Hello dear Hivers,

here are the:

$LEO Statistics For The Last 7 Days, 2024-08-30 to 2024-09-06:

Who has bought how many $LEO at which time:

Top $LEO Buyers And $HIVE Sellers

The inside of the circle shows the buyers of $LEO, ordered by $HIVE they have spent. The outside shows the recipients of that $HIVE (sellers of $LEO):

Comulated Amount Of Bought $LEO Per Person

Top 10 $LEO buyers, how much they got and how much $HIVE they spend for this. Sorted by $HIVE, that was spent:

Top 20 $LEO Buyers

Sorted by the $HIVE, they have spent:

Buyer(Descending)	Sold $HIVE	% Sold $HIVE	Bought $LEO	Avg. Price	Number of Trades
@jelly-cz	1989.73790	34.87 %	12391.79903	0.16046	94
@konvik	1090.72583	19.12 %	6809.23100	0.15981	10
@all.coin.hive	627.19022	10.99 %	3925.40098	0.15962	48
@uscrypton	541.18169	9.48 %	3370.63405	0.15992	24
@sbi-tokens	289.58497	5.07 %	1833.97694	0.15790	3
@ganjafarmer	237.55349	4.16 %	1483.24499	0.16020	61
@mcbot	222.78950	3.90 %	1393.79100	0.16024	47
@mightpossibly	186.24976	3.26 %	1154.76499	0.16179	20
@jongolson	90.28400	1.58 %	561.00501	0.16084	17
@leotaker	79.98137	1.40 %	498.94100	0.16022	54
@balina	62.71625	1.10 %	391.92200	0.16019	96
@god0	51.76984	0.91 %	327.50400	0.15894	5
@enginemaker	50.00003	0.88 %	312.35800	0.16007	3
@edkarnie	24.07000	0.42 %	150.00000	0.16045	8
@ahmadmanga	22.55287	0.40 %	140.00000	0.16104	3
@bradleyarrow	20.86966	0.37 %	127.95300	0.16310	2
@keychain.swap	17.08951	0.30 %	105.45900	0.16204	4
@cursedellie	16.58622	0.29 %	103.36600	0.16040	5
@mmrx	14.32191	0.25 %	89.40000	0.16027	5
@freecompliments	11.26738	0.20 %	70.00000	0.16096	4
others	59.59440	1.04 %	371.73300	0.16845	99
Sum:	5706.11680	100 %	35612.48399	0.16454	612

Comulated Amount Of Sold $LEO Per Person

Top 10 $LEO Sellers, how much they sold and how much $HIVE they got for this, sorted by $HIVE:

Top 20 $LEO Sellers

Sorted by the $HIVE, they have got:

Seller(Descending)	Earned $HIVE	% Earned $HIVE	Sold $LEO	Avg. Price	Number of Trades
@konvik	1626.87960	28.51 %	10128.19499	0.16061	45
@all.coin.hive	723.04159	12.67 %	4486.71206	0.16137	19
@sbi-tokens	567.60923	9.95 %	3534.74201	0.16058	7
@uscrypton	561.45422	9.84 %	3534.82496	0.15959	14
@sepracore	401.61881	7.04 %	2524.92998	0.15961	5
@keychain.swap	237.90196	4.17 %	1490.28899	0.16030	32
@ganjafarmer	214.15104	3.75 %	1339.09699	0.16061	12
@kolbjorn	194.61303	3.41 %	1212.71500	0.16100	8
@god0	110.60356	1.94 %	685.74101	0.16145	7
@uyobong	81.97918	1.44 %	513.36300	0.15972	30
@leotaker	79.98107	1.40 %	497.01300	0.16104	58
@tomhall	77.24686	1.35 %	483.45300	0.15976	11
@silvergoldhunter	56.48464	0.99 %	355.13700	0.15947	5
@enginemaker	50.41867	0.88 %	312.23400	0.16148	2
@moof	47.44456	0.83 %	300.47200	0.15790	3
@phortun	39.32095	0.69 %	244.86800	0.16058	3
@cursedellie	38.04641	0.67 %	235.86700	0.16103	21
@stiant	36.77316	0.64 %	230.59800	0.15984	3
@brando28	36.60507	0.64 %	227.95500	0.16058	3
@vimukthi	36.05669	0.63 %	225.67700	0.15975	4
others	487.88653	8.55 %	3048.60101	0.16157	320
Sum:	5706.11683	100 %	35612.48400	0.16138	612

Price Of The $LEO

$LEO Summarize Metrics

Request	Received Hive	Received HIVE %	Sold $LEO	Avg. Price
sell	3980.54386	69.76%	24859.60993	0.16019
buy	1725.57293	30.24%	10752.87406	0.16084
sum:	5706.11679	100%	35612.48399	0.16052

---

Comparison With Other Tokens

$HIVE/Token

This figure shows the value of $HIVE compared to some tokens. Be aware of the nonlinear (root square) y-axes.

US-Dollar/Token

Value of $USD compared to some token. Be aware of the nonlinear (root square) y-axes.

Origin

Table Of Token Prices in $HIVE and $USD

Average value of the prices of the token. Hive and US-Dollar compared to the token:

---

Links:

How I Have Set Up Elasticsearch And Kibana On My Raspberry Pi To Monitor Token Activities and here: Do You Want To See Statistics Of Your Favorite HIVE Token? or on github.

@advertisingbot2/posts?filter=stats
@achimmertens

https://github.com/achimmertens

---

My last Week

I MADE IT!!! For month I was mourning, that I struggle with LLM AI Finetuning: The library dependencies didn't fit, my (and Collab-) hardware was too small, or the solution was too expensive. This week I made the breakthrough. Here I explain how I managed to finetune an LLM via OpenAI. There next thing is to find and prepare some good training data - but that is feasible.
The was also another milestone in my life this week. Last Sunday my wife and me were for the first time without children because they were all out with their partners - new and strange feeling ;-).
Wednesday @ayleensatelier sang in a wonderfull choir:

And on Thursday @ayleensatelier had a market stand in her town Stolberg and could sell her art.

Regards,

Achim Mertens