# hosseinmoein/DataFrame

C++ DataFrame for statistical, financial, and ML analysis in modern C++

Repository: https://github.com/hosseinmoein/DataFrame
Canonical: https://ross.abutalabs.com/products/dataframe
Homepage: https://hosseinmoein.github.io/DataFrame/
Language: C++
License: BSD-3-Clause
License Family: permissive
Topics: numerical-analysis, dataframe, data-analysis, multidimensional-data, cpp, large-data, statistical-analysis, financial-data-analysis, financial-engineering, trading-strategies, trading-algorithms, statistical, machine-learning, data-science, tensor, tensorboard, ai
Last push: 2026-08-26T18:14:49+00:00

## Health v2 (maintenance only)
Score: 94/100 (v2, computed 2026-09-03T02:20:16.233290+00:00)
- activity 99, release rhythm 83, longevity 100
- inputs: {"age_days": 3231, "days_push": 7, "days_rel": 32, "gap_med": 76.5, "n_releases_24m": 9}
- flags: none
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 2981, forks 359 (observed 2026-08-28T04:07:33.794239+00:00)

## What it is
A high-performance, templatized C++ library providing a heterogeneous DataFrame container for in-memory data exploration, transformation, and statistical analysis, comparable to Python's Pandas or R's data.frame. It includes a large collection of built-in statistical, financial, and machine-learning algorithms as visitors, with extensive multithreading for large datasets.

## Use cases
- analyze tabular data in C++ like pandas
- compute trading indicators and financial statistics
- run statistical analysis on large datasets in C++
- group-by, join, pivot, and slice heterogeneous column data
- perform PCA, FFT, and polynomial fitting on data columns
- build ML pipelines without Python overhead

## When to choose
- you need pandas-like data manipulation in pure C++
- you process large datasets and want multithreaded performance
- you need built-in statistical, financial, or ML algorithms in C++
- you want a BSD-licensed, dependency-light analytics library

## When to avoid
- you need a rich plotting or notebook ecosystem
- your team primarily works in Python or R
- you need distributed/out-of-core processing beyond a single machine

## Facets
- artifact type: library
- maturity: active
- function: data-science, machine-learning, math, etl
- domain: data-science, machine-learning, fintech, big-data
- platform: cpp, cross-platform
- tags: dataframe, tabular-data, statistical-analysis, financial-analysis, pandas-alternative, multithreaded, in-memory-analytics

## Member repositories
- hosseinmoein/DataFrame (main) score 94

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:07:33.794239+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 2026-08-30T07:31:29.819450+00:00, confidence not recorded.
  - readme: https://github.com/hosseinmoein/DataFrame (fetched 2026-08-28T04:07:33.794239+00:00, sha 4d83e6729538)
  - homepage: https://hosseinmoein.github.io/DataFrame/ (fetched 2026-08-29T09:46:32.788474+00:00, sha 15efc9ca9e0f)
- Data as of 2026-08-30T08:39:29.467469+00:00.