13:22:32 For these three chains, prev_date is the same string, 2026-11-13, with not a single character different. But the three prev_tvl_usd values that follow are all different: BSC 4887558428, Ethereum 40328979620, Solana 4988717181. Their corresponding tvl_usd values are 4746429492.978147, 38961614139.21211, and 4863549673.352701, with daily changes of -2.89, -3.62, and -3.05.
At first, I gave rows like these a date key, thinking that looking back by day would be enough. It wasn't until I got to these three rows that I realized all three date cells are identical. The date can't distinguish one row from another, let alone one data retrieval from another. These are just my personal records of the figures; they are not investment advice. I've now switched to keeping the chain name, the original baseline value, and the retrieval time together, with the date relegated to a note.
For these tuples of current value, previous value, and daily change, what do you use to identify each row? I tried relying on the date alone, but things get mixed up when I compare them later. I'm still undecided about whether to add another column.
At first, I gave rows like these a date key, thinking that looking back by day would be enough. It wasn't until I got to these three rows that I realized all three date cells are identical. The date can't distinguish one row from another, let alone one data retrieval from another. These are just my personal records of the figures; they are not investment advice. I've now switched to keeping the chain name, the original baseline value, and the retrieval time together, with the date relegated to a note.
For these tuples of current value, previous value, and daily change, what do you use to identify each row? I tried relying on the date alone, but things get mixed up when I compare them later. I'm still undecided about whether to add another column.