CodeConvert AI - Convert code with a click of a button

CodeConvert

How to use this tool?

This free online converter lets you convert code from R to Fortran in a click of a button. To use this converter, take the following steps -

Type or paste your R code in the input box.
Click the convert button.
The resulting Fortran code from the conversion will be displayed in the output box.

Key differences between R and Fortran

Characteristic	R	Fortran
Syntax	R has a syntax that is similar to the S programming language, which is designed for data analysis and visualization. It has a wide range of built-in functions and operators that make it easy to manipulate data.	Fortran has a syntax that is optimized for scientific and engineering applications. It is designed to be easy to read and write, with a focus on mathematical operations and array processing.
Paradigm	R is a functional programming language that is designed for data analysis and statistical computing. It supports object-oriented programming and procedural programming as well.	Fortran is a procedural programming language that is designed for scientific and engineering applications. It supports structured programming and object-oriented programming to some extent.
Typing	R is a dynamically typed language, which means that the data type of a variable is determined at runtime. It is also a weakly typed language, which means that the type of a variable can be changed during runtime.	Fortran is a statically typed language, which means that the data type of a variable is determined at compile time. It is also a strongly typed language, which means that the type of a variable cannot be changed during runtime.
Performance	R is not as fast as Fortran when it comes to numerical computations, but it is optimized for data analysis and visualization. It has a wide range of built-in functions and libraries that make it easy to manipulate data.	Fortran is one of the fastest programming languages when it comes to numerical computations. It is optimized for scientific and engineering applications and has a wide range of libraries and frameworks for numerical analysis and simulation.
Libraries and frameworks	R has a wide range of libraries and frameworks for data analysis, statistical computing, and visualization. Some of the popular libraries include ggplot2, dplyr, and tidyr.	Fortran has a wide range of libraries and frameworks for scientific and engineering applications. Some of the popular libraries include LAPACK, BLAS, and FFTW.
Community and support	R has a large and active community of users and developers. There are many online resources and forums available for learning and getting help with R.	Fortran has a smaller community compared to R, but it is still an active and well-supported language. There are many online resources and forums available for learning and getting help with Fortran.
Learning curve	R has a steep learning curve for beginners, especially those who are not familiar with programming or statistical analysis. However, there are many online resources and tutorials available for learning R.	Fortran has a steep learning curve for beginners, especially those who are not familiar with programming or scientific computing. However, there are many online resources and tutorials available for learning Fortran.

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