Bounty Question

Osmosis is far and away the liquidity hub of the Cosmos. Axelar is acting as the primary liquidity bridge into ecosystem. Analyze activity on Osmosis once a user bridges via Axlear's Satellite. What asset do they most use to bridge? Once bridged what do they do next?

The Launch of Satellite

Satellite, one of the first ecosystem applications powered by the Axelar Network. Satellite is a decentralized cross-chain asset transfer application, which enables users to transfer assets they hold on a source chain to an address on a different destination chain.

Upon launch, Satellite will support the transfer of native Terra assets such as LUNA and UST between several EVM and non-EVM chains such as Terra, Avalanche, Polygon, Ethereum and Fantom, with Moonbeam added shortly thereafter. Multiple networks and assets will be added in the coming weeks and months.

Satellite is the first app to demonstrate that Axelar connects all Cosmos chains via IBC and its GCP protocol with multiple ecosystems. Axelar serves as the translation layer that allows Cosmos assets to flow freely to all Axelar-interconnected networks and back. Axelar supports routing, finalizing and executing transactions in different “languages”.

Why Satellite?

Web3 is growing. Today there are more blockchains, assets, decentralized applications and users than ever before. According to Electric Capital’s Annual Developer Report, 34,000 new developers began contributing to blockchain projects in 2021 — the largest single year increase ever.

As the ecosystem grows, the infrastructure to support this influx of talent, innovation, energy and capital must develop as well.

We built Satellite to connect this growing ecosystem, to provide end users with a simpler, more decentralized transfer experience and to demonstrate to developers what the Axelar Network is capable of.

Osmosis: A Fully Customizable, Cross-Chain AMM Built on Cosmos

Most existing AMMs are confined to operate within the native blockchain in which they were originally built. While there are workarounds, this places certain limitations on developing a truly chain-agnostic AMM that can execute transactions across different networks seamlessly and efficiently. In addition, while the features between AMMs can vary quite significantly, they are often hardcoded into the protocol, leaving a rigid infrastructure that is unable to adapt quickly to the demands of an ever-changing market. Developers very rarely have the freedom to change key parameters like swap fees, token weights, let alone the more infrastructure-drive values such as the curve algorithm or TWAP calculation.

For instance, popular AMMs like Uniswap V3 allow users to create liquidity pools with different fee sizes, specifically between 0.3% and 1%. This creates a bit of a quality of life improvement for casual users in that they are not required to spend time tinkering with the underlying tokenomics and implications of a given set of LP fees. It also provides some flexibility and is useful in cases that involve more exotic token pairs. For more sophisticated users, however, additional parameterization might be useful to better react to changing market conditions. This approach also shifts the focus of fee structures away from how common or how rare a given token pair is to be more comprehensive by including other factors such as slippage and market volatility. Ultimately, there is no single solution that fits all AMM design goals, and an additional layer of customization helps developers fine-tune optimal strategies around fees and liquidity provision, and takes into account other factors that may directly impact success of the AMM.

Osmosis attempts to solve these shortcomings in many different ways. To begin, the protocol was developed using the Cosmos SDK which allows it to operate across chains. This gives Osmosis access to any chain built on the Cosmos ecosystem which unlocks over $10B in TVL. It also allows Osmosis to integrate with non-IBC enabled chains, such as Ethereum, giving it even more composability and interoperability.

From a design perspective, Osmosis is focused on user experience and a deep level of customization. The protocol extends AMM functionality beyond simply token swaps and implements a host of other features such as bonding curves, dynamic fee swaps, and multi-token liquidity pools. It therefore enables developers to build, design, and deploy their very own AMM, fully customized with novel parameters and fully connected to the IBC ecosystem and beyond.

Some of the more interesting features include liquidity pools that are not limited to 50-50 token pair composition. Instead, developers are free to experiment with different designs, such as a 60-40 split. More broadly, Osmosis enables developers to implement changes around everything from token weights and swap fees to the AMM curve to determine which iteration works best. They also have the tools to quickly adjust these features (as quickly as one week) as market conditions change. The concept of deep customization is important because it allows for a truly decentralized AMM framework and lets market participants determine the optimal equilibrium between fees and liquidity, rather than being relegated to rigid protocol parameters that attempt to determine it for them

Methodology

In reviewing the dashboards of others and the methods used by them, it seemed to me that some currencies are not included in the calculations when checking the currencies with the adopted methods. Therefore, although it was not an optimal method in my opinion, due to my lack of mastery of SQL and the limited number of these currencies, I decided to check the currencies in "Bridge to" and "Bridge from" Satellite manually by Axelar Explorer. In this review, I checked a number of transactions from each of these currencies in the explorer and matched the symbols of the currencies with their symbols in the osmosis.core.dim_prices table. By doing this, I imagine that it is possible to both check all currencies and get a more accurate estimated $ value of these bridges.

