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Dataframe

Dataframe is a templatized C++ library that organizes heterogeneous data in columns and rows and provides operations and analytical algorithms for statistical, financial and machine-learning applications.

Explore the practical guide ↓

Independent OpenViST project profile, based on linked sources.

Dataframe — OpenViST project profile in AI Data & Analytics.
OpenViST project illustration. See the linked sources for product details.
Understand the project

Practical overview

When it fits

Use it when a C++ application needs in-memory data exploration, transformation or analysis, including work with large datasets where its multithreaded API may be relevant.

Who it is for

  • C++ developers building data-analysis software.
  • Teams creating statistical or financial analysis tools.
  • Developers preparing or analyzing data for machine-learning applications.

Documented uses

  • Represent heterogeneous data in columns, including nested DataFrames or other containers.
  • Slice, join, merge, group, pivot, sort and select data.
  • Run statistical and numerical analysis such as means, moving averages, PCA, polynomial fitting and FFT.
  • Apply financial indicators or add custom analytical algorithms.
Before you choose

Requirements & limits

The project is open source under the BSD-3-Clause license. The README identifies C++23 and Linux, macOS and Windows.

  • The library is designed for C++ applications and uses C++ templates.
  • Columns can hold varied types and nested containers, supporting multidimensional structures.
  • The API includes data-manipulation operations, analytical visitors and custom algorithm support.
  • The project describes extensive multithreading for large datasets and states that it depends only on C++ and its standard library.

Check current requirements in the official documentation. Source-based guidance does not mean OpenViST has run or independently tested this project.

Source-based practical guide

Access columns in a DataFrame

Retrieve a DataFrame column using its name or index and compile-time type.

Before you start

  • A DataFrame instance with the desired column.
  • The column name or index and its type must be known at compile time.

Steps

  1. Identify the column by its name or index.

  2. Use the DataFrame get_column interface to access it.

Expected outcome

The requested column is accessed through the DataFrame API.

Guide limitations

  • The column type must be known at compile time.
  • The documentation lists get_column but does not provide a complete code example in the available material.
Documentation 1 ↗
Evidence and transparency

Sources & review

Official repository ↗Guide documentation ↗
Source record details
Source availability
Active
Sources checked
10 October 2026
Original website title
hosseinmoein/DataFrame · Official homepage title · retained in its source language
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