4 Tricky R interview questions

Analytics industry in India is dominated by SAS currently. But, it will be too optimistic to hope that this remains to in years to come. R, on the other hand is open source, and can be implemented in any environment. SAS grows by efforts of smart people employed by SAS but  R grows by the effort of anyone who works on the language. Anyone can contribute to the language R. Hence, I feel that every analyst should develop expertise in both the languages.

There are some key differences in coding on R vs. coding on SAS. This makes some of the interview questions on R tricky and handling them becomes overwhelming for some candidates. I strongly feel a need of a common thread which has all the tricky R questions asked in interviews. This article will give a kick-start to such a thread.  We have a similar series of articles published on SAS (Part 1 and Part 2). Please note that the content of this article is based on the information I gathered from various R sources.

If you’re looking to understand these questions through the lens of cracking data science interviews, look no further! We have put together a comprehensive course to help you land your first data science role!

[stextbox id=”section”] Question 1 : Rotational multiplication [/stextbox]

You have two vector defined as follows :

[stextbox id=”grey”]

> a <- c(2,3,4) 
> b <- c(1,2)

[/stextbox]

What is the value of the vector d, which is defined as follows :

[stextbox id=”grey”]

> d <- a*b

[/stextbox]

Answer : 2 , 6 , 4

R language does vectorized operations. ‘a’ and ‘b’ are two vectors with different length. By process, R multiplies the first element of a with 1st element of b, than second element of a with that of b, and so on. But in this case, after the second multiplication R hits the end of vector “b”. In such cases R, starts with the first element of smaller vector till each element of longer vector is exhausted. The vectorized operation always leads to a vector of length equal to that of longer vector.

[stextbox id=”section”] Question 2 : Scoping Rules [/stextbox]

You need to understand the following code and answer a question based on this understanding.

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> y <- 3

> f <- function(x) {

+                            y <- 2

+                            y ^ 2 + g(x)

+                            }

> g <- function(x) {

+                             x * y

+                             }

[/stextbox]

What is the value of f(6)?

Answer : 22

If you answered anything other than 22, you probably need to refresh the lexical scoping in R.  The function f(x) returns a value y^2 + g(x). y in this environment has been defined as 2 and g(x) from inside this function. The value of x is passed of function g as 6. Now comes the catch, what is the value of free variable y here? Unlike dynamic environment where the value is assumed from the parent environment, lexical scoping assumes the value of a variable from the environment where the function is defined. The function g(x) is defined in the global environment here, and hence the value of y is assumed to be 3. Therefore a value of 18 is returned from the function g(x).  f(6) is finally returning as 22.

[stextbox id=”section”] Question 3 : Summarizing at each factor [/stextbox]

You have been assigned to check two race tracks. To complete this task you are expected to find the means of the total time taken by cars to cross the track. In the following data assignment, “b” is the vector of total time taken by different cars and “a” is the vector of track on which this time is taken. The first element of the vector “b” corresponds to the first element of vector “a” (and so on).

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> a <- c(1,1,1,1,2,2,2,2,2)

> b <- c(10,12,15,12,NA,30,42,38,40)

[/stextbox]

How do you find the mean time of each track using split function?

Answer : Code is as follows 

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> s <- split(b,a)

> lapply(s,mean)

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[stextbox id=”section”] Question 4 : Treating missing values [/stextbox]

$`1` [1] 12.25

$`2` [1] NA

> lapply(s,mean,na.rm=TRUE)

$`1` [1] 12.25

$`2` [1] 37.5

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Tavish Srivastava

Tavish Srivastava, co-founder and Chief Strategy Officer of Analytics Vidhya, is an IIT Madras graduate and a passionate data-science professional with 8+ years of diverse experience in markets including the US, India and Singapore, domains including Digital Acquisitions, Customer Servicing and Customer Management, and industry including Retail Banking, Credit Cards and Insurance. He is fascinated by the idea of artificial intelligence inspired by human intelligence and enjoys every discussion, theory or even movie related to this idea.