• In the osmosis.core.dim_prices table, there are 66 currencies whose daily prices can be checked.

• In the "bridge to" Satellite, there are 54 currencies that are bridged to it from other interchains. Out of these 54, 28 currencies do not exist in the dim_prices table and it is not possible to get the $ value of the bridges containing these currencies. But 26 other currencies can be calculated. (that is, 48.14% of all currencies bridged to Satellite).

• There are 31 currencies that have been bridged from Satellite to other interchains. Out of these 31, 11 currencies do not exist in the dim_prices table and it is not possible to obtain the $ value of the bridges containing these currencies. But 20 other currencies can be calculated. (that is, 64.5% of all currencies bridged from Satellite).

• But the promising thing is that the most used and important currencies in bridges are present in the dim_prices table, and for this reason, it is possible to get a good estimate of what happened in Satellite Bridge.

The analysis was done as follows:

• In the first step, I have presented an overview of my findings from Satellite Bridge. In two tables, one related to "Bridge to" and the other related to "Bridge from", the last 1000 transactions related to each of these sectors are placed. This section is just a preview of what is going to be used and will help me in further analysis.

• In the second step, the status of the bridges to and from Axelar were checked through the Satellite Bridge. In this survey, all the currencies that participated in these bridges were examined. The number of transactions, the number of users and the volume of USD for each of these currencies were also calculated. Bridge to and bridge from Axelar were also compared with these three parameters.

• In the third step, bridges to and from Osmosis through Satellite Bridge were checked. In this survey, both the general condition and the daily condition of these bridges were determined. In addition, currencies were also included in this review to determine their daily trends.

• In the fourth step, it was checked what activities users do in the first transaction after bridging their currencies to Osmosis. These activities were investigated in two parts. In the first part (actions), using the tables related to each action, the data related to the first transaction after the bridge was determined. The point here is that in the method adopted by us, the first transaction of each user in each of the separate tables is obtained after bridging them. For this reason, it cannot be considered an accurate measure of what bridgers do in the first transaction after bridging. For this reason, the second part (Occurrings) was addressed to provide us with a more accurate view of what happened. However, here too, because each transaction may have more than 1 row in this table, and each row generally has a separate MSG_TYPE, the numbers obtained for each MSG_TYPE cannot give an accurate view of what actually happened. give us But since it can show us the first transaction after the bridge, then its results can give us a view closer to reality than the first part. I'm maturing into finding post-bridge transactions and I find it a very interesting topic. But it requires a more precise level of SQL usage, which I am trying to reach in the near future.

