Question:

Calculate the distribution of $NEAR holdings by address.

In terms of charts, feel free to create a histogram or whichever visual you think works best!

Methodology:

• To get the holdings by address , the near.transfers table was used. The amount that has entered an address - the amount that left the address has been taken as balance
• The data received from the above calculation had a lot of addresses which were less than 1 NEAR. Upon some digging, it was found that most of these addresses had only received the amount from sweat_welcome and have made no transfers since. Hence, such addresses was removed to get a better and a more correct data
• The data still received from the above calculation was having a lot of addresses with less than 1 $NEAR. So, only addresses which have transacted more than thrice has been considered in the calculation to get a better data overall.

Summary:

In this dashboard we will look into the following:

• NEAR Distribution
• Net Wealth in each category
• NEAR Distribution excluding sweat welcome transfers
• NEAR Distribution excluding addresses with less than 3 transfers and receivers from sweat welcome
• NEAR normalised distribution of holdings by number of transactions
• Distribution of addresses by distribution of transactions
• Conclusions

Explanation & Insights:

• Almost 99% of the addresses have a wealth of less than 1 $NEAR and of the remaining more than half of them have between 1-10 NEAR and 37% have 10-100 NEAR. Or about 0.5% of the total addresses have 1-10 NEAR and 0.37% have about 10-100 NEAR
• By wealth distribution in a category, just 4 addresses were sufficient for about 37% of the total wealth and 29 of them have about 25% of the total wealth which shows a high inequality of wealth among categories.
• The wealth inequality might also be because of the protocols which have a lot of wealth such as aurora which is a bridge on NEAR

Next, let’s view the Distribution excluding sweat welcome transfers and when the transfers are less than 3 :

Explanation & Insights:

• About 95% of the addresses still have less than 1 $NEAR when one excludes the addresses which have received only from sweat welcome
• More than half of the addresses still hold less than 1 NEAR when only addresses which have made 3 or more deposit or withdrawal transactions are considered
• Notably, one-fifth of all such addresses have somewhere in between 10-100 NEAR and 12% of them 100-1k NEAR and then comes about 10% of addresses which have less than 1 $NEAR

Next, let’s look at the distribution of addresses by number of transactions and the normalised version of the same:

Explanation & Insights:

• When one looks at the question- More wealth means more transactions and the above chart, we find that there’s no straight answer for the same. This is because those having zero NEAR and those with 10M+ NEAR both have a very high number of transactions.
• What’s essential is that this high number of transactions decrease from both ends until one has about 100-1k NEAR. This means that it is a bell shaped graph meaning that if a user transacts less the chances of the user falling in the 100-1k NEAR category is higher
• While if a user transacts a lot more, the chances of the user being wealthy is slightly higher than that of having no NEAR at all
• By distribution, one can say that users with 3-5 transactions are higher throughout except for the rich where the users transact 6-10 times across withdrawals and deposits

Conclusions:

• Almost 99% of the addresses have a wealth of less than 1 $NEAR and of the remaining more than half of them have between 1-10 NEAR and 37% have 10-100 NEAR. Or about 0.5% of the total addresses have 1-10 NEAR and 0.37% have about 10-100 NEAR
• By wealth distribution in a category, just 4 addresses were sufficient for about 37% of the total wealth and 29 of them have about 25% of the total wealth which shows a high inequality of wealth among categories.
• The wealth inequality might also be because of the protocols which have a lot of wealth such as aurora which is a bridge on NEAR
• About 95% of the addresses still have less than 1 $NEAR when one excludes the addresses which have received only from sweat welcome
• More than half of the addresses still hold less than 1 NEAR when only addresses which have made 3 or more deposit or withdrawal transactions are considered
• Notably, one-fifth of all such addresses have somewhere in between 10-100 NEAR and 12% of them 100-1k NEAR and then comes about 10% of addresses which have less than 1 $NEAR
• When one looks at the question- More wealth means more transactions and the above chart, we find that there’s no straight answer for the same. This is because those having zero NEAR and those with 10M+ NEAR both have a very high number of transactions.
• What’s essential is that this high number of transactions decrease from both ends until one has about 100-1k NEAR. This means that it is a bell shaped graph meaning that if a user transacts less the chances of the user falling in the 100-1k NEAR category is higher
• While if a user transacts a lot more, the chances of the user being wealthy is slightly higher than that of having no NEAR at all
• By distribution, one can say that users with 3-5 transactions are higher throughout except for the rich where the users transact 6-10 times across withdrawals and deposits