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r programming interview questions and answers

R Programming Interview Questions and Answers

R Programming Interview Questions and Answers

R Programming languages are very much helpful in data visualization, forecast analysis, data manipulation, statistical analysis, predictive modeling, and many more. As this programming is used by various top-rated companies like Facebook, Google, and Twitter, interviews are becoming tougher these days and hence we are here providing the most frequently asked questions along with the solutions. This would really help all the candidates to overcome the interview and online tests easily. We have covered most of the important topics like SAS, SPSS, Python, Data Structures in R, Loading CSV files, the process to install a package, linear regression models in R, confusion matrix and many more to look at. If you excel in the interview by reading through this material, you can easily get the career roles like Data Analyst, Quantitative Analyst, Business Analyst, Data Scientist, and Data Visualization expert.

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Best R Programming Interview Questions and Answers

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Q1) What are all the operators in R?

  • Arithmetic Operators
  • Rational Operators
  • Logical Operators
  • Assignment operators

Q2) What are all the arithmetic operators?

Addition, Subtraction, Multiplication, Division are the basic arithmetic operators. In R, it is generally used to declare using with same representations as +, -, *, / respectively. Apart from this, we have %%, which gives the remainder value & ^ to an exponent.

Q3) What are all the relational operators?

<, >, <=, >= ==, != are the relational operators where the first vector is against the second vector in R.

Q4) What are all the Logical operators?

R supports 3 Logical operators. Where & refers the AND operator, | refers the OR operator and ! represents the NOT operator.

 Q5) What are all the assignment operators?

Assignment operators have 2 ideas of assignment. Left assignment operators & Right assignment operators. = cannot be used as the right assignment operator.
Left assignment operators are: <- | <<-  | =
Right assignment operators are: ->  | ->>

 Q6) What does: colon operator refers to?

It helps to create a sequence. When a sequence has to be declared, : operator is being utilized.
Example: 1:10, will result in 1 2 3 4 5 6 7 8 9 10.

 Q7) What are all the decision statements in R?

IF, IF_ELSE, Switch are the 3 decision statements in R.

 Q8)  What are all the Loops in R?

In R, we have FOR, WHILE & REPEAT loops. Loops help to make the certain executions repetitive for the given conditions.

 Q9)  Is R a General-Purpose Language?

  1. R is a statistical language which is hardcore for any statistical analysis. It doesn’t support general developments like other languages, such as Python & Java.

Q10) How can be a vector is represented in R?

A vector can be of any dimensions. Even any variables saved with 1 value, it becomes a vector. Greater than 1 dimension, vectors can be created using the function c().
Example: A = 1:5 results 1 2 3 4 5. A = c(1,2) results 1 2.

Q11) Is it possible to declare multiple data types within a vector in R?

No, the data types will be coerced. If it is a vector with few numeric data points and if any one data point is a character, vector will be coerced to character data type.

Q12) Do the Arithmetic operations are possible in a vector?

Yes, all arithmetic operations are possible in a vector.

Q13) How will the two vectors of different lengths will be applied in any arithmetic operations?

If the two vectors are of unequal lengths, the vector which is less in length will be repeated until the operation is getting performed.
Example:             a = c(1,2)              |              1 2                          # a becomes 1 2 1 2
b = c(3:6)             |              3 4 5 6
a+b                        |              4 6 6 8

Q14)  What does DMwR package does?

DMwR stands for Data Manipulation with R. Where this package is one of the widely used package for any data manipulations.

Q15) What is the package used for data operations?

Lubridate. This package is widely used for any data analysis on the date. It includes dates processing of seconds, minutes & hours with predefined functions of s, m, and h respectively.

Q16) Is the list mutable in R?

Yes, a list is editable in R. List is one of the widely used objects in R. Where it can have multiple data types within one list. Not like vector, which doesn’t support multiple data types within one vector. List can have a list within a list.

Q17) Is it possible to convert a list to a vector?

Yes. A list can be converted into a vector. UNLIST is a predefined function which converts a list to the vector. This function delists a list and produces output as a vector.
Example: sample_List = list(1:5)                 |              [1]          1 2 3 4 5
unlist(sample_list)           |              1 2 3 4 5

Q18) What is difference between matrix & Data frame?

