Beyond Basic For loops: Tidy Expressions | TidyX Episode 170

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TidyX Episode 170: Beyond Basic For loops - Tidy Expressions
We jump into the intricacies of for loops, pushing beyond the basics into the realm of Tidy Expressions, using the power of efficient coding using tidyverse functions, double curly embraces, and str2lang. By doing this, we can leverage tidyverse functions for efficient coding in custom functions and maintain the non standard evaluation tricks used by tidyverse!
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Опубликовано:

20 янв 2024

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Комментарии : 6

@ArcenisRojas 5 месяцев назад

Also, thank you both for this video!

@rayflyers 5 месяцев назад

You can accomplish it with a single pivot longer if the column names have a consistent pattern/separator. I gave the stat variables a new suffix ("_score") to make that happen. fake_dat |> rename_with(\(x) str_replace(x, "(.+\\d$)", "\\1_score")) |> pivot_longer( c(ends_with("_score"), ends_with("_n")), names_to = c("stat", ".value"), names_sep = "_", ) |> summarize( total_obs = sum(n), wgt_stat = weighted.mean(score, n), .by = c(athlete, stat) )

@zl1061 5 месяцев назад

Really appreciate the for loop solution as often running into this situation myself and I always wondered if you can do this without running the same code multiple times. This has been super helpful!