395 529 06jul2019 Saturday 6 7 2019 2019w27 2019m7 |
22. | 395 345 03jan2019 Thursday 3 1 2019 2019w1 2019m1 |
23. | 396 228 08sep2018 Saturday 8 9 2018 2018w36 2018m9 |
24. | 398 320 09dec2018 Sunday 9 12 2018 2018w49 2018m12 |
25. | 399 558 04aug2019 Sunday 4 8 2019 2019w31 2019m8 |
|-------------------------------------------------------------------------------|
26. | 400 262 12oct2018 Friday 12 10 2018 2018w41 2018m10 |
27. | 403 329 18dec2018 Tuesday 18 12 2018 2018w51 2018m12 |
28. | 406 287 06nov2018 Tuesday 6 11 2018 2018w45 2018m11 |
29. | 407 556 02aug2019 Friday 2 8 2019 2019w31 2019m8 |
30. | 411 565 11aug2019 Sunday 11 8 2019 2019w32 2019m8 |
|-------------------------------------------------------------------------------|
31. | 413 403 02mar2019 Saturday 2 3 2019 2019w9 2019m3 |
32. | 413 222 02sep2018 Sunday 2 9 2018 2018w35 2018m9 |
33. | 414 527 04jul2019 Thursday 4 7 2019 2019w27 2019m7 |
34. | 416 278 28oct2018 Sunday 28 10 2018 2018w43 2018m10 |
35. | 416 533 10jul2019 Wednesday 10 7 2019 2019w28 2019m7 |
|-------------------------------------------------------------------------------|
36. | 416 588 03sep2019 Tuesday 3 9 2019 2019w36 2019m9 |
37. | 417 109 12may2018 Saturday 12 5 2018 2018w19 2018m5 |
38. | 417 592 07sep2019 Saturday 7 9 2019 2019w36 2019m9 |
39. | 417 587 02sep2019 Monday 2 9 2019 2019w35 2019m9 |
40. | 419 186 28jul2018 Saturday 28 7 2018 2018w30 2018m7 |
|-------------------------------------------------------------------------------|
41. | 421 187 29jul2018 Sunday 29 7 2018 2018w30 2018m7 |
42. | 422 192 03aug2018 Friday 3 8 2018 2018w31 2018m8 |
43. | 425 276 26oct2018 Friday 26 10 2018 2018w43 2018m10 |
44. | 427 140 12jun2018 Tuesday 12 6 2018 2018w24 2018m6 |
45. | 427 277 27oct2018 Saturday 27 10 2018 2018w43 2018m10 |
|-------------------------------------------------------------------------------|
46. | 429 313 02dec2018 Sunday 2 12 2018 2018w48 2018m12 |
47. | 429 418 17mar2019 Sunday 17 3 2019 2019w11 2019m3 |
48. | 431 284 03nov2018 Saturday 3 11 2018 2018w44 2018m11 |
49. | 431 264 14oct2018 Sunday 14 10 2018 2018w41 2018m10 |
50. | 433 221 01sep2018 Saturday 1 9 2018 2018w35 2018m9 |
|-------------------------------------------------------------------------------|
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Time-series plots:Full dataset:Truncated dataset:
Basic statistics (for full dataset): Only drop last two days that belong to the 2019w51, incomplete week. variable | N mean sd p50 p25 p75 min max
-------------+--------------------------------------------------------------------------------
merit | 699 788.3004 722.4836 644 540 780 295 13018
----------------------------------------------------------------------------------------------
Applied formulas in previous weeks, potential outliers are days have intra-day merits beyond 180 or 1140. . di 780-540
240
. di 240*1.5
360
. di 780+360
1140
. di 540-360
180
There are 63 outliers (beyond 1140 or 180) in full dataset, in total. . count if (merit >= 1140 | merit <= 180) & merit != .
63
Those days are: +-------------------------+
| id merit date |
|-------------------------|
1. | 1 13018 24jan2018 |
2. | 2 6762 25jan2018 |
3. | 3 4500 26jan2018 |
4. | 4 3490 27jan2018 |
5. | 5 3190 28jan2018 |
6. | 6 3800 29jan2018 |
7. | 7 4193 30jan2018 |
8. | 8 2821 31jan2018 |
9. | 9 2546 01feb2018 |
10. | 10 2569 02feb2018 |
11. | 11 1868 03feb2018 |
12. | 12 2182 04feb2018 |
13. | 13 2078 05feb2018 |
14. | 14 2310 06feb2018 |
15. | 15 2142 07feb2018 |
16. | 16 2143 08feb2018 |
17. | 17 1449 09feb2018 |
18. | 18 1748 10feb2018 |
19. | 19 1443 11feb2018 |
20. | 20 1332 12feb2018 |
21. | 21 1580 13feb2018 |
22. | 22 2514 14feb2018 |
23. | 23 1992 15feb2018 |
24. | 24 1416 16feb2018 |
25. | 25 1618 17feb2018 |
26. | 26 1293 18feb2018 |
27. | 27 1404 19feb2018 |
28. | 28 1170 20feb2018 |
29. | 29 1268 21feb2018 |
30. | 30 1280 22feb2018 |
32. | 32 1410 24feb2018 |
33. | 33 1187 25feb2018 |
34. | 34 1392 26feb2018 |
35. | 35 1327 27feb2018 |
37. | 37 1335 01mar2018 |
38. | 38 1706 02mar2018 |
41. | 41 1246 05mar2018 |
48. | 48 1355 12mar2018 |
50. | 50 1160 14mar2018 |
56. | 56 1324 20mar2018 |
57. | 57 1229 21mar2018 |
68. | 68 1258 01apr2018 |
69. | 69 1147 02apr2018 |
236. | 236 2464 16sep2018 |
237. | 237 1863 17sep2018 |
238. | 238 1295 18sep2018 |
239. | 239 1271 19sep2018 |
|-------------------------|
351. | 351 1162 09jan2019 |
428. | 428 1250 27mar2019 |
475. | 475 1151 13may2019 |
504. | 504 1188 11jun2019 |
659. | 659 1476 13nov2019 |
660. | 660 2510 14nov2019 |
661. | 661 1542 15nov2019 |
662. | 662 1441 16nov2019 |
663. | 663 2753 17nov2019 |
664. | 664 3854 18nov2019 |
665. | 665 2182 19nov2019 |
666. | 666 5275 20nov2019 |
667. | 667 5412 21nov2019 |
668. | 668 1660 22nov2019 |
669. | 669 1153 23nov2019 |
677. | 677 1466 01dec2019 |
+-------------------------+
Only 16 of them occured in 2019. See details in the list of outliers above.