Matrix & Data frame has a similar structural object. But data frame can have different data types in the different column. Where matrix cannot have different data types.

Q19) Do matrix support arithmetic operations?

Yes, all arithmetic operations are possible in a matrix.

Q20) What is the factor in R?

Factor is an object in R, which converts a vector to a categorizable object level. Which it can have N levels.

Q21) what are all the functions used to get the structure & summary of the data frames?

  • str() – Will get the structure of the data frame
  • summary() – will give you the summary of the data frame. The summary function gives you the MIN, MAX, MEAN, 1st, 2nd, 3rd

Q22) How to merge two different data frames by row & column level to the data frame in R?

rbind() – It merges the two data frames by row level in the data
cbind() – It merges the two different data frames by column level in the data.

Q23) Explain MAX & MIN function.

MAX – It will give you the maximum value of the data. Eg: max(data_frame$Column_name)
MIN – It will give you the minimum value of the data. Eg: min(data_frame$Column_name)

Q24) How to read/write a CSV file in R?

read_csv() – this function reads the data to R.
write.csv() – this function writes the data from R.

Q25) Can we connect MySQL with R?

Yes,  dbConnect() – function can be used to connect the MySQL.
dbSendQuery() – this function helps SQL query to be applied in R to get those query results in R.

Q26) Name the data structures in R?

  • Vector
  • List
  • Array
  • Matrix
  • Tables
  • Data frame

Q27) What are all the advantages of a MarkDown file?

RMD files help to create a better reporting portable code file.
RMD helps to generate the HTML file which can be transferred which doesn’t demand data for processing.

Q28) What is R-Shiny?

R shiny is a package which helps to generate the web application from R. It does support the CSS, Java-script integrations.

Q29) How to calculate the character count of a variable or in a vector?

str_count() – this function helps to count the number of strings in the variable or in the vector.

Q30) What are the functions to calculate mean, median & mode in R?

mean() – this function calculates mean value.
median() – this function calculates the median value.
Unlike mean & median, we don’t have a pre-defined function in R for Mode. We must derive it for our own.

Q31) How can we apply Linear regression in R?

lm() – this function helps us to build a linear regression model, which results from the slope and intercept values of the model.

Q32) Which package do the lm() function uses?

Linear regression function(lm()) uses stats package in R. Linear regression included in the machine learning family, but it is just a statistical idea, where it helps to predict. Technically it is not a machine learning model.

Q33) How to create a scatter plot in R?

plot(x,y) – this function will create a scatter plot in R. It needs to get 2 parameters given, both should be numeric.

Q34) Can the normal vector can be parsed to a time series model?

No, normal data cannot parse directly. Data has to be converted into a time series data using ts() function in R.

Q35) Is it possible to do joins in R? if yes, name the functions.

Yes, Join functions are possible in R.

  • left_join() – this performs the left join
  • right_join() – this performs the right join
  • inner_join() – this performs the inner join
  • full_join() – this performs the full join

Q36) How to get the column names of a data frame in R?

colnames() – this function will result from the column names of a data frame.

Q37) What is the memory limitation of R?

R will support 3GB memory if it is a 32-bit processor and it is a 64-bit processor, It does support till 8TB.
Q38) What correlation is being used in R? what is the function to get a correlation in R?
R uses Pearson correlation in default. Cor() – function gives the correlation between the columns. Pearson correlation cannot be applied for a categorical column.

 Q39) Do R support reverse indexing?

No, R doesn’t support reverse indexing. Rather, if you use – with index, it drops it.

Q40) What is the difference between install.packages() & installed.packages() in R?

Install.packages() – will install package to your local system from CRAN/Git.
installed.packages() – will give the list of packages that have been installed in a local system.

 Q41) Is it possible to do arithmetic operations between a vector & a list in R?

No, it is not possible to do arithmetic operations between two different data types. It will result in the error.

 Q42) What is the difference between the array and the matrix?

All Matrix can be called as the array, but all array cannot be called as Matrix. It is because that, a matrix will always have a 2 dimension, where the array can have any dimension in nature.
Q43) How to create a logistic regression model in R?
GLM() – this function builds a logistic model, we have to make sure the family parameter is BINOMIAL. Because GLM stands for Generalised Linear Models. Where this function can perform other generalized models like Gaussian.

