Thread by @selcukorkmaz

[1/10] 🚀 Advanced R Debugging: Debugging & error handling are essential skills for every R programmer. In this thread, we'll explore powerful tools & techniques like traceback(), browser(), & conditional breakpoints to make debugging in R a breeze. #rstats #datascience

[2/10] 📝 traceback(): When your code throws an error, use traceback() to get a detailed call stack. This function helps you identify the exact location of the error in your code, making it easier to pinpoint the issue. #rstats #debugging #datascience

[3/10] 🔍 browser(): With browser(), you can pause the execution of your code & step through it one line at a time. This interactive debugging tool allows you to inspect the values of variables and expressions, which can be a game-changer when diagnosing complex issues. #rstats

[4/10] 🎯 Conditional breakpoints: Use the debugonce() or debug() functions to set conditional breakpoints in your R code. When a specific condition is met, the execution will stop, allowing you to inspect the environment and identify potential issues. #rstats #datascience

[5/10] 🧪 Testing your code: Writing tests for your code using the testthat package can help you catch errors early on. This practice will save you time and effort in the long run, ensuring your code is reliable and robust. #rstats #testthat #datascience

[6/10] 🕵️‍♀️ Debugging Shiny apps: Use the reactiveLog() and reactiveConsole() functions to debug Shiny apps. These tools will help you understand the relationships between reactive expressions and track their execution. #rstats #shinyapps #datascience

[7/10] ⏲️ Debugging performance issues: Use the profvis package to profile your R code and identify performance bottlenecks. Optimizing your code can lead to significant speed improvements and a better user experience. #rstats #profvis #datascience

[8/10] 📚 Learning from others: When you encounter an error, don't hesitate to search for similar issues on platforms like Stack Overflow or the R mailing list. Chances are, someone has already encountered a similar problem & shared their solution. #rstats #datascience

[9/10] 🛠️ Customize error messages: Use the stop() and warning() functions to create custom error messages in your R code. This practice makes your code more user-friendly, and it can also help you identify errors more easily. #rstats #errorhandling #datascience

[10/10] 🎉 Happy debugging! Mastering these advanced debugging techniques will make you a more efficient R programmer and help you tackle even the most challenging coding issues. Keep practicing and learning, and you'll be unstoppable! 💪 #rstats #debuggingtips #datascience