Dataset Preview
The full dataset viewer is not available (click to read why). Only showing a preview of the rows.
Could not read the parquet files: Parquet magic bytes not found in footer. Either the file is corrupted or this is not a parquet file.
Error code: FileSystemError
Need help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.
candle_time timestamp[us, tz=UTC] | open float64 | high float64 | low float64 | close float64 | volume float64 | trades unknown |
|---|---|---|---|---|---|---|
2020-01-01T00:00:00 | 0.03285 | 0.03285 | 0.0327 | 0.03278 | 944,734.3 | "206" |
2020-01-01T00:15:00 | 0.03279 | 0.03279 | 0.03274 | 0.03274 | 68,379.7 | "16" |
2020-01-01T00:30:00 | 0.03277 | 0.0328 | 0.03271 | 0.03275 | 84,245.6 | "43" |
2020-01-01T00:45:00 | 0.03276 | 0.03279 | 0.03273 | 0.03278 | 68,641.3 | "36" |
2020-01-01T01:00:00 | 0.03277 | 0.03288 | 0.03276 | 0.03286 | 81,780.8 | "43" |
2020-01-01T01:15:00 | 0.03285 | 0.03298 | 0.03285 | 0.03298 | 1,066,989.4 | "96" |
2020-01-01T01:30:00 | 0.03298 | 0.03303 | 0.03294 | 0.03298 | 257,029.5 | "70" |
2020-01-01T01:45:00 | 0.03297 | 0.03299 | 0.03292 | 0.03299 | 154,952.1 | "56" |
2020-01-01T02:00:00 | 0.03299 | 0.03301 | 0.03298 | 0.033 | 205,851.5 | "42" |
2020-01-01T02:15:00 | 0.03301 | 0.03308 | 0.033 | 0.03305 | 149,717.9 | "77" |
2020-01-01T02:30:00 | 0.03308 | 0.03316 | 0.03308 | 0.03314 | 228,652.6 | "72" |
2020-01-01T02:45:00 | 0.03315 | 0.0332 | 0.03313 | 0.03317 | 507,753.1 | "77" |
2020-01-01T03:00:00 | 0.03319 | 0.03319 | 0.03297 | 0.033 | 472,067 | "70" |
2020-01-01T03:15:00 | 0.033 | 0.0331 | 0.033 | 0.0331 | 40,579.9 | "28" |
2020-01-01T03:30:00 | 0.03311 | 0.03311 | 0.03303 | 0.03303 | 70,968.8 | "16" |
2020-01-01T03:45:00 | 0.033 | 0.03305 | 0.03299 | 0.03303 | 155,749.2 | "36" |
2020-01-01T04:00:00 | 0.03301 | 0.03305 | 0.03299 | 0.033 | 169,550.7 | "32" |
2020-01-01T04:15:00 | 0.03299 | 0.03299 | 0.0329 | 0.03293 | 1,002,649.8 | "261" |
2020-01-01T04:30:00 | 0.03294 | 0.03302 | 0.03292 | 0.03298 | 137,634.2 | "33" |
2020-01-01T04:45:00 | 0.03303 | 0.03305 | 0.03299 | 0.03299 | 40,645.3 | "28" |
2020-01-01T05:00:00 | 0.033 | 0.03307 | 0.033 | 0.03304 | 88,314.5 | "40" |
2020-01-01T05:15:00 | 0.033 | 0.03306 | 0.033 | 0.03305 | 69,288.9 | "15" |
2020-01-01T05:30:00 | 0.03306 | 0.03307 | 0.03303 | 0.03303 | 25,232.5 | "21" |
2020-01-01T05:45:00 | 0.03306 | 0.03311 | 0.03306 | 0.03309 | 221,441.8 | "83" |
2020-01-01T06:00:00 | 0.03309 | 0.03325 | 0.03309 | 0.03322 | 607,597.6 | "108" |
2020-01-01T06:15:00 | 0.03324 | 0.03327 | 0.03318 | 0.03318 | 407,019.7 | "66" |
2020-01-01T06:30:00 | 0.03318 | 0.03322 | 0.03318 | 0.03322 | 73,773.3 | "37" |