Base Query For “Bridge To” Axelar

with price_table as (
  select 
  	date(recorded_at) as DATE,
	lower (symbol) as SYMBOL,
	avg (price) as DAILY_PRICE
from osmosis.core.dim_prices
group by 1,2),
from_axelar as (
select
  date(BLOCK_TIMESTAMP) as BLOCK_TIMESTAMP,
  case currency 
  when 'aevmos' then 'evmos'
  when 'afet' then 'fet'
  when 'dai-wei' then 'axldai'
  when 'dot-planck' then 'xcdot' --no exist
  when 'eeur' then 'eeur'
  when 'inj' then 'inj'
  when 'uatom' then 'atom'
  when 'uaxl' then 'axl'
  when 'wbtc-satoshi' then 'axlwbtc'
  when 'usdt' then 'sdt' --no exist
  when 'wei' then 'wei' --no exist
  when 'mkr-wei' then 'axlmkr' --no exist
  when 'factory:kujira1qk00h5atutpsv900x202pxx42npjr9thg58dnqpa72f2p7m2luase444a7:uusk' then 'factory1' --no exist
  when 'gravity0xC02aaA39b223FE8D0A0e5C4F27eAD9083C756Cc2' then 'gravity1' --no exist
  when 'gravity0xA0b86991c6218b36c1d19D4a2e9Eb0cE3606eB48' then 'gravity2' --no exist
  when 'gravity0x6B175474E89094C44Da98b954EedeAC495271d0F' then 'gravity3' --no exist
  when 'uluna' then 'luna'
  when 'ukuji' then 'kuji'
  when 'umntl' then 'mntl'
  when 'ustars' then 'stars'
  when 'uregen' then 'regen'
  when 'uusdt' then 'usdt'  --no exist
  when 'uumee' then 'umee'
  when 'uusd' then 'usd'  --no exist
  when 'ungm' then 'ngm'
  when 'ucre' then 'cre'  --no exist
  when 'uosmo' then 'osmo'
  when 'ujuno' then 'juno'
  when 'uusdc' then 'axlusdc'
  when 'weth-wei' then 'axlweth'
  when 'uxki' then 'xki'
  when 'cmatic' then 'cmatic'  --no exist
  when 'cusdc' then 'cusdc'  --no exist
  when 'echf' then 'echf'  --no exist
  when 'edkk' then 'edkk' --no exist
  when 'enok' then 'enok' --no exist
  when 'frax-wei' then 'frax-wei' --no exist
  when 'link-wei' then 'link-wei' --no exist
  when 'steth-wei' then 'steth-wei' --no exist
  when 'uatolo' then 'uatolo' --no exist
  when 'ubcre' then 'bcre' --no exist
  when 'ubld' then 'bld' --no exist
  when 'ucmdx' then 'cmdx'
  when 'uion' then 'ion'
  when 'ubcna' then 'bcna'
  when 'uscrt' then 'scrt'
  when 'uusdc' then 'usdc'
  when 'uxprt' then 'xprt'
  when 'wavax-wei' then 'wavax-wei'  --no exist
  when 'wbnb-wei' then 'wbnb-wei'  --no exist
  when 'wftm-wei' then 'wftm-wei'  --no exist
  when 'wglmr-wei' then 'wglmr-wei'  --no exist
  when 'wmatic-wei' then 'wmatic-wei'  --no exist
  when 'esek' then 'esek'  --no exist
  end as ASSET_NAME,
  TX_ID,
  TRANSFER_TYPE,
  SENDER,
  RECEIVER,
  regexp_substr (SENDER,'[a-zA-Z]+|\d+') as ORIGIN,
  regexp_substr (RECEIVER,'[a-zA-Z]+|\d+') as DESTINATION,
  (amount/pow(10 , decimal)) as BRIDGE_AMOUNT

from axelar.core.fact_transfers
where transfer_type in ('IBC_TRANSFER_IN')
and TX_SUCCEEDED = 'TRUE')

select 
  BLOCK_TIMESTAMP,
  ASSET_NAME,
  TX_ID,
  TRANSFER_TYPE,
  ORIGIN,
  DESTINATION,
  SENDER,
  RECEIVER,
  BRIDGE_AMOUNT,
  (BRIDGE_AMOUNT * DAILY_PRICE) as USD_AMOUNT
from from_axelar
full join price_table on SYMBOL = ASSET_NAME and DATE = BLOCK_TIMESTAMP
limit 1000

Base Query For “Bridge From” Axelar

with price_table as (
  select 
  	date(recorded_at) as DATE,
	lower (symbol) as SYMBOL,
	avg (price) as DAILY_PRICE
from osmosis.core.dim_prices
group by 1,2),
from_axelar as (
select
  date(BLOCK_TIMESTAMP) as BLOCK_TIMESTAMP,
  case currency 
  when 'aevmos' then 'evmos'
  when 'afet' then 'fet'
  when 'dai-wei' then 'axldai'
  when 'dot-planck' then 'xcdot' --no exist
  when 'eeur' then 'eeur'
  when 'inj' then 'inj'
  when 'uatom' then 'atom'
  when 'uaxl' then 'axl'
  when 'wbtc-satoshi' then 'axlwbtc'
  when 'usdt' then 'sdt' --no exist
  when 'wei' then 'wei' --no exist
  when 'mkr-wei' then 'axlmkr' --no exist
  when 'factory:kujira1qk00h5atutpsv900x202pxx42npjr9thg58dnqpa72f2p7m2luase444a7:uusk' then 'factory1' --no exist
  when 'gravity0xC02aaA39b223FE8D0A0e5C4F27eAD9083C756Cc2' then 'gravity1' --no exist
  when 'gravity0xA0b86991c6218b36c1d19D4a2e9Eb0cE3606eB48' then 'gravity2' --no exist
  when 'gravity0x6B175474E89094C44Da98b954EedeAC495271d0F' then 'gravity3' --no exist
  when 'uluna' then 'luna'
  when 'ukuji' then 'kuji'
  when 'umntl' then 'mntl'
  when 'ustars' then 'stars'
  when 'uregen' then 'regen'
  when 'uusdt' then 'usdt'  --no exist
  when 'uumee' then 'umee'
  when 'uusd' then 'usd'  --no exist
  when 'ungm' then 'ngm'
  when 'ucre' then 'cre'  --no exist
  when 'uosmo' then 'osmo'
  when 'ujuno' then 'juno'
  when 'uusdc' then 'axlusdc'
  when 'weth-wei' then 'axlweth'
  when 'uxki' then 'xki'
  end as ASSET_NAME,
  TX_ID,
  TRANSFER_TYPE,
  SENDER,
  RECEIVER,
  regexp_substr (SENDER,'[a-zA-Z]+|\d+') as ORIGIN,
  regexp_substr (RECEIVER,'[a-zA-Z]+|\d+') as DESTINATION,
  (amount/pow(10 , decimal)) as BRIDGE_AMOUNT
  
