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timestamp
timestamp[ns, tz=UTC]
open
float64
high
float64
low
float64
close
float64
volume
float64
ticker
string
1992-01-02T14:32:00
8.875
8.875
8.875
8.875
1,700
FRF
1992-01-02T14:47:00
8.875
8.875
8.875
8.875
2,200
FRF
1992-01-02T14:50:00
8.875
8.875
8.875
8.875
1,200
FRF
1992-01-02T15:06:00
8.875
8.875
8.875
8.875
800
FRF
1992-01-02T15:35:00
8.75
8.75
8.75
8.75
400
FRF
1992-01-02T15:52:00
8.75
8.75
8.75
8.75
1,200
FRF
1992-01-02T15:57:00
8.75
8.75
8.75
8.75
100
FRF
1992-01-02T15:58:00
8.75
8.75
8.75
8.75
1,600
FRF
1992-01-02T16:04:00
8.75
8.75
8.75
8.75
1,200
FRF
1992-01-02T16:05:00
8.75
8.75
8.75
8.75
2,500
FRF
1992-01-02T16:06:00
8.75
8.75
8.75
8.75
200
FRF
1992-01-02T16:20:00
8.875
8.875
8.875
8.875
300
FRF
1992-01-02T16:33:00
8.75
8.75
8.75
8.75
600
FRF
1992-01-02T16:34:00
8.75
8.75
8.75
8.75
1,000
FRF
1992-01-02T16:46:00
8.75
8.75
8.75
8.75
500
FRF
1992-01-02T17:02:00
8.875
8.875
8.875
8.875
100
FRF
1992-01-02T17:03:00
8.75
8.75
8.75
8.75
300
FRF
1992-01-02T17:25:00
8.75
8.75
8.75
8.75
500
FRF
1992-01-02T17:50:00
8.875
8.875
8.875
8.875
500
FRF
1992-01-02T17:53:00
8.75
8.75
8.75
8.75
300
FRF
1992-01-02T18:14:00
8.75
8.75
8.75
8.75
1,000
FRF
1992-01-02T18:15:00
8.75
8.75
8.75
8.75
2,100
FRF
1992-01-02T18:17:00
8.75
8.75
8.75
8.75
500
FRF
1992-01-02T18:40:00
8.75
8.75
8.75
8.75
3,200
FRF
1992-01-02T18:41:00
8.75
8.75
8.75
8.75
500
FRF
1992-01-02T19:00:00
8.875
8.875
8.875
8.875
200
FRF
1992-01-02T19:19:00
8.875
8.875
8.875
8.875
500
FRF
1992-01-02T19:48:00
8.875
8.875
8.875
8.875
2,000
FRF
1992-01-02T19:56:00
8.75
8.75
8.75
8.75
900
FRF
1992-01-02T19:58:00
8.875
8.875
8.875
8.875
2,000
FRF
1992-01-02T20:02:00
8.875
8.875
8.875
8.875
1,000
FRF
1992-01-02T20:34:00
8.75
8.875
8.75
8.875
7,000
FRF
1992-01-02T20:44:00
8.875
8.875
8.875
8.875
3,000
FRF
1992-01-02T21:01:00
8.875
8.875
8.875
8.875
800
FRF
1992-01-02T21:11:00
8.875
8.875
8.875
8.875
800
FRF
1992-01-03T14:30:00
8.75
8.75
8.75
8.75
4,900
FRF
1992-01-03T14:32:00
8.75
8.75
8.75
8.75
4,000
FRF
1992-01-03T14:41:00
8.75
8.75
8.75
8.75
7,400
FRF
1992-01-03T14:43:00
8.75
8.75
8.75
8.75
5,000
FRF
1992-01-03T15:01:00
8.75
8.75
8.75
8.75
3,000
FRF
1992-01-03T15:10:00
8.75
8.75
8.75
8.75
5,500
FRF
1992-01-03T16:35:00
8.75
8.75
8.75
8.75
4,000
FRF
1992-01-03T17:06:00
8.75
8.75
8.75
8.75
200
FRF
1992-01-03T17:13:00
8.75
8.75
8.75
8.75
1,000
FRF
1992-01-03T17:54:00
8.625
8.625
8.625
8.625
200
FRF
1992-01-03T18:06:00
8.625
8.625
8.625
8.625
700
FRF
1992-01-03T18:27:00
8.625
8.625
8.625
8.625
500
FRF
1992-01-03T18:34:00
8.625
8.625
8.625
8.625
19,300
FRF
1992-01-03T18:43:00
8.75
8.75
8.75
8.75
43,500
FRF
1992-01-03T18:52:00
8.75
8.75
8.75
8.75
3,000
FRF
1992-01-03T20:23:00
8.875
8.875
8.875
8.875
300
FRF
