Method

I used the flow.core.fact_transactions table to visualize active users (proposers) in the past months. For the MOM factor, I used the technique of subtracting the number of users in each month from the previous month to see which factors led to an increase or decrease in network users. For the second part , my goal was to see which factors led to an increase or decrease in network users, and for this purpose, I looked at the correlation between price (flow.core.fact_hourly_prices) and the number of users daily. I also looked at the correlation between users and popular contracts in flow.core.fact_transactions and flow.core.fact_events tables. In addition, I analyzed the type of popular events and their role in the number of network users in flow.core.fact_events. Lastly, I investigated the types of transactions by users and which type of transaction led to an increase in network users in flow.core.ez_nft_sales, flow.core.ez_swaps, flow.core.ez_staking_actions, flow.core.ez_bridge_transactions, and flow.core.ez_token_transfers tables.

Metrics

1.Monthly stats of transactions and wallets 2.Monthly growth rate of active users 3.Daily stats of active users and Flow price 4.Monthly stats of contracts and users 5.Monthly stats of transactions by type 6.Daily top 10 event types by users

Flow - 3. Daily Active Users