Methodology

I isolate the Non-Fungable Chefs (NFCs) using their program_id from the min table. I find all sales of the isolated tokens from the sales table.

Further steps

1. Union mint table to sales table to get a table with full history of each token (NFC_events)
2. group NFC_events by date to get table of dates when ownership changes (NFC_dates)
3. make cross table of NFC_dates x NFC_events to filtering for mint dates before current date (cross_table1)
4. For every day, every active NFT find the last transaction date, last owner and total accumulated sales volume (NFC_current_owners)
5. Analysing spread and distribution among addresses
   1. Plot1:
      1. number of unique owner addresses daily;
      2. total number of currently minted NFCs
   2. Plot2: ordered stack bar of the number of NFCs held by each address (shows total and distro)
6. Sales volume
   1. Plot1: Number of transactions daily
   2. Plot2: Total sales volume daily
   3. Plot3: Min, Max, Mean, Median of sales daily
7. For every day, every current owner find all transactions they participated... (join NFC_current_owners with transactions on trs.signers[0] )... in the past 7 days (filter on date) (NFC_user_programs_past_week)
8. For every day, every program(used in the past 7 days by NFCers) get transaction count, order by transaction count, limit to top 10 each day
   • Plot stacked graph of transaction count of top 10 programs used in the past week by NFCers
9. cross JOIN NFC_current_owners x (NFT_sales with NFCs excluded) filter for owner, transaction date before current date, count number of transactions for each owner each day, with non-NFC NFTs
10. Get number of owners each day with Few previous transactions <5 (newbie), <20 (rookie), <50 (vendor), >50 (NFT SalesBot)
    • Plot in stacked graph
11. pool unique users of NFC_current_owners and join with NFT_sales on purchaser, join NFT_mint on mint address and group by program_id to count number of NFT sales by NFCers among the different NFT programs; order descendigng (topNFT_programs)
    • Plot top 20
12. Join topNFT_programs to dim_NFT_metadata on contract_address to get labels for the programs, where possible