1992-01-03T20:27:00
8.75
8.75
8.75
8.75
600
FRF
1992-01-06T14:32:00
8.75
8.75
8.75
8.75
3,300
FRF
1992-01-06T14:34:00
8.75
8.75
8.75
8.75
3,000
FRF
1992-01-06T14:45:00
8.75
8.75
8.75
8.75
5,100
FRF
1992-01-06T14:49:00
8.875
8.875
8.75
8.75
1,000
FRF
1992-01-06T14:54:00
8.75
8.75
8.75
8.75
1,500
FRF
1992-01-06T15:04:00
8.875
8.875
8.875
8.875
300
FRF
1992-01-06T15:08:00
8.875
8.875
8.875
8.875
1,100
FRF
1992-01-06T15:17:00
8.875
8.875
8.875
8.875
1,100
FRF
1992-01-06T15:21:00
8.875
8.875
8.875
8.875
3,000
FRF
1992-01-06T15:36:00
8.75
8.75
8.75
8.75
1,000
FRF
1992-01-06T15:55:00
8.875
8.875
8.875
8.875
25,000
FRF
1992-01-06T15:56:00
8.875
8.875
8.875
8.875
1,500
FRF
1992-01-06T16:00:00
9
9
8.875
8.875
45,300
FRF
1992-01-06T16:06:00
9
9
9
9
3,200
FRF
1992-01-06T16:07:00
9
9
9
9
1,500
FRF
1992-01-06T16:09:00
9
9
9
9
500
FRF
1992-01-06T16:10:00
9
9
9
9
7,700
FRF
1992-01-06T16:19:00
9
9
9
9
3,500
FRF
1992-01-06T16:50:00
9
9
9
9
1,000
FRF
1992-01-06T17:14:00
9
9
9
9
200
FRF
1992-01-06T17:41:00
9.125
9.125
9.125
9.125
1,000
FRF
1992-01-06T17:52:00
9
9
9
9
1,000
FRF
1992-01-06T17:58:00
9
9
9
9
25,000
FRF
1992-01-06T18:50:00
9
9
9
9
100
FRF
1992-01-06T18:56:00
9
9
9
9
100
FRF
1992-01-06T19:42:00
8.875
8.875
8.875
8.875
300
FRF
1992-01-06T19:49:00
8.875
8.875
8.875
8.875
100
FRF
1992-01-06T20:01:00
8.875
8.875
8.875
8.875
1,500
FRF
1992-01-06T20:02:00
8.875
8.875
8.875
8.875
2,000
FRF
1992-01-06T20:18:00
9
9
9
9
121,000
FRF
1992-01-06T20:19:00
9
9
9
9
500
FRF
1992-01-06T21:09:00
9
9
9
9
100
FRF
1992-01-07T14:32:00
8.75
8.75
8.75
8.75
3,400
FRF
1992-01-07T14:33:00
8.75
8.75
8.75
8.75
300
FRF
1992-01-07T14:36:00
8.75
8.75
8.75
8.75
300
FRF
1992-01-07T14:47:00
8.75
8.75
8.75
8.75
2,200
FRF
1992-01-07T14:48:00
8.75
8.75
8.75
8.75
2,000
FRF
1992-01-07T14:50:00
8.75
8.75
8.75
8.75
1,000
FRF
1992-01-07T15:03:00
8.75
8.75
8.75
8.75
10,800
FRF
1992-01-07T15:04:00
8.875
8.875
8.875
8.875
200
FRF
1992-01-07T16:07:00
8.875
8.875
8.875
8.875
200
FRF
1992-01-07T16:21:00
8.875
8.875
8.875
8.875
200
FRF
1992-01-07T16:26:00
8.875
8.875
8.875
8.875
1,200
FRF
1992-01-07T17:07:00
8.75
8.75
8.75
8.75
500
FRF
1992-01-07T18:28:00
8.75
8.875
8.75
8.875
2,000
FRF
1992-01-07T18:39:00
8.75
8.75
8.75
8.75
1,000
FRF
1992-01-07T18:43:00
8.75
8.75
8.75
8.75
200
FRF
1992-01-07T19:10:00
8.75
8.75
8.75
8.75
200
FRF
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πŸ“ˆ 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, a real-time market data provider.

It has been aggregated and reformatted from monthly .tar archives into clean and unified Parquet files β€” one per month β€” 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

πŸ“š Usage

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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