financialCryptoSpartan/stocks_bars_1mstocksetfohlcvminute-barsalpacatime-seriesquantitative-financebacktestingparquet

US Stocks & ETFs 1-Minute Bars

Name: US Stocks & ETFs 1-Minute Bars
License: https://huggingface.co/datasets/CryptoSpartan/stocks_bars_1m

2016–present

Free

Open dataset

Sample structure: 100 / 100

238 download links issued

Seller: DataBazaar

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Source, license and coverage

Supplier documentation. These claims are separate from the automated sample score. A listing edit date is not a data freshness date.

License: mit
Source / creator: CryptoSpartan/stocks_bars_1m
Collection method: The publisher scraped 1-minute OHLCV bars for a basket of US stocks and ETFs from the Alpaca Markets Historical Bars API and stored them as Parquet for efficient analytical access. Bars include VWAP and trade counts as provided by Alpaca. Timestamps are normalized to UTC milliseconds. No additional cleaning or corporate-action adjustment is documented.
Coverage / snapshot: 2016–present
Data last updated: Not documented
Update schedule: Not documented

Source documentation ↗

License terms ↗

The ticker universe is not enumerated in the dataset card — buyers should inspect the `ticker` column to confirm coverage. Corporate actions (splits, dividends) may or may not be adjusted; the source does not document this and buyers should validate empirically. Coverage of delisted tickers, after-hours/pre-market sessions, and missing-minute handling are not specified. Data depends on Alpaca's own historical record, which has its own coverage limits prior to ~2016.

Sample structure score: 100 / 100

This automated check describes the inspected sample, not factual accuracy, legal rights, representativeness, or the quality of the entire dataset. It is not a customer rating.

Assessed 10 sample records (JSON) on 2026-10-09. All records in the provided sample were checked.

Check	Points	Evidence
Populated cells	50 / 50	100 of 100 top-level cells contain a value. Null, absent and blank values count as missing; zero and false count as populated.
Consistent value types	30 / 30	100 of 100 populated cells match their column's most common observed type. Types are inferred, not checked against real-world truth.
Consistent record shape	20 / 20	10 of 10 records have the expected fields. CSV/TSV use the header width; JSON uses the union of observed keys.

Field-level findings and improvements

Check missing cells and mixed types below. Document intentional missing values or mixed types in your field descriptions. Do not fill legitimate unknowns with invented values just to increase this score.

Field	Missing cells	Most common type	Other populated types
open	0 / 10	number	0 / 10
high	0 / 10	number	0 / 10
low	0 / 10	number	0 / 10
close	0 / 10	number	0 / 10
volume	0 / 10	number	0 / 10
trade_count	0 / 10	number	0 / 10
vol_weighted_avg_price	0 / 10	number	0 / 10
timestamp	0 / 10	object	0 / 10
ticker	0 / 10	string	0 / 10
name	0 / 10	string	0 / 10

How the score is calculated, its limitations, and how to correct an assessment →

About this data

Minute-level OHLCV bars for US stocks and ETFs from Alpaca Markets Historical Bars API, containing over 584 million rows of price and volume data.

Retrieve with your agent or Python

Inspect historical stock bars with an authenticated data query →

Create an account and configure DATABAZAAR_API_KEY. This example retrieves free or already purchased data; it never makes a purchase. For a multi-file dataset, choose a file index from the manifest.

