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MARIO
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  • Installation
  • Table formats
  • Scenarios
Docs
  • Data sources
  • Working with a database
  • Calculations and analysis
  • Transformations and scenarios
  • Configuration
  • Examples
  • API reference
Resources
  • Database explorer
  • Projects & Publications
  • Teaching
  • Downloadable material

Input-output analysis in Python

Work with input-output and supply-use tables, from reading a database to building scenarios and analysing impacts across regions and sectors.

pip install mariopy
Get started

Get started ↗

Set up MARIO and learn the essentials.

  • Installation Install MARIO and prepare your Python environment.
  • Table formats Read IOT and SUT structure, indices and matrix names.
  • Scenarios Organise and compare different model scenarios.

Documentation ↗

Find a guide for every step of your workflow.

  • Data sources Choose a source, import its tables and understand its metadata.
  • Working with a database Explore sets and matrices, find classification codes and export data.
  • Calculations and analysis Calculate matrices, characterize emissions and interpret results.
  • Transformations and scenarios Aggregate or convert a table, extend its accounts and build scenarios.
  • Configuration Choose computation settings and customize your Python session.
  • Examples Follow complete analyses with downloadable notebooks.
  • API reference Look up signatures, parameters, returned values and equations.

Resources ↗

Explore databases, applications and learning material.

  • Database explorer Compare classifications, explore indicators and read analyses.
  • Projects & Publications Discover the research built with MARIO.
  • Teaching Learn through courses and guided examples.
  • Downloadable material Download notebooks, set lists and reference sheets.

Cite MARIO

Using MARIO in your research? Please cite the software paper.

Tahavori, M. A., Golinucci, N., Rinaldi, L., Rocco, M. V., & Colombo, E. (2023). MARIO: A Versatile and User-Friendly Software for Building Input-Output Models. Journal of Open Research Software · 11.

doi.org/10.5334/jors.473

BibTeX
@article{Tahavori2023,
    author = "Tahavori, Mohammad Amin and Golinucci, Nicolò and Rinaldi, Lorenzo and Rocco, Matteo Vincenzo and Colombo, Emanuela",
    doi = "10.5334/jors.473",
    issn = "2049-9647",
    journal = "Journal of Open Research Software",
    month = "10",
    title = "MARIO: A Versatile and User-Friendly Software for Building Input-Output Models",
    volume = "11",
    year = "2023"
}

Supporting institutions

MARIO connects academic research and applied analysis.

Politecnico di MilanoResearch and scientific development eNextGenApplied analysis and decision support
MARIO

Multifunctional Analysis of Regions through Input-Output

Get startedDocsResources Changelog GitHubPyPI

© 2026, Lorenzo Rinaldi, Mohammad Amin Tahavori, Nicolo Golinucci AI disclosure. This documentation and its database explorer were written and built with AI agents, then reviewed by the MARIO team, who remain responsible for their content. Spotted an error? Tell us on GitHub Issues.

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