Use this free online tool to convert C# code to R with just one click!
Here's how:
1. Type or paste your C# code into the input box.
2. Click the 'Convert' button.
3. See your R code appear in the output box.
1. Type or paste your C# code into the input box.
2. Click the 'Convert' button.
3. See your R code appear in the output box.
To
Key differences between C# and R
Characteristic | C# | R |
---|---|---|
Type | Compiled, statically-typed programming language | Interpreted, dynamically-typed programming language |
Memory Management | Automatic memory management with garbage collection | Automatic memory management (Garbage Collection) |
Platform Dependency | Runs on .NET Framework or .NET Core | Platform-independent, runs on any system with R installed |
Syntax and Features | Object-oriented programming, modern language features, LINQ, async/await | Vectorized operations, high-level data analysis, statistical computing |
Compilation | Compiled to Common Intermediate Language (CIL) bytecode, then Just-In-Time (JIT) compiled to machine code by .NET runtime | Interpreted by the R interpreter |
Standard Library | .NET Framework or .NET Core with extensive standard library and ecosystem | Comprehensive standard library for data analysis, statistics, and visualization |
Object-Oriented Programming | Fully supports object-oriented programming with classes, interfaces, inheritance, and other features | Supports multiple OOP systems (S3, S4, R6) |
Concurrency | Built-in support for multithreading and asynchronous programming with async/await | Supports parallel computing with packages like parallel and future |
Use Cases | Web development, desktop applications, mobile apps (Xamarin), enterprise software | Statistical analysis, data visualization, data science, bioinformatics |
Performance | Optimized for performance, generally faster due to compilation to native code | Generally slower due to being interpreted, but optimized for data analysis tasks |
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