from axelar.core.fact_transfers
where transfer_type in ('IBC_TRANSFER_OUT')
and TX_SUCCEEDED = 'TRUE')

select 
  BLOCK_TIMESTAMP,
  ASSET_NAME,
  TX_ID,
  TRANSFER_TYPE,
  ORIGIN,
  DESTINATION,
  SENDER,
  RECEIVER,
  BRIDGE_AMOUNT,
  (BRIDGE_AMOUNT* DAILY_PRICE) as USD_AMOUNT
from from_axelar
full join price_table on SYMBOL = ASSET_NAME and DATE = BLOCK_TIMESTAMP

Satellite Bridge Overview: Bridges Count

• The number of bridges from other interchains to Axelar is 2.24 x the number of bridges from Axelar to other interchains.

• Among the 31 tokens that have been bridged from Axelar, the top 5 are these currencies:
  • axl
  • axlusdc
  • xki
  • axlweth
  • axlwbtc

• "axl" bridges (with more than 67.7k bridges from Axelar):
  • 14.26 x "axlusdc" bridges with 4750 bridges
  • 24.37 x "xki" bridges with 2780 bridges
  • 40.79 x "axlweth" bridges with 1661 bridges
  • 88 x "axlwbtc" bridges with 770 bridges

• Among the 53 tokens that have been bridged from Axelar, the top 5 are these currencies:
  • usd
  • axlusdc
  • luna
  • axl
  • axlweth

• "usd" bridges (with more than 60k bridges to):
  • 1.14 x “axlusdc" bridges with 52.874k bridges
  • 1.65 x "luna" bridges with 36.395k bridges
  • 6.33 x "axl" bridges with 9.515k bridges
  • 12.91 x the bridges of "axlweth" with 4.663k bridges

• About 70% of all bridges from Axelar to other interchains were with "axl"! While more than 34.5% of all bridges to Axelar from other interchains were with "usd".

• The above numbers and ratios show that the difference between the currencies in bridge from Axelar is very large compared to bridge to Axelar . In bridge from Axelar, there is a very clear advantage with axl, in the case of bridge from Axelar , this level of difference cannot be observed between currencies.

• 21 currencies out of 53 currencies that have been bridged to Axelar have had less than 10 bridges!

• 20 of the 31 currencies that have been bridged to Axelar have had less than 10 bridges!

Part I: Satellite Bridge Overview

Part II: From Osmosis

Part 0: Preview

Satellite Bridge Overview: Bridgers Count

• The number of bridgers who have bridged currency from interchains to Axelar is 41.64 times the number of bridgers who have bridged from Axelar to other interchains.

