Hello dear Hivers,
here are the:
$BEER Statistics For The Last 7 Days, 2024-09-13 to 2024-09-20:
Who has bought how many $BEER at which time:
Top $BEER Buyers And $HIVE Sellers
The inside of the circle shows the buyers of $BEER, ordered by $HIVE they have spent. The outside shows the recipients of that $HIVE (sellers of $BEER):
Comulated Amount Of Bought $BEER Per Person
Top 10 $BEER buyers, how much they got and how much $HIVE they spend for this. Sorted by $HIVE, that was spent:
Top 20 $BEER Buyers
Sorted by the $HIVE, they have spent:
| Buyer(Descending) | Sold $HIVE | % Sold $HIVE | Bought $BEER | Avg. Price | Number of Trades |
|---|---|---|---|---|---|
 @keychain.swap | 26.89700 | 52.62 % | 320.76615 | 0.08351 | 8 |
 @imagenius.dac | 9.90572 | 19.38 % | 365.26166 | 0.02688 | 3 |
 @intacto | 4.77670 | 9.34 % | 174.19107 | 0.02691 | 22 |
 @edkarnie | 3.12777 | 6.12 % | 119.38030 | 0.02620 | 3 |
 @god-0 | 2.80398 | 5.49 % | 97.42235 | 0.02856 | 8 |
 @master-lamps | 1.19191 | 2.33 % | 41.27114 | 0.02888 | 1 |
 @pepetoken | 0.98350 | 1.92 % | 35.00000 | 0.02810 | 1 |
 @methus | 0.70633 | 1.38 % | 25.00000 | 0.02825 | 1 |
 @hivecurious | 0.46400 | 0.91 % | 16.00000 | 0.02900 | 1 |
 @pepentropy | 0.26200 | 0.51 % | 10.00000 | 0.02620 | 1 |
 @ironshield | 0.00033 | 0.00 % | 0.01250 | 0.02640 | 1 |
| others | 0 | 0.00 % | 0 | 0.00000 | 0 |
| Sum: | 51.11924 | 100 % | 1204.30517 | 0.03589 | 50 |
Comulated Amount Of Sold $BEER Per Person
Top 10 $BEER Sellers, how much they sold and how much $HIVE they got for this, sorted by $HIVE:
Top 20 $BEER Sellers
Sorted by the $HIVE, they have got:
| Seller(Descending) | Earned $HIVE | % Earned $HIVE | Sold $BEER | Avg. Price | Number of Trades |
|---|---|---|---|---|---|
 @johannpiber | 22.75471 | 44.51 % | 829.64545 | 0.02787 | 19 |
| @intacto | 22.36531 | 43.75 % | 267.53404 | 0.07532 | 7 |
 @kryptodenno | 4.14760 | 8.11 % | 49.29461 | 0.08414 | 1 |
 @pixelfan | 0.56920 | 1.11 % | 20.00000 | 0.02765 | 2 |
 @tryagain.ordie | 0.41049 | 0.80 % | 4.93750 | 0.08314 | 1 |
 @mcbot | 0.32393 | 0.63 % | 12.26904 | 0.02640 | 2 |
 @thedrummerboy | 0.14038 | 0.27 % | 5.31726 | 0.02640 | 1 |
 @acidyo | 0.13875 | 0.27 % | 5.25514 | 0.02640 | 1 |
 @tomsmaid | 0.09617 | 0.19 % | 3.64273 | 0.02640 | 1 |
| @keychain.swap | 0.06352 | 0.12 % | 2.40575 | 0.02640 | 1 |
 @lxsxl | 0.04047 | 0.08 % | 1.53300 | 0.02640 | 1 |
 @sylmarill | 0.02239 | 0.04 % | 0.77500 | 0.02889 | 1 |
| cwow2 | 0.01636 | 0.03 % | 0.56622 | 0.02889 | 1 |
 @ugochill | 0.01060 | 0.02 % | 0.40161 | 0.02640 | 1 |
 @itharagaian | 0.00957 | 0.02 % | 0.36250 | 0.02640 | 1 |
 @osiriss | 0.00630 | 0.01 % | 0.23867 | 0.02640 | 1 |
 @berthold | 0.00194 | 0.00 % | 0.06711 | 0.02889 | 1 |
 @cursephantom | 0.00065 | 0.00 % | 0.02500 | 0.02620 | 1 |
 @birdwatcher | 0.00033 | 0.00 % | 0.01250 | 0.02640 | 1 |
 @bulliontools | 0.00033 | 0.00 % | 0.01250 | 0.02640 | 1 |
| others | 0.00026 | 0.00 % | 0.00955 | 0.03960 | 4 |
| Sum: | 51.11926 | 100 % | 1204.30518 | 0.03548 | 50 |
Price Of The $BEER
$BEER Summarize Metrics
| Request | Received Hive | Received HIVE % | Sold $BEER | Avg. Price |
|---|---|---|---|---|
| buy | 26.89733 | 52.62% | 320.77865 | 0.07717 |
| sell | 24.22193 | 47.38% | 883.52651 | 0.02732 |
| sum: | 51.11926 | 100% | 1204.3051600000001 | 0.05224 |
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.
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
Last Friday was the funeral of my Father in law.
Saturday my brother and me mowed weeds at our flat. We were visited from this nice guy:
In the evening we had BBQ with our family at home.
Sunday I cooked Paela in the garden, also with my family, so we had a good and lazy weekend.
Tuesday I was in Bonn with my "Green Code Team" and we had very good discussions about how to safe some CO2 with intelligent software solutions.
Here is a book hint:
In the night I slept here:
The next day I went to Würzburg for a meeting with my new team.
I waited more that one hour for my train, which set me out in the middle of nowhere (Bad Breisig). The following train also ended up in nothing. A woman next to me said "I go on by car. Who wants to join me?" so I went with her to Koblenz. There I got by luck a train, which was also too late. I arrived 3 hours to late for my first visit in the Company. 4 hours later I went back. So I sat 13 hours of the day in trains. Germany has been in better conditions (not only with the trains).
The next two weeks there will be no statistics!
Regards,
Achim Mertens