Available datasets
Name | Tag | Entry count (k) | Size (MBytes) | Format | Last updated | Links |
---|---|---|---|---|---|---|
Decentralised exchanges | exchange_universe | 4 | 2 | JSON | Documentation Download | |
Trading pairs | pair_universe | 156 | 20 | Parquet | Documentation Download | |
OHLCV candles, 1 minute | candles_1m | 453,735 | 23,750 | Parquet | Documentation Download | |
OHLCV candles, 5 minutes | candles_5m | 268,963 | 14,161 | Parquet | Documentation Download | |
OHLCV candles, 15 minutes | candles_15m | 170,038 | 9,050 | Parquet | Documentation Download | |
OHLCV candles, 1 hour | candles_1h | 84,785 | 4,567 | Parquet | Documentation Download | |
OHLCV candles, 4 hours | candles_4h | 37,403 | 2,043 | Parquet | Documentation Download | |
OHLCV candles, daily | candles_1d | 11,095 | 627 | Parquet | Documentation Download | |
OHLCV candles, weekly | candles_7d | 2,588 | 153 | Parquet | Documentation Download | |
OHLCV candles, montly | candles_30d | 882 | 54 | Parquet | Documentation Download | |
XY Liquidity, 1 minute | liquidity_1m | 486,225 | 19,146 | Parquet | Documentation Download | |
XY Liquidity, 5 minutes | liquidity_5m | 283,949 | 11,150 | Parquet | Documentation Download | |
XY Liquidity, 15 minutes | liquidity_15m | 178,575 | 7,061 | Parquet | Documentation Download | |
XY Liquidity, 1 hour | liquidity_1h | 89,005 | 3,550 | Parquet | Documentation Download | |
XY Liquidity, 4 hours | liquidity_4h | 39,555 | 1,596 | Parquet | Documentation Download | |
XY Liquidity, daily | liquidity_1d | 11,964 | 507 | Parquet | Documentation Download | |
XY Liquidity, weekly | liquidity_7d | 2,846 | 132 | Parquet | Documentation Download | |
XY Liquidity, monthly | liquidity_30d | 973 | 49 | Parquet | Documentation Download | |
Top momentum, daily | top_movers_24h | 0.500 | 0.594 | JSON | Documentation Download | |
AAVE v3 supply and borrow rates | aave_v3 | 2,138 | 185 | Parquet | Documentation Download |
Data logistics
Datasets are distributed in Parquet file format designed for data research. Parquet is a columnar data format for high performance in-memory datasets from Apache Arrow project.
Datasets are large. Datasets are compressed using Parquet built-in Snappy compression and may be considerably larger when expanded to RAM. We expect you to download the dataset, cache the resulting file on a local disk and perform your own strategy specific trading pair filtering before using the data. Uncompressed one minute candle data takes several gigabyte of memory.