Download the Python example

python3 retrieve-dataset.py 89d911b1-31ee-40eb-bd09-fc3ef75a5838 --output dataset.bin

Full supplier documentation

## Overview Minute-resolution stock and ETF price bars covering US equities from 2016 through 2025. Contains 100M–1B rows across 10 columns in Parquet format, sourced from the Alpaca Markets Historical Bars API. Suitable for quantitative finance research, backtesting, time-series modeling, and agentic trading workflows. ## Schema - `open` — Float64 — opening price of the minute bar - `high` — Float64 — high price within the minute - `low` — Float64 — low price within the minute - `close` — Float64 — closing price of the minute bar - `trade_count` — UInt32 — number of trades within the minute - `volume` — UInt32 — total shares traded - `vol_weighted_avg_price` — Float64 — VWAP for the bar - `timestamp` — Datetime (ms, UTC) — bar start time - `ticker` — Categorical — ticker symbol - `name` — Categorical — company/ETF name ## Sources - CryptoSpartan/stocks_bars_1m on Hugging Face — https://huggingface.co/datasets/CryptoSpartan/stocks_bars_1m — MIT license - Underlying data: Alpaca Markets Historical Bars API — https://alpaca.markets ## Methodology The publisher scraped 1-minute OHLCV bars for a basket of US stocks and ETFs from the Alpaca Markets Historical Bars API and stored them as Parquet for efficient analytical access. Bars include VWAP and trade counts as provided by Alpaca. Timestamps are normalized to UTC milliseconds. No additional cleaning or corporate-action adjustment is documented. ## Known gaps & limitations The ticker universe is not enumerated in the dataset card — buyers should inspect the `ticker` column to confirm coverage. Corporate actions (splits, dividends) may or may not be adjusted; the source does not document this and buyers should validate empirically. Coverage of delisted tickers, after-hours/pre-market sessions, and missing-minute handling are not specified. Data depends on Alpaca's own historical record, which has its own coverage limits prior to ~2016. ## Intended use & out-of-scope - IS for: quantitative backtesting, time-series forecasting, RAG over market events, fine-tuning trading agents, intraday microstructure research. - NOT for: real-time/live trading (this is historical only), regulatory reporting, or any use that assumes corporate-action adjustment without verification. _Federated dataset: 1 parquet shards, 9.83 GB total. Queries and downloads stream through the DataBazaar API._ _PII signals: cc_shape×10 (Luhn-valid: 0) present in the sample. Common in public datasets (papers, logs) but worth knowing before joining with private data._ Original supplier listing: US Stocks & ETFs 1-Minute Bars (2016–Present) Minute-level OHLCV bars for US stocks and ETFs from 2016 onward, scraped from the Alpaca Markets Historical Bars API. Parquet format, 100M+ rows, MIT licensed.

Schema

Name	Type	Description
open	DOUBLE	Opening price in USD for the 1-minute bar.
high	DOUBLE	Highest price in USD traded within the 1-minute bar.
low	DOUBLE	Lowest price in USD traded within the 1-minute bar.
close	DOUBLE	Closing price in USD for the 1-minute bar.
volume	UINTEGER	Total number of shares traded during the 1-minute bar.
trade_count	UINTEGER	Number of individual trades executed during the 1-minute bar.
vol_weighted_avg_price	DOUBLE	Volume-weighted average price in USD for the 1-minute bar.
timestamp	TIMESTAMP WITH TIME ZONE	Bar start time in UTC with millisecond precision.
ticker	VARCHAR	Stock or ETF ticker symbol.
name	VARCHAR	Company or ETF full name.

Sample Data

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For AI Agents

Via MCP Server

# 1. Add to your agent's MCP config (claude_desktop_config.json or similar):
{
  "mcpServers": {
    "databazaar": { "command": "npx", "args": ["databazaar-mcp"] }
  }
}

# 2. Your agent can then call:
search_datasets({ query: "US Stocks & ETFs 1-Minute Bars" })
// Found: 89d911b1-31ee-40eb-bd09-fc3ef75a5838
get_download_url({ dataset_id: "89d911b1-31ee-40eb-bd09-fc3ef75a5838" })  // free — sign in with MCP OAuth first

Via REST API

# Free dataset — sign in or use your account API key:
curl https://api.databazaar.io/datasets/89d911b1-31ee-40eb-bd09-fc3ef75a5838/download-url -H "Authorization: Bearer $DATABAZAAR_API_KEY"