Dataset
indian-stock-market-minute-data
Minute-level open-high-low-close-volume bars for Indian equities, hundreds of millions of rows in Parquet under MIT. Gives high-frequency microstructure across the Indian cash market for intraday and market-on-close strategies.
Data preview
Dataset card
xxparthparekhxx/indian-stock-market-minute-data is a Hugging Face dataset of historical price history for 2,500+ NSE stocks and indices, offered in minute and daily frequency. It is distributed as Parquet shards intended for time-series loading via the datasets, dask, or polars libraries.
What this dataset contains
The dataset covers NSE-listed equities and indices from 2000 through 2026, provided in two splits: a minute-level intraday series and a daily series, totalling roughly 720 million rows. Minute data is delivered across sharded Parquet files grouped by ticker letter ranges, while daily data sits in a separate, smaller file. The published metadata does not state a license, so commercial reuse should be confirmed with the publisher before ingestion.
Structure and fields
Each row carries a symbol identifier, a timestamp in UTC microsecond precision, and standard OHLCV pricing fields: open, high, low, and close as float32, and volume as int64. An additional int64 field named oi is present, typically used for derivatives open interest, though its applicability here depends on the instrument. Rows can be filtered by the symbol column to isolate a single ticker such as RELIANCE, and the minute split is sorted by symbol for efficient sequential reads.
How analysts use it
Long-horizon Indian equity backtests, intraday volatility studies, and NSE index return attribution are natural fits given the depth and continuity of the series. Quant teams can stream the minute shards for execution-cost research or build daily factor models from the lighter day split. Because minute data is large, analysts usually filter by symbol or sample a subset of tickers before loading into modeling pipelines.
Documentation & references 1
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