By Matt Wiley
Application for info research utilizing R and research sensible abilities to make your paintings extra effective. This e-book covers tips on how to automate working code and the production of news to proportion your effects, in addition to writing capabilities and programs. complex R isn't designed to educate complicated R programming nor to coach the idea in the back of statistical techniques. relatively, it's designed to be a realistic consultant relocating past in basic terms utilizing R to programming in R to automate projects. This ebook will enable you to control facts in smooth R constructions and contains connecting R to info bases akin to SQLite, PostgeSQL, and MongoDB. The ebook closes with a hands-on part to get R working within the cloud. every one bankruptcy additionally contains a specified bibliography with references to analyze articles and different assets that conceal proper conceptual and theoretical subject matters.
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Extra resources for Advanced R: Data Programming and the Cloud
Another concern with loops has to do with the fact that they are functions. Although we have used that word already, we are postponing a frank discussion of functions until the next chapter. For now, just keep in mind that anything created inside a function may disappear when that function ends. In the case of loops, this happens when they stop repeating. So, if you want to hold onto results, you need to build the container for those results outside the loop. Again, we go deeper into specifics in the next chapter.
Dta") : abbreviating variable names 25 CHAPTER 2 ■ PROGRAMMING UTILITIES Figure 2-7. Output in Excel, SPSS, and Stata file formats is created from R The sink function takes console output and directs it to a file. Thus, the results of an R process may be stored for later observation or saved to a shared drive for perusal by others. The console sends only output to the file, not the input. txt") Figure 2-8. The output of the sink() function to a text file We turn our attention away from the output for a little while, knowing that we’ll revisit this topic in several more chapters.
Loops are meant to perform a task as many times as required. In R, we control these tasks in three ways. If the task should be done to a certain count, a for loop is likely best. If the task is one that we want to be done until a certain condition occurs, a while loop may be best. In particular, a while loop tests the condition that determines whether the loop runs, before the loop runs. This is critical! If the condition is already met, the while loop never runs. In the short examples you’ve seen so far, this may not seem possible or apparent, and that is okay.