- It has a bunch of different types of classes, and they all behave differently. Debugging isn't awful, but it's harder than it should be. Also, the documentation isn't clear about which classes to use.
- A lot of the workhorse functions suffer from parameter glut. Despite having different kinds of classes, almost all functions expect plain vectors. Packages like survival show how objects make it easier to read code, reuse data, and validate data. Without the base packages doing it more, everyone's chosen their own systems. The community's been gravitating to organizing "objects" as rows in tables (i.e. tidy).
- The way a function uses an argument might surprisingly change based on other arguments given (e.g., `binom.test`). And then the documentation won't have examples for the different use cases.
- Most users don't have the time or desire to become better R programmers. They have other work to do. For my own work, I write packages with custom classes, functions, and template documents. For collaboration, I keep things very plain and rarely go beyond dplyr; very often, the script goes between two steps executed in a GUI software.
- It has a bunch of different types of classes, and they all behave differently. Debugging isn't awful, but it's harder than it should be. Also, the documentation isn't clear about which classes to use.
- A lot of the workhorse functions suffer from parameter glut. Despite having different kinds of classes, almost all functions expect plain vectors. Packages like survival show how objects make it easier to read code, reuse data, and validate data. Without the base packages doing it more, everyone's chosen their own systems. The community's been gravitating to organizing "objects" as rows in tables (i.e. tidy).
- The way a function uses an argument might surprisingly change based on other arguments given (e.g., `binom.test`). And then the documentation won't have examples for the different use cases.
- Most users don't have the time or desire to become better R programmers. They have other work to do. For my own work, I write packages with custom classes, functions, and template documents. For collaboration, I keep things very plain and rarely go beyond dplyr; very often, the script goes between two steps executed in a GUI software.