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vessel888/OHLCV-1m

๐Ÿ“ˆ OHLCV-1m: US Stock Market Minute-Level Candlestick Data (1992โ€“2026) This dataset provides minute-level OHLCV (Open, High, Low, Close, Volume) candlestick data for thousands of U.S. stocks across multiple decades (1992 to 2026). The data was originally sourced from Finnhub.io, a real-time market data provider. It has been aggregated and reformatted from monthly .tar archives into clean and unified Parquet files โ€” one per month โ€” and uploaded to the Hugging Face Hub for easyโ€ฆ See the full description on the dataset page: https://huggingface.co/datasets/vessel888/OHLCV-1m.

sourceHugging Faceupdated 28d agoView on Hugging Face
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๐Ÿ“ˆ OHLCV-1m: US Stock Market Minute-Level Candlestick Data (1992โ€“2026)

This dataset provides minute-level OHLCV (Open, High, Low, Close, Volume) candlestick data for thousands of U.S. stocks across multiple decades (1992 to 2026). The data was originally sourced from Finnhub.io, a real-time market data provider.

It has been aggregated and reformatted from monthly .tar archives into clean and unified Parquet files โ€” one per month โ€” and uploaded to the Hugging Face Hub for easy access.

๐Ÿงพ Dataset Structure

Each row in the dataset represents one minute of trading for a given stock ticker, and includes the following columns:

ColumnTypeDescription
timestampdatetime64[ns, UTC]Start time of the minute
openfloat64Opening price
highfloat64Highest price within the minute
lowfloat64Lowest price within the minute
closefloat64Closing price
volumefloat64Volume traded within the minute
tickerstringStock ticker symbol

The data is split by month into files like:

data/ohlcv1992-01.parquet data/ohlcv1992-02.parquet ... data/ohlcv_2026-03.parquet

๐Ÿ“š 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())