 Q44) What are all the functions for performing a Kmeans & Kmeans-Plus plus Clustering algorithms?

Kmeans() – Performs Kmeans algorithm for the given data, K parameter is a mandate.
KmeansPP() – performs Kmeans-Plus-plus algorithm. K parameter is a mandate.
Q45) Name some packages which can be used to perform different algorithms in R?

  • randomForest – To build a random Forest algorithm
  • rpart – To build a CART algorithm
  • C50 – To build a C5.0 algorithm
  • naive Bayes – To build a Naïve Bayes algorithm
  • XP boost – To build an XG boost Algorithm
  • fastAdaboost – To build a Ada Boost algorithm
  • stats – To build both Linear & Logistic regression, models

 Q46) Is it possible to do a Data transpose in R?

Yes, we can do transpose the data in R. t() – function will transpose the data in R.

 Q47) How to identify the number if missing values in a data frame in R?

is.na() function will result whether the data point is NA or not. To sum it up and get the number of missing values, we can use both sum & is.na function together to achieve it.
sum(is.na(data_frame)) will result from the number of NA values in the data frame.

 Q48) Is it possible to import a text file in R?

Yes, you can use read.table() function from utils package to import it.

 Q49) What are all the different ways of sub-setting data in R?

[] – subsets with Index values
subset() – performs with the given condition, includes row names in results
filter() – performs with given condition, excludes row names in results
select() – performs with the conditions, similar to SQL select statement

 Q50)  How to set a working directory and to get the path of it?

setwd() – function sets the current working directory
getwd() – function gets the path of the working directory.

Q51) What’s your evaluation about the bang pack in R?

  • The rattle is a famous GUI for data mining using R.
  • It presents quantifiable and visual rundowns of data, changes data with the objective that it might be immediately showed up, builds both free and controlled AI models from the data, presents the introduction of models graphically, and scores new datasets for sending into creation.
  • A key combine is that the whole of your correspondences through the graphical UI is gotten as a R content that can be immediately executed in R straightforwardly of the Rattle interface.

Q52) Uncover to me something about gleaming.

  • Cleaned is a R pack that makes it easy to assemble adroit web applications direct from R.
  • You can have independent applications on a page or supplement them in Rmarkdown records or amass dashboards.
  • You can in like manner expand your Shiny applications with CSS subjects, HTML devices, and JavaScript works out.

Q53) What is Rmarkdown? What is its utilization?

RMarkdown is a declaring device given by R. With the help of Rmarkdown, you can make extraordinary reports of your R code.
The yield course of action of Rmarkdown can be:

  • HTML
  • PDF
  • WORD

Q54) Explain what is R?

R is a data evaluation programming that is used by stars, quants, pros, data examiners, and others.

Q55) How you can import Data in R Programing?

  • You use R position to import Data in R, and there are three astounding courses through which you can enter data into it
  • You can enter data truly by procedures for Data  New Data Set
  • Import data from a plain substance (ASCII) or various annals (SPSS, Minitab, etc.)
  • Explore an educational once-over either by making the name out of the informative assortment or picking the enlightening once-over in the trade box

Q56) Mention what doesn’t ‘R’ language do?

Regardless of the way in which that R programming can without a great deal of a stretch interface with DBMS isn’t a database

Q57) Does exclude any graphical UI Using R?

Expelling the way that it interfaces with Excel/Microsoft Office successfully, R language doesn’t give any spreadsheet viewpoint on data

Q58) Explain R bearing are encircled?

In R, wherever in the program, you have to display the line of code with a #sign, for example
# subtraction
# division
# note offers of exercises exists

Q59) What system may you save your data in R?

To save data in R, there are various ways, at any rate, the least referencing procedure for doing this is
Go to Data > Active Data Set > Export Active Data Set and a trade box will appear, when you click OK the talkbox empowers you to save your data in the ordinary way.

Q60) Notice how you can pass on co-relations and covariances?

You can make co-relations by the cor () ability to pass on co-relations and cov () ability to make covariances.

Q61) Explain what is t-tests in R?