2020-01-01T06:45:00 | 0.03321 | 0.03321 | 0.03316 | 0.03318 | 43,429.8 | "32" |
2020-01-01T07:00:00 | 0.03319 | 0.03321 | 0.03318 | 0.03318 | 30,258.6 | "9" |
2020-01-01T07:15:00 | 0.03317 | 0.03323 | 0.03317 | 0.03321 | 112,869.9 | "26" |
2020-01-01T07:30:00 | 0.03321 | 0.03321 | 0.03309 | 0.03313 | 264,756.5 | "67" |
2020-01-01T07:45:00 | 0.0331 | 0.03315 | 0.0331 | 0.03315 | 30,613.7 | "29" |
2020-01-01T08:00:00 | 0.03312 | 0.03315 | 0.03308 | 0.03308 | 21,820 | "9" |
2020-01-01T08:15:00 | 0.03307 | 0.03314 | 0.03306 | 0.03312 | 304,097.9 | "51" |
2020-01-01T08:30:00 | 0.0331 | 0.03311 | 0.03306 | 0.03306 | 93,880.8 | "49" |
2020-01-01T08:45:00 | 0.03304 | 0.03313 | 0.03304 | 0.03313 | 82,084 | "21" |
2020-01-01T09:00:00 | 0.03318 | 0.03318 | 0.03314 | 0.03314 | 140,444.3 | "34" |
2020-01-01T09:15:00 | 0.03314 | 0.03318 | 0.03314 | 0.03314 | 9,154.2 | "7" |
2020-01-01T09:30:00 | 0.03316 | 0.03319 | 0.03314 | 0.03314 | 36,653.5 | "24" |
2020-01-01T09:45:00 | 0.03314 | 0.03316 | 0.03312 | 0.03314 | 280,886.5 | "30" |
2020-01-01T10:00:00 | 0.03313 | 0.03318 | 0.03311 | 0.03318 | 37,845.9 | "24" |
2020-01-01T10:15:00 | 0.03318 | 0.03322 | 0.03316 | 0.0332 | 207,913.9 | "39" |
2020-01-01T10:30:00 | 0.03319 | 0.03322 | 0.03318 | 0.03321 | 199,576.6 | "23" |
2020-01-01T10:45:00 | 0.03321 | 0.03321 | 0.03315 | 0.03319 | 49,291.8 | "30" |
2020-01-01T11:00:00 | 0.03317 | 0.03318 | 0.03313 | 0.03313 | 57,032 | "20" |
2020-01-01T11:15:00 | 0.03315 | 0.03333 | 0.03311 | 0.0333 | 535,925 | "143" |
2020-01-01T11:30:00 | 0.0333 | 0.03335 | 0.03326 | 0.03329 | 310,401.4 | "36" |
2020-01-01T11:45:00 | 0.03328 | 0.03328 | 0.03308 | 0.03312 | 374,009.7 | "65" |
2020-01-01T12:00:00 | 0.03312 | 0.03321 | 0.0331 | 0.03318 | 109,680.7 | "26" |
2020-01-01T12:15:00 | 0.03316 | 0.03325 | 0.03315 | 0.03323 | 61,169.1 | "22" |
2020-01-01T12:30:00 | 0.03322 | 0.03333 | 0.0332 | 0.03333 | 354,548.3 | "78" |
2020-01-01T12:45:00 | 0.03332 | 0.03349 | 0.03331 | 0.03344 | 1,189,647.6 | "125" |
2020-01-01T13:00:00 | 0.03345 | 0.03349 | 0.0334 | 0.03347 | 799,301 | "127" |
2020-01-01T13:15:00 | 0.03347 | 0.03347 | 0.03343 | 0.03345 | 69,488.1 | "19" |
2020-01-01T13:30:00 | 0.03345 | 0.03347 | 0.03341 | 0.03344 | 244,468.5 | "41" |
2020-01-01T13:45:00 | 0.03343 | 0.03345 | 0.03338 | 0.03338 | 279,924.3 | "64" |
2020-01-01T14:00:00 | 0.03338 | 0.03342 | 0.03334 | 0.03341 | 153,079.8 | "33" |
2020-01-01T14:15:00 | 0.03341 | 0.03348 | 0.03338 | 0.03347 | 212,491.4 | "71" |
2020-01-01T14:30:00 | 0.03347 | 0.03348 | 0.0334 | 0.03347 | 441,344.7 | "69" |
2020-01-01T14:45:00 | 0.03349 | 0.03371 | 0.03347 | 0.03369 | 1,035,433.9 | "167" |
2020-01-01T15:00:00 | 0.0337 | 0.0338 | 0.03351 | 0.03355 | 2,481,014.4 | "310" |
