# jealous/stockstats

Supply a wrapper ``StockDataFrame`` based on the ``pandas.DataFrame`` with inline stock statistics/indicators support.

Repository: https://github.com/jealous/stockstats
Canonical: https://ross.abutalabs.com/products/stockstats
Language: Python
License: NOASSERTION
License Family: other
Last push: 2026-06-19T22:46:31+00:00

## Health v2 (maintenance only)
Score: 80/100 (v2, computed 2026-09-03T02:20:16.233290+00:00)
- activity 88, release rhythm 59, longevity 100
- inputs: {"age_days": 3741, "days_push": 75, "days_rel": 198, "gap_med": 41, "n_releases_24m": 6}
- flags: no_license
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 1486, forks 317 (observed 2026-08-28T04:04:51.869905+00:00)

## What it is
A Python library providing a StockDataFrame wrapper around pandas.DataFrame for computing stock statistics and technical indicators inline. It supports dozens of indicators like RSI, MACD, Bollinger Bands, and moving averages with lazy column-based access.

## Use cases
- calculate technical indicators like rsi and macd on stock price data
- compute bollinger bands and moving averages with pandas
- detect golden cross and crossover signals in stock data
- add stock statistics columns to a pandas dataframe
- backtest trading strategies with technical indicators

## When to choose
- you already use pandas and want inline indicator computation on OHLCV data
- you need a wide range of technical indicators with simple column-based syntax

## When to avoid
- you need a full backtesting or live trading framework
- your data is not in OHLCV format or you work outside the pandas ecosystem

## Facets
- artifact type: library
- maturity: active
- function: data-science, analytics, math
- domain: fintech, data-science, analytics
- platform: python
- tags: stock-indicators, technical-analysis, pandas, trading, time-series

## Member repositories
- jealous/stockstats (main) score 80

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:04:51.869905+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-30T04:33:51.864892+00:00, confidence not recorded.
  - readme: https://github.com/jealous/stockstats (fetched 2026-08-28T04:04:51.869905+00:00, sha 50b4a7f296bc)
  - registry_pypi: https://pypi.org/pypi/stockstats/json (fetched 2026-08-29T11:40:01.247485+00:00, sha e06ed38043ee)
- Data as of 2026-08-30T08:39:29.467469+00:00.