In akrmenec/efficient-R: Becoming an Efficient R Programmer

Exercises {-}

1. The final line in the code chunk above shows a neat feature of rio and some other packages: the output format is determined by the suffix of the file-name, which make for concise code. Try opening the voc_voyages.xlsx file with an editor such as LibreOffice Calc or Microsoft Excel to ensure that the export worked, before removing this rather inefficient file format from your system:

   r file.remove("voc_voyages.xlsx")

   To verify that the file saved as an Excel file correctly, try opening it, e.g. with LibreOffice, as illustrated below.

   r knitr::include_graphics("graphics/xls-screen.png")

2. Try saving the the voyages data frames into 3 other file formats of your choosing (see vignette("rio") for supported formats). Try opening these in external programs. Which file formats are more portable?

To see the range of export options supported by rio, consult the documentation:

library("rio")
?export

Three output options suported by the package are illustrated below:

export(cars, "cars.psv") # relatively unusual but highly portable
export(cars, "cars.json") # portable web-friendly format
export(cars, "cars.sav") # can be read-in by SPSS, not portable

1. As a bonus exercise, create a simple benchmark to compare the write times for the different file formats used to complete the previous exercise. Which is fastest? Which is the most space efficient?

   Of the above examples, .sav was the fastest:

   ```r library(microbenchmark) microbenchmark(times = 10, export(cars, "cars.json"), # portable web-friendly format export(cars, "cars.psv"), # relatively unusual but highly portable export(cars, "cars.sav") # can be read-in by SPSS, not portable )

   Unit: microseconds

   expr min lq mean median uq

   export(cars, "cars.json") 847.734 856.760 1046.0637 1004.2230 1257.855

   export(cars, "cars.psv") 630.689 641.662 693.5819 684.9845 733.419

   export(cars, "cars.sav") 197.913 218.843 265.2692 232.7065 273.377

   ```

   We can use file.size() to test the file size of the resulting files:

   r f_cars = list.files(pattern = "cars") knitr::kable(data.frame( Format = c(".json", ".psv", ".sav"), Size = file.size(f_cars) )) file.remove(f_cars) # remove excess files

   |Format | Size| |:------|----:| |.json | 1144| |.psv | 308| |.sav | 1220|

akrmenec/efficient-R documentation built on May 28, 2019, 4:53 p.m.