2020-01-01T15:15:00 | 0.03353 | 0.03355 | 0.03348 | 0.03355 | 426,304.8 | "75" |
2020-01-01T15:30:00 | 0.03353 | 0.03371 | 0.03352 | 0.0336 | 720,356.5 | "95" |
2020-01-01T15:45:00 | 0.03361 | 0.03362 | 0.03352 | 0.03358 | 462,921.7 | "82" |
2020-01-01T16:00:00 | 0.0336 | 0.03374 | 0.03359 | 0.03371 | 679,313.6 | "185" |
2020-01-01T16:15:00 | 0.03371 | 0.03371 | 0.03357 | 0.03365 | 434,505.3 | "84" |
2020-01-01T16:30:00 | 0.03363 | 0.03369 | 0.0336 | 0.03367 | 170,670.8 | "54" |
2020-01-01T16:45:00 | 0.03369 | 0.03374 | 0.03366 | 0.03374 | 110,382.2 | "31" |
2020-01-01T17:00:00 | 0.03375 | 0.03378 | 0.03366 | 0.03371 | 294,619.5 | "83" |
2020-01-01T17:15:00 | 0.0337 | 0.03374 | 0.03367 | 0.03372 | 126,724 | "62" |
2020-01-01T17:30:00 | 0.03371 | 0.03371 | 0.03364 | 0.03367 | 248,330.3 | "42" |
2020-01-01T17:45:00 | 0.03365 | 0.03371 | 0.03365 | 0.03366 | 131,206.6 | "21" |
2020-01-01T18:00:00 | 0.03368 | 0.03373 | 0.03366 | 0.03371 | 188,569.6 | "68" |
2020-01-01T18:15:00 | 0.03372 | 0.03374 | 0.03363 | 0.03364 | 237,664.8 | "44" |
2020-01-01T18:30:00 | 0.03361 | 0.03366 | 0.0336 | 0.03366 | 337,553.4 | "54" |
2020-01-01T18:45:00 | 0.03368 | 0.03373 | 0.03362 | 0.03371 | 215,035.2 | "60" |
2020-01-01T19:00:00 | 0.0337 | 0.03371 | 0.03364 | 0.03368 | 160,650.9 | "49" |
2020-01-01T19:15:00 | 0.03368 | 0.03371 | 0.03362 | 0.03365 | 112,846.4 | "67" |
2020-01-01T19:30:00 | 0.03365 | 0.03366 | 0.03362 | 0.03362 | 11,914.7 | "12" |
2020-01-01T19:45:00 | 0.03362 | 0.03366 | 0.0336 | 0.03362 | 179,976.1 | "48" |
2020-01-01T20:00:00 | 0.03362 | 0.03367 | 0.03362 | 0.03363 | 135,951.3 | "38" |
2020-01-01T20:15:00 | 0.03364 | 0.03376 | 0.03363 | 0.03373 | 276,791.5 | "86" |
2020-01-01T20:30:00 | 0.03373 | 0.03373 | 0.03366 | 0.03368 | 93,806.4 | "41" |
2020-01-01T20:45:00 | 0.03366 | 0.03368 | 0.03354 | 0.03354 | 547,434.9 | "103" |
2020-01-01T21:00:00 | 0.03354 | 0.03359 | 0.0335 | 0.03353 | 476,429.8 | "86" |
2020-01-01T21:15:00 | 0.03353 | 0.03356 | 0.03353 | 0.03354 | 31,009 | "16" |
2020-01-01T21:30:00 | 0.03355 | 0.0336 | 0.03353 | 0.03356 | 355,099.6 | "66" |
2020-01-01T21:45:00 | 0.03359 | 0.03369 | 0.03357 | 0.03367 | 691,835.5 | "141" |
2020-01-01T22:00:00 | 0.03366 | 0.03366 | 0.03348 | 0.0335 | 1,553,357.5 | "148" |
2020-01-01T22:15:00 | 0.0335 | 0.03354 | 0.03349 | 0.0335 | 372,479.8 | "40" |
2020-01-01T22:30:00 | 0.0335 | 0.03351 | 0.03337 | 0.0334 | 749,221.3 | "119" |
2020-01-01T22:45:00 | 0.0334 | 0.0335 | 0.03338 | 0.0335 | 305,784.7 | "86" |
2020-01-01T23:00:00 | 0.03346 | 0.03349 | 0.03335 | 0.03338 | 402,067.3 | "100" |
2020-01-01T23:15:00 | 0.03337 | 0.03349 | 0.03336 | 0.03347 | 341,278.1 | "103" |
