Torch-Trade/solusdt_spot_1m_05_2021_to_03_2026

--- license: mit task_categories: - time-series-forecasting tags: - finance - trading - cryptocurrency - sol - ohlcv - binance size_categories: - 1M<n<10M --- # SOLUSDT Spot 1-Minute OHLCV Dataset 1-minute OHLCV candlestick data for the **SOL/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 (SOL) | ## Statistics | Metric | Value | |--------|-------| | Start price | $42.6920 | | End price | $84.3500 | | Min price | $8.0000 | | Max price | $295.6200 | | Return | +97.6% | ## 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/solusdt_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.