Скачать или смотреть Mastering rlang and tidyselect: Passing Variables Between Functions in R

Discover how to effectively call and pass variable names between functions in R using `rlang` and `tidyselect`. This guide simplifies the process and provides practical examples.
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This video is based on the question https://stackoverflow.com/q/73912560/ asked by the user 'cdcarrion' ( https://stackoverflow.com/u/11570343/ ) and on the answer https://stackoverflow.com/a/73913019/ provided by the user 'Juan C' ( https://stackoverflow.com/u/9462829/ ) at 'Stack Overflow' website. Thanks to these great users and Stackexchange community for their contributions.

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Mastering rlang and tidyselect: Passing Variables Between Functions in R

When working with R, especially in data manipulation with libraries like dplyr, there may come a time when you want to call or pass variable names from one function to another. This can often lead to confusion, especially if you're using advanced tools like rlang and tidyselect. In this guide, we will guide you through a common scenario and its solution, ensuring that your functions can communicate effectively.

The Problem: Calling Variables from One Function to Another

Imagine you have two functions: f1() and f2(). In f1(), you want to summarize data based on a variable, while in f2() you want to utilize that summary and pass another set of variable names along for further calculations. The challenge lies in correctly passing these variable names without hardcoding them, and ensuring that the results are printed correctly.

Let’s take a look at the example code snippet to illustrate this problem:

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The Solution: Adjusting Functions for Variable Passing

Step 1: Refine the f1() Function

In f1(), we’ll replace the hardcoded variable name with the ability to handle dynamic input using {{}} syntax from rlang. This allows R to understand that varname is a variable to evaluate rather than a string.

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Step 2: Update the f2() Function

In f2(), we need to apply similar improvements and use tidyselect to extract the variable names dynamically. Here’s an updated version of f2() that achieves our goal:

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Step 3: Running the Function

Finally, when you run f2() with your data frame and the control variable names, it should look something like this:

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This will produce the output where you see calculated variables and respective groupings presented clearly.

Example Output

Expected output from having run the above function might look like this:

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Conclusion

By enhancing the design of your functions and utilizing rlang and tidyselect effectively, you've simplified how you interact with variable names in R. Now, you can confidently call variables from one function to another without hardcoding values, making your code cleaner and more maintainable.

Always remember, when working with R, harnessing the power of libraries and understanding the syntax can transform how you manage data and build functions. Happy coding!