2020-01-01T23:30:00 | 0.03345 | 0.03348 | 0.03337 | 0.03347 | 127,171.3 | "54" |
2020-01-01T23:45:00 | 0.03347 | 0.03351 | 0.03345 | 0.03348 | 62,365.3 | "45" |
2020-01-02T00:00:00 | 0.03345 | 0.03347 | 0.03345 | 0.03346 | 261,535.1 | "29" |
2020-01-02T00:15:00 | 0.03344 | 0.03347 | 0.03343 | 0.03347 | 46,087 | "35" |
2020-01-02T00:30:00 | 0.03347 | 0.03347 | 0.0334 | 0.03345 | 435,445.1 | "47" |
2020-01-02T00:45:00 | 0.03346 | 0.03348 | 0.03341 | 0.03345 | 277,242 | "84" |
End of preview.
Cardano OHLCV Pack — Full 6.5-Year Dataset (Free)
6 timeframes · 3.4M candles (1m) · 2020–2026 · Free, no email required
Complete Cardano OHLCV dataset built from audited tick-level trade data by The Glitch List.
What's Included
- 6 Parquet files: 1m, 5m, 15m, 1h, 4h, 1d
- Coverage: 2020-01-01 → 2026-07-04 (6.5 years)
- Zero look-ahead bias — verified
- Format: Apache Parquet (ZSTD compressed)
- Built from audited ADA/USDT tick-level trades
Quick Start
import polars as pl
df = pl.read_parquet("ADA_OHLCV_1m.parquet")
print(df.shape)
print(df.head())
Need Tick-Level Data?
The OHLCV pack is built from raw tick data. For HFT simulation, order flow imbalance, and market microstructure research, you need the tick-level dataset.
License
Personal research and trading bot development only. No commercial redistribution, resale, or public API deployment.
Citation
If you use this dataset, please credit The Glitch List and link to theglitchlist.com.
🎁 REGALO SORPRESA: Sovereign Setup — Hyperliquid Onboarding Kit
¡Sí, lo has leído bien! Con este dataset te regalamos además el Sovereign Setup — Hyperliquid Onboarding Kit completo, GRATIS: una guía interactiva paso a paso para salir de los exchanges centralizados y operar por fin en tu propia wallet, con control total de tus claves.
Lo encontrarás dentro del ZIP como BONUS_sovereign-setup-hyperliquid-kit.zip. Ábrelo, sigue los pasos, y bienvenido a la soberanía financiera. 🚀
Want the full audited dataset? The Glitch List publishes tick-level and OHLCV crypto data with a documented integrity declaration (gaps included). Full 12-month tick-level version: https://whop.com/ada-spot-tick-last-year/?utm_source=hf&utm_medium=sample&utm_campaign=ada
Also from The Glitch List
This dataset is published by The Glitch List. We also run TGL Macro Alerts: Gold and S&P 500 breakout alerts in Discord, scored 0-6, with public rules and a public log of every alert.
Alerts, not financial advice. Past alerts don't predict future results.
Free breakout log (open data, no email): https://theglitchlist.com/breakout-log/?utm_source=hf&utm_medium=sample&utm_campaign=breakout-log
- Downloads last month
- 146