  • In R, the t.test () work driving forces t-tests.
  • The T-test is the most all things considered saw test in experiences and used to pick if the frameworks for two gatherings are proportionate to each other.

Q62) What are the various techniques for working with R?

  • In R, information modes and classes outline the basic characteristics and direct of an information object.
  • For instance, various modes and classes are regulated contrastingly by center motivations driving covering like print(), audit(), and plot().

Q63) What is the factor information type in R?

  • Reasonably, factors can’t avoid being factors in R which take on a predestined number of various attributes; such factors are persistently suggested as unmitigated segments.
  • Factors in Rare controlled as a vector of whole number properties with an isolating way of thinking of character respects with use when the factor is showed up.

Q64) What does factor work do in R?

R factor Function. R factors variable is a vector of clear information. factor() work makes a factor variable and figures the unmitigated dispersing of vector information.

Q65) What is an information pack in R?

R – Data Frames. Affiliations. An information group is a table or a two-dimensional show like structure in which each zone contains estimations of one variable and each line contains one part of qualities from every district.

Q66) What is a R structure?

  • Structures are the R request where the parts are made in a two-dimensional rectangular approach.
  • They contain portions of the obscure nuclear sorts. … A Matrix is made utilizing the structure() work.

Q67) What is the thing in R?

  • We can do battle empowered programming in R. Truth be told, everything in R is a thing.
  • A thing is an information structure having a couple of qualities and systems which follow up on its properties.
  • Class is a structure for the thing.The best number of houses can be passed on using an outline, we can make different things from a class.

Q68) What is the utilization of the cross part gathering?

Cross a zone pack is to improve base R delineations by giving better defaults and it can without a ton of a stretch show multivariate affiliations.

Q69) Explain how data is amassed in R.

Two techniques are disintegrating data by using, in any event, one BY factors and the other in the aggregate() work in which the BY factor should be on the structure.

Q70) What is basic to fall away from conviction?

Key slip into awful conduct is used to envision the twofold outcome from the given methodology of undaunted marker factors.

Q71) Depict Poison falls from conviction.

It is used to envision the outcome variable which tends to counts from the given arrangement of never-ending pointer factors.

Q72) What is the utilization of subset() and test() work in R?

A subset () is used to pick the fragments and statements and test() work is used to pass on a self-picked case of the size n from a dataset.

Q73) What is prescribed by K-nearest neighbor?

K-Nearest Neighbor is one of the clearest AI request figurings that is a subset of oversaw learning subject to slow learning. In this estimation, the explanation behind the restriction is approximated locally and any figurings are surrendered until request.

Q74) How can you resample quantifiable tests in the R language?

  • The coin bunch in R gives various decisions to pre-randomization and stages subject to veritable tests.
  • Totally when test suppositions can’t be met then this social gathering fills in as the best choice instead of old-style techniques as it doesn’t see sporadic looking wonderfully delineated masses.

Q75) What is the R Base pack?

R Base party is the pack that is stacked by the standard at whatever point the R programming condition is stacked .R base get-together gives essential functionalities in R condition like math estimations, input/yield.

Q76) What cutoff may you join two data plots in the R language?

Data plots in R language can be joined physically using tie () limits or by using the association () handle supervisor lines or pieces.

Q77) What Objects Do You Use Most Often in R?

  • It’s needs to get a feeling of how experienced you are in R programming with this inquiry.
  • Be set up by knowing, in detail, a portion of your ongoing work and clarify your most regularly utilized items, while additionally clarifying how and why you use them.

Q78) What Are Some of Your Favorite R Programming Functions?

  • In case you’re meeting for a vocation in R writing computer programs, it’s not simply significant that you comprehend and know R all around, however that you’re enthusiastic about it, as well.
  • It ought to anticipate that as a specialist in R, you’ll not exclusively have the option to effectively think of capacities on the spot yet that you can without much of a stretch name the ones you like the most. Make certain to respond to this inquiry with certainty and eagerness.

Q79) What is the pack among library() and require() works in R language?

There is no obvious most far off period within the two if the packs are not being stacked inside the most remote point. require () work is routinely used inside the cutoff and drives rebuff at whatever point a particular pack isn’t found. If all else fails side, the library () work gives a good message if the perfect pack can’t be stacked.

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