metadata
license: mit
task_categories:
- time-series-forecasting
language:
- en
tags:
- crypto
- cryptocurrency
- finance
- ohlcv
- klines
- gateio
- trading
pretty_name: Gate.io USDT OHLCV Klines
size_categories:
- 1B<n<10B
Gate.io USDT OHLCV Klines
Historical OHLCV candlestick (kline) data for Gate.io USDT-quoted markets, stored as zstd-compressed Parquet.
Coverage
| Exchange | Gate.io |
| Markets | spot (primary) · futures (USDT perpetuals — limited history, see Notes) |
| Timeframes | 5m · 15m · 1h · 4h · 1d (all pairs) — plus 1m for a ~1.3k-pair subset |
| Pairs | ~3,300 spot USDT pairs |
| History | spot back to 2013 for the oldest listings |
| As of | static snapshot (~2025-05); periodic refresh planned |
| Source | seeded from the DigiTuccar HistoricalDataForTradeBacktest snapshot |
File layout
{market}/{timeframe}/{PAIR}.parquet
Examples: spot/1d/BTC_USDT.parquet, spot/5m/ETH_USDT.parquet
Each Parquet holds one pair × one timeframe. Columns:
| column | type | description |
|---|---|---|
date |
datetime (UTC) | candle open time |
open |
float | open price |
high |
float | high price |
low |
float | low price |
close |
float | close price |
volume |
float | base-asset volume |
Usage
Single file:
from huggingface_hub import hf_hub_download
import pandas as pd
path = hf_hub_download("rogerdehe/klines-gateio",
"spot/1d/BTC_USDT.parquet", repo_type="dataset")
df = pd.read_parquet(path)
A subset (or all) of the dataset:
from huggingface_hub import snapshot_download
snapshot_download("rogerdehe/klines-gateio", repo_type="dataset",
allow_patterns=["spot/1d/*"]) # e.g. just daily spot
Notes
- Futures history is limited: Gate.io's API only served ~180 days back at
snapshot time, so
futures/is thin relative tospot/. Use spot for deep history. 1mis available only for a subset of pairs (~1.3k); other timeframes cover all pairs.- The HF dataset viewer is disabled (custom per-pair layout); load files directly as shown above.
- Timestamps are UTC. Data is provided as-is for research purposes, with no warranty of accuracy or completeness.