In general, if you have a bunch of variables that are a variation on a theme you’re better off giving them a common prefix, rather than a common suffix, because autocomplete works best on the start of a variable. It’s easy for inconsistencies to arise when you forget a previous convention, so don’t feel bad if you have to go back and rename things. If you have a bunch of names for related things, do your best to be consistent.
TYPESTYLER II CODE
Short names save relatively little time when writing code (especially since autocomplete will help you finish typing them), but can be time-consuming when you come back to old code and are forced to puzzle out a cryptic abbreviation. # Strive for: short_flights filter ( air_time filter ( air_time < 60 )Īs a general rule of thumb, it’s better to prefer long, descriptive names that are easy to understand, rather than concise names that are fast to type. Open the palette by pressing Cmd/Ctrl + Shift + P, then type “styler” to see all the shortcuts provided by styler. The command palette lets you use any build-in RStudio command, as well as many addins provided by packages. Once you’ve installed it with install.packages("styler"), an easy way to use it is via RStudio’s command palette. Additionally, there are some great tools to quickly restyle existing code, like the styler package by Lorenz Walthert. Styling your code will feel a bit tedious to start with, but if you practice it, it will soon become second nature. This chapter will introduce to the most important points of the tidyverse style guide, which is used throughout this book. Using a consistent style makes it easier for others (including future-you!) to read your work, and is particularly important if you need to get help from someone else. Even as a very new programmer it’s a good idea to work on your code style.
Good coding style is like correct punctuation: you can manage without it, butitsuremakesthingseasiertoread. You can find the complete first edition at. This chapter should be readable but is currently undergoing final polishing. You are reading the work-in-progress second edition of R for Data Science.
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