MARIO Documentation#

MARIO (Multifunctional Analysis of Regions through Input-Output) is a Python package for handling Input-Output Tables (IOT) and Supply and Use Tables (SUT). It is designed to make common IO workflows accessible without requiring deep programming expertise, while still exposing the full flexibility needed for research and applied analysis.

What you can do#

MARIO can parse tables from many well-known sources out of the box, including EXIOBASE (monetary), EXIOBASE (hybrid), EORA, EUROSTAT, FIGARO, WIOD, OECD, and more. When data are not already structured for a known format, MARIO also accepts custom databases through Excel, CSV, text files, or pandas DataFrames.

Supported table types include single-region and multi-region systems, monetary and hybrid tables, Input-Output Tables, and Supply and Use Tables.

Beyond parsing, MARIO provides a set of analytical and transformation tools:

  • aggregation of sectors, regions, and extensions;

  • SUT-to-IOT transformation;

  • adding new sectors, activities, commodities, and satellite extensions;

  • scenario and shock analysis;

  • backward and forward linkage analysis;

  • extraction of single-region tables from multi-region databases;

  • balance and productivity checks;

  • export to Excel, text, and Parquet formats.

Quickstart#

After installing MARIO, you can perform a quick test with the minimal IOT or SUT example databases included in the package. For example, for IOT workflows:

import mario

iot = mario.load_test("IOT")
print(iot)
print(iot.get_index("Region"))

iot.calc_all()
iot.to_excel(path="output_folder")

For SUT workflows:

sut = mario.load_test("SUT")
print(sut)
print(sut.get_index("Sector"))

sut.calc_all()
sut.to_txt(path="output_folder", coefficients=True)

Detailed documentation and examples are available in the user guide.

Citation#

If you use MARIO in academic work, please cite:

[1]

Tahavori, M. A., Golinucci, N., Rinaldi, L., Rocco, M. V., and Colombo, E. Mario: a versatile and user-friendly software for building input-output models. Journal of Open Research Software, 10 2023. doi:10.5334/jors.473.

The full list of publications using MARIO is in the Research page.

Supporting institutions#

MARIO grows across two complementary settings.

Politecnico di Milano Politecnico di Milano Development stays closer to the academic side: research methods, modelling choices, scientific validation, and documentation-oriented workflows.
eNextGen eNextGen As a spin-off of Politecnico di Milano, eNextGen brings MARIO into applied settings for companies and organisations, where the same analytical core supports real decarbonisation, sustainability, and decision-support cases.