• Among the 31 currencies bridged from Axelar, the top 5 currencies by the number of bridgers are:
  • axl
  • axlusdc
  • axlweth
  • atom
  • axlwbtc

• Bridgers "axl" (1624 bridgers from Axelar):
  • 9.78 times "axlusdc" bridgers with 166 bridgers
  • 56 times "axlweth" bridgers with 29 bridgers
  • 95.5 times "atom" bridgers with 17 bridgers
  • 116 times "axlwbtc" bridgers with 14 bridgers

• Among the 53 tokens bridged by bridgers to Axelar, the top 5 currencies by number of bridgers are:
  • usd
  • luna
  • axlusdc
  • axl
  • axlweth

• "usd" bridgers (with more than 33.05k bridgers to Axelar):
  • 1.42 times the bridgers of "luna" with 23.296k bridgers
  • 2.14 times "axlusdc" bridgers with 15.412k bridgers
  • 9.17 times "axl" bridgers with 3.603k bridgers
  • 20.29 times "axlweth" bridgers with 1.629k bridgers

• About 84.5% of all bridgers from Axelar to other interchains have bridged "axl"! While more than 41.2 percent of all bridgers have bridged "usd" to Axelar from other interchains.

• The above numbers and ratios show that the difference between currencies in the number of bridgers from Axelar is large compared to the number of bridgers to Axelar. In the bridge from Axelar, there is a very clear advantage with the number of axl bridgers, where in the case of bridge from Axelar, this level of difference between currencies cannot be seen at all.

• 30 out of 53 currencies bridged to Axelar had less than 10 bridgers!

• Only 5 currencies out of 31 bridged currencies from Axelar have more than 10 bridgers.

• In the number of bridges, compared to the number of bridges, the distance between currencies has increased in the mentioned proportions. This could be seen at the first glance from the pie chart that the ratio of 2.24 times has changed to 41.24 times.

Satellite Bridge Overview: Bridge Volume

• The volume of USD bridges that have been bridged from interchains to Axelar is 25.69 times the volume of USD bridges that have been bridged from Axelar to other interchains.

• Among the 31 currencies that have been bridged from Axelar, 17 currencies have been present in the price table. The top 5 currencies in terms of USD volume of bridges are:
  • inj
  • axl
  • axlusdc
  • axlweth
  • axlwbtc

• USD volume of "inj" bridges from Axelar ($7.18m):
  • 2.21 times the USD volume of "axl" bridges with $3.24m
  • 4.8 times the USD volume of "axlusdc" bridges with $1.499m
  • 15.31 times the USD volume of "axlweth" bridges with $0.469m
  • 58.85 times the USD volume of "axlwbtc" bridges with $0.122m

• Among the 53 currencies bridged by Axelar, 22 currencies were present in the price table. The top 5 currencies in terms of USD volume of bridges are:
  • axlusdc
  • luna
  • axlweth
  • axlwbtc
  • atom

• USD volume of "axlusdc" bridges from Axelar ($164.77m):
  • 1.49 times the USD volume of "luna" bridges with $110.03m
  • 9.31 times the USD volume of "axlweth" bridges with $17.7m
  • 17.51 ​​times the USD volume of "axlwbtc" bridges with $9.41m
  • 24.7 times the USD volume of "atom" bridges with $6.67m

• About 57.3% of all USD volume of bridges from Axelar to other interchains belonged to "inj". While more than 51.1% of all USD volume of bridges to Axelar from other interchains belonged to "axlusdc".

From Osmosis

• The top 5 currencies in terms of the number of bridges:

  • axlusdc

  • axl

  • axlweth

  • axlwbtc

  • xcdot

• "axlusdc" in terms of number of bridges, compared to other top 4 currencies:
  • 3.71 X the number of "axl" bridges
  • 10.45 X the number of "axlweth" bridges
  • 43.06 X number of "axlwbtc" bridges
  • 61.79 X number of "xcdot" bridges

• The top 5 currencies in terms of the number of bridgers:
  • axlusdc
  • axl
  • axlweth
  • xcdot
  • axldai

• "axlusdc" in terms of number of bridges, compared to other top 4 currencies:
  • 3.96 X the number of "axl" bridgers
  • 12.28 X number of "axlweth" bridgers
  • 57.37 X number of "xcdot" bridgers
  • 62.13 X number of "axldai" bridgers

• Top 5 currencies in terms of USD volume:
  • axlusdc
  • axlweth
  • axlwbtc
  • axldai
  • axl

• "axlusdc" in terms of USD volume of bridges, compared to other top 4 currencies:
  • 8.34 X USD volume of "axlweth" bridges
  • 15.11 X USD volume of "axlwbtc" bridges
  • 30.72 X USD volume of "axldai" bridges
  • 33.71 X USD volume of "axl" bridges

• In all three parameters, "axlusdc" has a clear advantage over other currencies. In the number of bridges, the difference between the first and second ranks is small, but the difference between the first and fifth ranks is high. While in the USD volume of bridges, the difference between the first and second rank is more, but instead the distribution of the difference between the first rank and other ranks is less than other parameters.

