Are There C Libraries for Statistical and Data Analysis Like R?

It depends heavily on your goal. C can handle numerical work, but it’s fairly inconvenient for manipulating higher-level data structures and experimenting with analyses. R and Python have much larger ecosystems and make this workflow considerably easier. C is usually a better fit when you need low-level control, high performance, or are working on embedded or systems software.

C doesn’t include statistical or data-analysis tools as part of the language itself, but there are many external libraries available. In fact, some of R’s underlying functionality is implemented in C, so C can provide the performance layer even though R offers a much easier interface. The available libraries vary widely depending on whether you need linear algebra, numerical methods, probability distributions, or something more specialized.

There are C libraries for many individual statistical tasks, but you generally won’t get the same integrated, convenient environment that R provides. R and Python are designed around data analysis, while C is more of a foundation that other languages and applications can build on. If ease of analysis is the priority, using R or Python directly will probably save a lot of effort.