Buckets:
| dataset_info: | |
| features: | |
| - name: timestamp | |
| dtype: timestamp[ns, tz=UTC] | |
| - name: open | |
| dtype: float64 | |
| - name: high | |
| dtype: float64 | |
| - name: low | |
| dtype: float64 | |
| - name: close | |
| dtype: float64 | |
| - name: volume | |
| dtype: float64 | |
| - name: ticker | |
| dtype: string | |
| splits: | |
| - name: train | |
| num_bytes: 195863846 | |
| num_examples: 3538138 | |
| download_size: 52097595 | |
| dataset_size: 195863846 | |
| configs: | |
| - config_name: default | |
| data_files: | |
| - split: train | |
| path: data/ohlcv_*.parquet | |
| # 📈 OHLCV-1m: US Stock Market Minute-Level Candlestick Data (1992–2025) | |
| This dataset provides minute-level OHLCV (Open, High, Low, Close, Volume) candlestick data for thousands of U.S. stocks across multiple decades (1992 to 2025). The data was originally sourced from [Finnhub.io](https://finnhub.io), a real-time market data provider. | |
| It has been aggregated and reformatted from monthly `.tar` archives into clean and unified Parquet files — one per month — and uploaded to the Hugging Face Hub for easy access. | |
| ## 🧾 Dataset Structure | |
| Each row in the dataset represents **one minute** of trading for a given stock ticker, and includes the following columns: | |
| | Column | Type | Description | | |
| |------------|------------------------------|-------------------------------------| | |
| | `timestamp`| `datetime64[ns, UTC]` | Start time of the minute | | |
| | `open` | `float64` | Opening price | | |
| | `high` | `float64` | Highest price within the minute | | |
| | `low` | `float64` | Lowest price within the minute | | |
| | `close` | `float64` | Closing price | | |
| | `volume` | `float64` | Volume traded within the minute | | |
| | `ticker` | `string` | Stock ticker symbol | | |
| The data is split by month into files like: | |
| data/ohlcv_1992-01.parquet | |
| data/ohlcv_1992-02.parquet | |
| ... | |
| data/ohlcv_2025-05.parquet | |
| ## 📚 Usage | |
| ```python | |
| from datasets import load_dataset | |
| # Load the dataset (will stream across all months) | |
| ds = load_dataset("mito0o852/OHLCV-1m", split="train") | |
| # View one row | |
| print(ds[0]) | |
| # To convert it into a pandas DataFrame: | |
| import pandas as pd | |
| df = ds.to_pandas() | |
| print(df.head()) | |
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- Size:
- 2.38 kB
- Xet hash:
- 54b4f9843f4f36a6853170feece374098f581d5426464dd30c5f7e52294a0182
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