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Thinking in R vs. Thinking in SAS

Coming into the Data Science Specialization with years of experience in SAS and SPSS, it took a concerted effort to understand some of the key concepts in R well enough for to use them effectively, such as:

Everything that exists is an object.
Everything that happens is a function call.

-- John Chambers, quoted in Advanced R (1)

As I progressed through the Specialization and began work as a Community TA, I noticed other students struggling with the same issue, especially students who had prior experience with SAS. Arguably, one's SAS experience becomes an impediment to learning R to the degree that we expect R to work like SAS.

For example, once you've had experience in SAS, you tend to think about sorting like this:

 * read the mtcars data set from the R datasets library,
 * after having written it with a pipe delimiter and no column names

data mtcars;
   infile "/folders/myfolders/mtcars.tsv" dlm="|";
   input vehicle : $20. mpg cyl disp hp drat wt qsec vs am gear carb;
 * sort the data by cyl and mpg
proc sort data = mtcars out = sorted;
   by cyl mpg;
 * print the data
proc print data = sorted;


The R version of sorting requires either loading a package specifically designed to sort data frames, or knowledge of syntax to coerce the vector-oriented order() function to operate on a data frame by ordering the rows as an operation within the row component of the dataFrame[rows , columns] syntax as follows:

# use base::order() to sort the data frame by cyl and mpt
orderedData <- mtcars[order(mtcars$cyl,mtcars$mpg),]

               mpg cyl  disp  hp drat    wt  qsec vs am gear carb
Volvo 142E    21.4   4 121.0 109 4.11 2.780 18.60  1  1    4    2
Toyota Corona 21.5   4 120.1  97 3.70 2.465 20.01  1  0    3    1
Datsun 710    22.8   4 108.0  93 3.85 2.320 18.61  1  1    4    1
Merc 230      22.8   4 140.8  95 3.92 3.150 22.90  1  0    4    2
Merc 240D     24.4   4 146.7  62 3.69 3.190 20.00  1  0    4    2
Porsche 914-2 26.0   4 120.3  91 4.43 2.140 16.70  0  1    5    2

The "out of box" R solution to the sort problem would not seem intuitive to a SAS programmer. As we gain experience with R and learn about the existence of packages such as Hadley Wickham's dplyr, we discover that third party package developers have built a variety of capabilities to shield people from some of the complexities of the base language for common data manipulation tasks. For example, dplyr's arrange() function arranges rows in a data frame based on the values of one or more variables.

While these features are helpful to reduce the amount of R code required for common data manipulation tasks, it's still important to understand how R works under the covers in order to use these packages correctly.

Bottom line: if you're used to working with SAS and expect R to behave in a similar manner (e.g. R must have a sort() function that works on data frames, not vectors), you're in for a steep learning curve while you "unlearn" how one does things in SAS, or find the third party packages that support features whose behavior is more similar to SAS.


(1) Wickham, Hadley (2015) -- Advanced R, CRC Press, Boca Raton, FL