Torch-Trade/trxusdt_spot_1m_05_2021_to_03_2026

---
license: mit
task_categories:
- time-series-forecasting
tags:
- finance
- trading
- cryptocurrency
- trx
- ohlcv
- binance
size_categories:
- 1M<n<10M
---

# TRXUSDT Spot 1-Minute OHLCV Dataset

1-minute OHLCV candlestick data for the **TRX/USDT** spot pair on Binance,
covering **May 1, 2021** to **February 28, 2026**.

- **Rows:** 2,541,210
- **Completeness:** 99.98%
- **Time Range:** May 1, 2021 — February 28, 2026


## Columns

| Column | Type | Description |
|--------|------|-------------|
| `timestamp` | `datetime64[ns]` | Candle open time (UTC) |
| `open` | `float64` | Opening price (USDT) |
| `high` | `float64` | Highest price in the candle |
| `low` | `float64` | Lowest price in the candle |
| `close` | `float64` | Closing price (USDT) |
| `volume` | `float64` | Trading volume (TRX) |

## Statistics

| Metric | Value |
|--------|-------|
| Start price | $0.1323 |
| End price | $0.2819 |
| Min price | $0.0453 |
| Max price | $0.4474 |
| Return | +113.1% |

## Data Quality

### Remaining gaps

390 bars across 2 gap(s) could not be backfilled.

| From | To | Missing bars |
|------|----|-------------|
| 2021-08-13 01:59:00 | 2021-08-13 06:30:00 | 270 |
| 2021-09-29 06:59:00 | 2021-09-29 09:00:00 | 120 |

These are from Binance maintenance windows where Bybit data was also unavailable.

## Usage

```python
from datasets import load_dataset
import pandas as pd

ds = load_dataset("Torch-Trade/trxusdt_spot_1m_05_2021_to_03_2026")
df = ds["train"].to_pandas()
df["timestamp"] = pd.to_datetime(df["timestamp"])

print(df.shape) # (2541210, 6)
print(df.head())
```

## License

**MIT** — price data sourced from Binance and Bybit public data repositories.