The Scenario
You're a crypto analyst at a small DeFi fund. It's Sunday evening and you're building Monday's weekly performance report. Your Excel workbook has 20 token contract addresses in column A — the fund's current watchlist. Columns B through D are supposed to show last week's total USD volume, average price, and trade count on Uniswap v3 for each token.
Every week, you do this by hand.
The bad version:
- Open the Bitquery IDE, paste the first contract address into your saved GraphQL query, run it, copy the aggregated result from the response panel
- Switch to the workbook, find the right row, paste three values into three separate cells, fix the formatting because Bitquery returns scientific notation that Excel misinterprets
- Repeat for the remaining 19 addresses, then spend 10 minutes reconciling two tokens that returned null instead of zero
The fund's Monday morning call starts at 9 AM. You've done this enough times to know it takes 45 minutes on a good week and 90 if one of the addresses changed format. There's no version of this that doesn't eat your Sunday night.
The Easy Way: One Prompt in SheetXAI
SheetXAI is an AI agent that lives inside your Excel workbook. It reads your token list, calls the Bitquery API for you, and writes the results directly into the workbook. No query construction, no JSON parsing, no copy-paste.
Open the SheetXAI sidebar and paste this prompt:
For each token contract address in column A, query Bitquery's combined database for the last 7 days of Ethereum DEX trades and write total volume (USD), average price, and trade count into columns B, C, and D
What You Get
- Column B: total USD volume for the 7-day window, numeric
- Column C: average price across all trades, numeric
- Column D: trade count, integer
- Addresses with no DEX activity in the window receive a zero in each column — not a blank that would break your downstream formulas
- Any address that failed to resolve logs a note in a status column so you know which ones to investigate
What If the Data Is Not Quite Ready
The contract addresses are mixed-case or have extra whitespace
For each token contract address in column A, trim whitespace and normalize to lowercase before querying Bitquery. Write volume, average price, and trade count into columns B, C, and D. Flag any addresses that failed to resolve in column E.
Some tokens trade on multiple DEXes and you only want Uniswap v3
For each token in column A, query Bitquery for the last 7 days of DEX trades on Uniswap v3 only on Ethereum mainnet. Write total USD volume into column B, average price into column C, and trade count into column D.
You want to join against a second worksheet that maps contract addresses to token names
Cross-reference each contract in column A with the token name in worksheet "Watchlist" column B. For each address, query Bitquery for last 7 days Uniswap v3 trade data and write token name, volume, average price, and trade count into columns A through D of worksheet "Weekly Report".
You want to clean outliers, flag low-liquidity tokens, and run the pull in one shot
For each token contract in column A, query Bitquery for last 7 days of Ethereum DEX trades. Exclude any trades below $500 USD. Write total volume, average price, and trade count into columns B–D. Flag tokens with fewer than 10 trades as "low liquidity" in column E. Then sort the results by column B descending.
The pattern: the data shaping and the pull happen in a single instruction — you don't clean first and query second.
Try It
Get the 7-day free trial of SheetXAI and open your token watchlist workbook, then ask SheetXAI to pull last week's Uniswap trade data for every address in column A. For a related task, see how to build a DEX buy vs. sell summary or explore the full Bitquery integration overview.