If you’re up-to-date with the programming world, you might have often heard about the R language from various sources. So, what is this language all about?
R is an open-source programming language. Its implementation includes Data Visualization, Statistical Analysis, Forecast Analysis, Predictive Modeling, Data Manipulations, and many more.
Enormous businesses like Facebook, Google, Twitter, etc., make use of the R language. This article provides a compilation of the top 20 R interview questions that applicants must know before applying for job interviews!
Before we get to the R language interview questions, let us first examine the R language definition.
R is a free software environment and a programming language as well. It involves Statistical Computing and Graphics.
Statisticians and Data Miners extensively implement R for developing statistical software and Data Analysis. It is a popular programming language. As of September 2020, R holds the 9th rank in the TIOBE index. The TIOBE index estimates the popularity of programming languages.
Let us now examine the top 20 interview questions in R!
The following is a list of 20 R basic interview questions that prepare interviewees for their interviews.
The following functions are some of the many R functions –
Even though Python and R have a similar model, there is a significant difference between them. For instance, R has a better Model Interpretability than Python. On the other hand, Python provides better Production. When it comes to Community Support, R has the upper hand over Python. Moreover, R offers excellent Data Visualization Libraries and Tools. Nonetheless, Python is more comfortable to learn compared to the R language.
To import data in R, we use the R commander. Using any of the following three ways, we can successfully import data –
R offers the following five Sorting Algorithms –
The disadvantages of using R are below –
The rbind() function joins two datasets. They must have the same variables, but they do not have to be in the same order.
We can use diverse methods to save data in R, but the most straightforward approach is as follows –
Go to Data -> Active Data Set -> Export Active Data Set
Here, a dialogue box will appear. Click ‘ok’ on the dialogue box to save your data.
To start the R commander GUI, type the command – Rcmdr – into the R console.
Some data structures that R uses for Statistical Analyses and creation of graphs –
The subset() function selects variables and observations.
The sample() function chooses a random sample of size n from a dataset.
The following code helps us to create a table in R without using an external file –
mytable = data.frame()
This code will open a spreadsheet to enter your data quickly.
R provides various methods to re-shape data before analysis, and transpose is the simplest of them all. To transpose a matrix or a data set, we use the t() function.
When using the aggregate() function, we should use the BY variable.
In R, NA (Not Available) represents missing values.
To represent the impossible values, R uses NaN (not a number).
The t.test() function creates various t-tests. In Statistics, a T-test is the most common test determining if the means of the required two groups are equal.
You can produce co-relations using the cor() function and produce covariances using the cov() function.
In a 32-bit system, the memory limit is 3Gb, but most versions are limited to 2Gb. In a 64-bit system, the memory limit of R is 8Tb.
Coin package helps achieve the Re-randomization or Permutation-based Statistical tests.
R is a programming language with multiple implementations. Understanding these interview questions on R help learners to increase their chances of getting hired.
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