• 26 currencies have been bridged by osmosis. Out of these, only 8 currencies have been present in the price table and it is possible to calculate the $ value of their bridges.

Part III: Into Osmosis

Part IV: After Bridge

Note: In this part, I used Ali3N query in this dashboard to extract data related to Actions and Occurrences.

Into Osmosis

• The top 5 currencies in terms of the number of bridges:

  • axl

  • axlesdc

  • axlweth

  • axlwbtc

  • osmo

• "axl" in terms of number of bridges, compared to other top 4 currencies:

  • 6.13 X the number of "axlusdc" bridges

  • 11.5 X the number of "axlweth" bridges

  • 25.8 X number of "axlwbtc" bridges

  • 730.77 X number of "osmo" bridges

• The top 5 currencies in terms of the number of bridgers:

  • axl

  • axlesdc

  • axlweth

  • axlwbtc

  • osmo

• "axl" in terms of number of bridges, compared to other top 4 currencies:

  • 8.16 X the number of bridgers "axlusdc"

  • 31.81 X number of "axlweth" bridgers

  • 118.48 X number of "axlwbtc" bridgers

  • 381.77 X number of "osmo" bridgers

• Top 5 currencies in terms of USD volume:

  • axl

  • axlesdc

  • axlweth

  • axlwbtc

  • atom

• "axl" in terms of USD volume of bridges, compared to the other top 4 currencies:

  • 3.9 X USD volume of "axlusdc" bridges

  • 13.61 X USD volume of "axlweth" bridges

  • 53.54 X USD volume of "axlwbtc" bridges

  • 3825.18 X USD volume of "atom" bridges

• In all three parameters, "axl" has a clear advantage over other currencies. In USD Volume of Bridges, the difference between the first and second ranks is small, but between the first and fifth ranks is high. While in the number of bridges, the difference between the first and second rank is more, but instead the distribution of the difference between the first rank and other ranks is less than other parameters.

• 15 currencies have been bridged by osmosis. Out of these, only 8 currencies have been present in the price table and it is possible to calculate the $ value of their bridges.

• The main activity of this bridge actually started on September 27. This date coincides with the launch of "AXL" currency. A large part of bridges has been by osmosis with this currency. You can easily see the launch day of this currency in the number of its bridges. But as we move from the launch date of this currency to the current date, the share of "axl" in all three parameters has become less and less. This decrease in the share in the number of bridgers is less than the other two parameters.

After Bridge | Actions

The share of swapping among the number of transactions of the investigated actions is 50%. That is, among all these actions that happened after bridging, the share of swapping is equal to the share of 6 other actions.

The share of swapping is at least 2.1 times greater than any other action examined.

The special type of Liquidity Providing (Locked) and Staking (SuperFluid) along with Governance Vote has been the least popular among bridgers, which of course cannot be an unexpected result.

It seems that as we go from the first rank to the next ranks, the share of actions is almost halved. (This is how it is from the first to the fourth place)

In the number of users, swapping has lost 17.4% of its share (compared to the number of transactions). While the share of transfers has increased by 7.6%. This means that swappers have been more active than transferers.

In general, it can be said that the trends of the number of transactions and the number of users were similar and increasing.

In all 7 investigated actions, we can see an increasing trend, and the intensity of this increase is greater in the main actions.

After Bridge | Occurrings

Among the "Occurrings", the first four in terms of the number of transactions (i.e. message, tx, coin_received and coin_spent) seem to be cases where in most transactions one can find a line that is one of them in these lines. Especially the first three have such conditions. It seems that all transactions include the first two cases, and in the case of transactions for which any kind of money is paid, there is also the third case.

But among the next ranks of Occurrences that seem to be related to an activity and have higher ranks:

• transfer
• token_swapped
• burn
• ibc_transfer
• pool_joined

These show that although the results obtained from the actions are not accurate enough, their teaching is confirmed to a large extent.

Among "Occurrings", the first four in terms of the number of users (in order: coin_received, message, coin_spent_transfer) are different from the top 4 in terms of the number of transactions. (in order: message, tx, coin_received and coin_spent).

The first 5 ranks have the same number of users in terms of the number of users, this means that in the transactions performed by all users, there is at least one row in the table that their Occurrences