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It depends on your definition of "full" and from my point of view a full node is something which stores the entire Blockchain including all past UTXOs as well as the complete database including mempool and past blocks.
I could be wrong but I totally agree with you on this. SPV wallets, ie. do not store the full blockchain, instead they only store block headers (not the block transactions). Consequently, as you said, they don't have fully details on UTXOs, and there are risks of double spend with SPV wallets. To overcome such attacks, they have to connect to the other nodes, and should be honest nodes on the network in order to avoid terrible connections to fake nodes or wrong blockchains, not real blockchain of bitcoin. In the other words, nodes are called as Full nodes (from my understandings) if they store the full blockchain, and therefore they have complete history of blockchain transactions (includes all UTXOs, as you said). Prune nodes, despite of the fact that they download and sync with all blockchain database, but such nodes automatically truncate their database over time. The level of database truncation on prune nodes depends on the N parameter setup by users. The smaller N parameter, the more severity of database truncation. Maybe someone will argue that prune node actually download the full blockchain, but the thing is download, sync, and store the full blockchain is very different. Full nodes always store the full blockchain at the last time point it synchronises with the network, whilst prune node always store the small part of the blockchain. |
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Transaction fee: -0.00054440 BTC
< ... >
Transaction total size: 2722 bytes
The fee is good, at 20 satoshis/ byte. Your transactions should be confirmed already. That is high enough to get confirmations fastly, according to 1, 2[1]: https://whatthefee.io/[2]: https://coinb.in/#feesIn addition, I saw that mempool looks good now, so if you move your coins correctly (correct bitcoin address), I guess it will be confirmed very soon from now. However, I think what nc50lc pointed out is right. Your transaction has not yet been broadcasted.
For your privacy, If you care about privacy, and that one (the image in that post) comes from your same wallet, I believe you should blur or hide those addresses. I did not quote that image, just in case you decide to delete it. |
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It's not. That's the blocks dir (blocks only), you're forgetting the chainstate (which you need for a prune node too). It sits slightly over 3.5 GB for me on a full node now, thus you'd need at least 5 GB (3.5 GB chainstate + 2 GB blocks) of total storage for the pruned one.
Thank you. To sum up, to run a prune node with minimum storage value (2GB), one need to have at least 3.5 GB - for chainstate + 2GB - for blocks + 52.1 MB for initial setup (image below).
1) a pruned node downloads the entire blockchain but only stores a small portion of it (from the end).
a pruned node Can also relay new transactions and new blocks and the old blocks that it has to other nodes (routing?)
a pruned node can also be used as the backend for mining and can be used as a wallet.
2) this is the only difference.
3) a pruned node can also do it by verifying the entire blockchain and the new blocks and transactions while rejecting anything invalid and relaying valid ones to other nodes.
4) you have the chainstate and can always use bloom filters to get your history so i don't think you technically need to resync from scratch if you imported a new wallet. although i have never done it with bitcoin core to see what happens.
Despite of there are some overlayed functionality between full node and prune node, they are different. A full node means it has four functionalities at the same time: routing, complete blockchain database, mining, and wallet services. Importantly, without the complete blockchain database, a prune node will never become a full node. But when someone set up the n parameter for prune node to the one of full node, it turns to be a full node, and no longer be a prune node. Unfortunately, it will become a full node shortly because when time goes longer, that n parameter will become less than the complete blockchain-size, and that node will be degraded to a prune node, again. Prune node can be a mining node, I agree because a mining node theoritically comes from a full node (stores the complete blockchain) or a lightweight node (does not mandatorily store blockchain database, it depends on a pool server). |
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Prune node
Pros:
Required only 2 GB by default.
This is wrong though. With the chainstate I believe the minimum is between 5 to 10 GB, but you should verify if you want exact numbers. That's it. They are required storage space for today: 284 GB for a full node, and 2 GB for a prune node. 2GB is the default value of storage space (for now), when you run a prune node. As you see, when I want to modify and expand the storage space of my prune node, the default value shows 2GB. I guess 2GB is the minimum value for a prune node. |
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"Routing Node"? What is this? Bitcoin nodes are not Onion Nodes; that is a term I haven't seen someone us to describe nodes.
That is what I got from Mastering Bitcoin - chapter 6 (A. Antonopoulos) All nodes include the routing function to participate in the network and might include other functionality. All nodes validate and propagate transactions and blocks, and discover and maintain connections to peers. In the full-node example in Figure 6-1, the routing function is indicated by an orange circle named “Network Routing Node.”
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