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{fio}

Friendly & Fast Input-Output Analysis

{fio} (Friendly Input-Output) is a R package designed for input-output analysis, emphasizing usability for Excel users and performance. It includes an RStudio Addin and a suite of functions for straightforward import of input-output tables from Excel, either programmatically or directly from the clipboard.

The package is optimized for speed and efficiency. It leverages the R6 class for clean, memory-efficient object-oriented programming. Furthermore, all linear algebra computations are implemented in Rust to achieve highly optimized performance.

Installation

CRAN Release

You can install the latest stable release of {fio} from CRAN with:

install.packages("fio")

Latest tested version

install the latest tested but unreleased version from the main branch, use the precompiled binaries available on R-universe:

install.packages("fio", repos = c("https://albersonmiranda.r-universe.dev", "https://cloud.r-project.org"))

Development version

For the cutting-edge development branches from Github, you’ll need to compile it from source. This requires Rust to be installed on your system. You can install Rust using the following commands:

Getting Started

If you are just getting started with {fio}, we recommend you to read the vignettes for a comprehensive overview of the package.

Examples

Calculate Leontief’s inverse from brazilian 2020 input-output matrix:

# load included dataset
iom_br <- fio::br_2020

# calculate technical coefficients matrix
iom_br$compute_tech_coeff()

# calculate Leontief's inverse
iom_br$compute_leontief_inverse()

And pronto!

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Version

Install

install.packages('fio')

Monthly Downloads

11,497

Version

0.1.6

License

MIT + file LICENSE

Issues

Pull Requests

Stars

Forks

Maintainer

Alberson da Silva Miranda

Last Published

April 6th, 2025

Functions in fio (0.1.6)

import_element

Import IOM data
br_2020

Brazil input-output matrix, year 2020, 51 sectors
fio_addin

Conveniently import data from an Excel file
iom

R6 class for input-output matrix