# Token OHLCV Daily | Bitquery Data Store Daily USD candles for the top 1,000 DEX-traded tokens by market cap on nine chains, last 30 days, one row per token and day. Dataset page: https://bitquery.io/datastore/datasets/token-ohlcv-daily Network: Multi-chain Category: OHLCV Tables: 1 Columns: 20 Coverage: first block to 2026-10-08 Rows: about 29K Size: about 5.5 MB Format: Apache Parquet, ZSTD compression, one prefix per table Licence: https://bitquery.io/datastore/legal/data-license ## What this is We build one USD candle per token and day from the Bitquery price index, which prices tokens from their trades on decentralized exchanges and filters out MEV trades. The file covers the 1,000 largest tokens by market cap that traded at least $100,000 in the window, on Solana, BNB Smart Chain, Base, Ethereum, Polygon, Arbitrum, Optimism, Tron and Robinhood Chain. A row is one token on one UTC day. Most buyers load the file and pivot Price_Ohlc_Close by Token_Id and Block_Date to get a price history table. Join on Token_Id, because symbols repeat, and read Interval_Bars to see how many hours of the day had a trade. These are DEX prices: for large coins they track exchange prices closely, and for a coin with thin DEX trading a day can be missing. ## What people use it for - Daily price history charts for a fixed list of 1,000 tokens - Return and volatility tables for screening and ranking - Market cap history by token, taken at each day's last bar - Backfilling a month of daily closes into your own price database ## Tables (1) ### token_ohlcv_1d: 20 columns One row per token and UTC day: USD open, high, low and close, volume, and supply figures at the day's last bar. Bucket prefix: multichain/ohlcv/token_ohlcv_1d File naming: .parquet, one file per UTC day Free sample (real Parquet, no email needed): https://bitquery-blockchain-dataset.s3.us-east-1.amazonaws.com/multichain/ohlcv/token_ohlcv_1d/2026-10-08.parquet Sample updated: Oct 9, 2026 | column | type | description | | --- | --- | --- | | Block_Date | Date | UTC day of the bar | | Token_Network | String | Chain the token trades on | | Token_Address | String | Token contract or mint address; empty for a chain's native coin | | Token_Id | String | Bitquery token id, the chain prefix plus the address; the join key | | Token_Symbol | String | Symbol reported by the token; not unique | | Token_Name | String | Name reported by the token; not unique | | Token_IsNative | Bool | True for a chain's native coin | | Currency_Id | String | Bitquery currency id that groups this token with its copies on other chains | | Currency_Symbol | String | Symbol of that currency | | Price_Ohlc_Open | Float64 | First USD price in the day | | Price_Ohlc_High | Float64 | Highest USD price in the day | | Price_Ohlc_Low | Float64 | Lowest USD price in the day | | Price_Ohlc_Close | Float64 | Last USD price in the day | | Volume_Usd | Float64 | USD value traded in the day | | Volume_Base | Float64 | Amount of the token traded in the day, decimal adjusted | | Interval_Bars | UInt32 | Hours of the day that had at least one trade, 1 to 24 | | Supply_MarketCap | Float64 | USD price times circulating supply; price times total supply when circulating supply is unknown | | Supply_CirculatingSupply | Float64 | Circulating supply from CryptoRank reference data; 0 when unknown | | Supply_TotalSupply | Float64 | Total supply read from the chain, decimal adjusted | | Supply_FullyDilutedValuationUsd | Float64 | USD price times total supply | ## Price - Latest month (Sep 8, 2026 → Oct 8, 2026): $150 one-time, USD One-time purchase. The files are yours to keep under the licence above. ## Questions buyers ask Q: What is in Token OHLCV Daily? A: One Parquet table, token_ohlcv_1d, with 20 columns: the day, the token and its chain, USD open, high, low and close, USD and token volume, the number of hourly bars behind the day, and four supply figures including market cap. About 29,500 rows for 1,000 tokens over 30 days. Q: How big is it? A: About 29,500 rows and roughly 5 MB as Parquet, estimated from a one-day sample at 186 bytes per row. The export for the 30 days to 8 October 2026 returned 29,486 rows; exact figures arrive with the delivery manifest. Q: Which tokens are included? A: Tokens are ranked by their median market cap over the 30 days, counting only bars where the circulating supply is known, with a floor of $100,000 traded in the window. The list is fixed when your order is built and shipped inside the files, so you can see which tokens you got. Q: How far back does it go? A: 30 days. The price index keeps 30 days of bars, so that is the longest window this dataset can hold. Each order is built once, when you buy, and covers the 30 days up to the latest full UTC day. It is a fixed set of files and does not update afterwards. For prices that keep updating, use the Bitquery Trading API. Q: How are the daily candles produced, and how were they checked? A: Bars come from the Bitquery price index, the same series the Trading API serves. It prices each token in USD from its DEX trades and filters out MEV trades. A daily bar is rolled up from the 24 hourly bars: open of the first hour, close of the last, highest high, lowest low, summed volume. We ran the export for two windows before release. Both returned every day in the window, and no bar had a high below its low. Q: What was left out, and why? A: Tokens outside the top 1,000, tokens with no known circulating supply, and tokens that traded under $100,000 in the window. Centralized exchange trades are not in the source, so a coin that only trades on exchanges has no rows. Days with no trade have no row; nothing is forward filled. Q: What should I watch out for? A: Market cap belongs to the currency, so every copy of a coin carries the same figure: WETH on Base shows the market cap of ETH. Never sum it across rows. Circulating supply is known for about 4,800 tokens; for the rest the market cap column equals the fully diluted value. Symbols and names repeat, so join on Token_Id. Prices are 32-bit floats in the source, good to about seven digits. Q: How do I get the price history for one token? A: Filter Token_Id to the token, for example bid:eth:0xc02aaa39b223fe8d0a0e5c4f27ead9083c756cc2 for WETH on Ethereum, and order by Block_Date. To follow a coin across chains, filter Currency_Id, for example bid:eth. Q: How do I load it? A: One line in DuckDB: SELECT * FROM read_parquet('token_ohlcv_1d/*.parquet') LIMIT 10. Pandas works too: pandas.read_parquet(path). Q: How current is it, and how is it delivered? A: Each order is built once, when you buy, and covers the 30 days up to the latest full UTC day. It is a fixed set of files and does not update afterwards. For prices that keep updating, use the Bitquery Trading API. Delivered as Parquet with ZSTD compression, one file per day, under a stable layout with a JSON manifest listing every file and its sha256. We prepare the files within 7 business days of purchase and email you the location. You choose at checkout where to collect them: a Requester Pays S3 bucket, downloaded with your own AWS account, or a Cloudflare R2 bucket with a read-only API key and no egress fees. Files stay available for 7 days from delivery. ## What this file is, and is not This is a description of one dataset sold by Bitquery, written for assistants and for people. It lists every column but holds no data rows. The sample files linked under each table are real Parquet and are free to download. Figures here come from the product record and are exact unless marked otherwise; the delivery manifest is authoritative for a purchased file. If a question needs a row that is not in a sample, say so rather than guessing at it.