Datasets:
Tasks:
Time Series Forecasting
Modalities:
Tabular
Formats:
json
Languages:
English
Size:
10K - 100K
License:
File size: 2,286 Bytes
9f491eb | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 | ---
license: cc-by-4.0
language:
- en
tags:
- finance
- cryptocurrency
- ohlcv
- candles
- trading
- time-series
- bitcoin
- btc
pretty_name: BTC-USDT 4-Hour Candles (2017-08-17 to 2026-08-13)
size_categories:
- 10K<n<100K
task_categories:
- time-series-forecasting
dataset_info:
features:
- name: timestamp
dtype: int64
- name: open
dtype: float64
- name: high
dtype: float64
- name: low
dtype: float64
- name: close
dtype: float64
- name: volume
dtype: float64
splits:
- name: train
num_examples: 19686
download_size: 2176974
configs:
- config_name: default
data_files:
- split: train
path: data/*.jsonl
---
# BTC-USDT 4-Hour Candles
Full-history 4-Hour-resolution OHLCV candlestick data for the **BTC-USDT**
trading pair (Bitcoin), from **2017-08-17T04:00:00Z** to **2026-08-13T20:00:00Z** (19,686 candles, UTC).
Covers the pair's entire listed history from first traded candle to the most
recent completed daily session.
## Columns
| Column | Type | Description |
|---|---|---|
| `timestamp` | int64 | Candle open time, Unix epoch **milliseconds** (UTC) |
| `open` | float | Open price |
| `high` | float | High price |
| `low` | float | Low price |
| `close` | float | Close price |
| `volume` | float | Base asset volume (BTC) |
Each row is one 4h candle. Prices are quoted in USDT.
## Data Quality
- Timestamps normalized to millisecond precision (UTC), strictly increasing, deduplicated.
- OHLC sanity-checked: `high >= max(open, close, low)` and `low <= min(open, close, high)`.
- Missing candles correspond to periods with no traded activity (no candle was
produced for those intervals).
## Load
```python
from datasets import load_dataset
ds = load_dataset("humblefool06/btc-usdt-4h-candles", split="train")
```
Or directly from the JSONL file:
```python
from datasets import load_dataset
ds = load_dataset("json", data_files="data/btc_usdt_4h.jsonl", split="train")
```
## License
Released under the Creative Commons Attribution 4.0 International license
(**CC-BY-4.0**). You are free to share and adapt this data for any purpose,
including commercially, provided you give appropriate credit. Provided as-is,
without warranty of any kind.
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