Guides / 31 October 2026

NIFTY options historical data archive: how a multi-year archive is organised

A NIFTY options historical data archive from 2020: how the files are laid out by day and expiry, how to index years of data quickly, and how to choose a window.

A multi-year NIFTY options archive is thousands of files. The useful question is not "how big is it?" but "can I find any contract on any day in a second?". This guide shows how our NIFTY archive is organised and how to put an index on top of it.

Layout

One folder per year, one Parquet file per trading day per listed expiry:

NIFTY/
  2020/NIFTY_OPT_1min_2020-01-02_exp2020-01-02.parquet
  ...
  2026/NIFTY_OPT_1min_2026-10-27_exp2026-10-28.parquet
  2026/NIFTY_FUT_1min_2026-10-27_exp2026-11-25.parquet   (Complete packs)
  2026/NIFTY_SPOT_1min_2026-10-27.parquet                (Complete packs)

Each option row is one contract in one minute: strike, call or put, expiry, open, high, low, close, volume and open interest.

Build a catalogue once

import re
from pathlib import Path
import pandas as pd

pat = re.compile(r"NIFTY_OPT_1min_(\d{4}-\d{2}-\d{2})_exp(\d{4}-\d{2}-\d{2})")
cat = pd.DataFrame([(m[1], m[2], str(f)) for f in Path("NIFTY").rglob("*.parquet")
                    if (m := pat.search(f.name))], columns=["day", "expiry", "path"])
cat.to_parquet("catalogue.parquet")

# later: every file for one expiry, or one day, without walking the disk
print(cat[cat.expiry == "2024-06-27"].path.tolist()[:3])

Choosing how much history

• One year if you are testing a single idea: 2023, 2024.
• Three years to see it across expiry-rule changes: 3 years.
• The whole archive with futures and the index: since 2020.

Older files use slightly different column names. The FAQ shows how to map them.