README.md

In fio: Friendly Input-Output Analysis

{fio}

Friendly & Fast Input-Output Analysis [](https://CRAN.R-project.org/package=fio) [](https://albersonmiranda.r-universe.dev/fio) [](https://github.com/albersonmiranda/fio/actions/workflows/R-CMD-check.yaml) [](https://app.codecov.io/gh/albersonmiranda/fio?branch=main) [](https://CRAN.R-project.org/package=fio) `{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](https://rstudio.github.io/rstudioaddins/) 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](https://r6.r-lib.org/) for clean, memory-efficient object-oriented programming. Furthermore, all linear algebra computations are implemented in [Rust](https://www.rust-lang.org/) to achieve highly optimized performance. ## Installation ### CRAN Release You can install the latest stable release of {fio} from CRAN with: wzxhzdk:0 ### Latest tested version install the latest tested but unreleased version from the [main branch](https://github.com/albersonmiranda/fio/tree/main), use the precompiled binaries available on [R-universe](https://albersonmiranda.r-universe.dev/fio): wzxhzdk:1 ### Development version For the cutting-edge development branches from Github, you’ll need to compile it from source. This requires [Rust](https://www.rust-lang.org/) to be installed on your system. You can install Rust using the following commands: - Debian/Ubuntu: `sudo apt install cargo` - Fedora/CentOS: `sudo dnf install cargo` - macOS: `brew install rust` - Windows: ## Getting Started If you are just getting started with `{fio}`, we recommend you to read the [vignettes](https://albersonmiranda.github.io/fio/articles/index.html) for a comprehensive overview of the package. ## Examples Calculate Leontief’s inverse from brazilian 2020 input-output matrix: wzxhzdk:2 And pronto! 🎉, you’re all good to carry on with your analysis. You can evoke the Data Viewer to inspect the results with `iom_br$technical_coefficients_matrix |> View()` and `iom_br$leontief_inverse_matrix |> View()`.  *Leontief’s inverse from brazilian 2020 input-output matrix* ## Related tools Other great tools for input-output analysis in R include: - [{leontief}](https://pachamaltese.github.io/leontief/) - [{ioanalysis}](https://cran.r-project.org/package=ioanalysis)

fio documentation built on April 11, 2025, 6:11 p.m.