Posted on : 18 Mar, 2021, 09:53:45 AM
Created by : Somya Goswami
R is one of the advanced open-source programming languages used to operate and verify multiple tasks, including statistical analysis, data visualization, predictive modeling, forecast analysis, data manipulations, etc. According to the survey, the R programming language is considered the fastest-growing field in the software or IT industry. It is used in all the major organizations like Google, Facebook, Twitter, etc.
This blog covers the list of the top 50 frequently asked questions during the R interview that candidates most likely encounter. That’s why Wissenhive decided to target the most important R programming interview questions with answers that candidate must prepare for:
R refers to a programming language and software development platform for statistical graphics and computing that the R foundation supports. The R programming language is broadly used in various areas by data miners, statisticians, and data analytics, to develop statistical software with advanced features.
There are many advantages of the R language, and those advantages are
NA or Not Available is used to represent missing values, whereas NaN or Not a Number represents impossible values. Mentioning deleted missing values is not a good idea as the probable causes for missing values can raise some problems in programming and data collection. That’s why it is important to find the root cause of missing values to take the necessary steps to handle them.
|Features||Python Programming Language||R Programming Language|
|Model Building||They both are similar.||They both are similar.|
|Model Interpretability||Python is not better than R||R is better than Python.|
|Production||Python is better than R||R is not better than Python.|
|Community Support||Python is not better than R||R is better than Python.|
|Data Science Libraries||They both are similar.||They both are similar.|
|Data Visualizations||Python is not better than R||R is better than Python|
|Learning Curve||Learning Python is more manageable than R||R has a steep learning curve.|
|Features||Python Programming Language||R Programming Language|
|Scope||Used for multiple purposes like data analysis and web application development||Primarily used for statistical modeling|
|Suitable For||Newbie to experienced IT professionals||People with no prior experience in programming|
|Database Handling Capacity||Can handle extensive data easily without any fault||Poses problems for handling extensive database|
|Essential Packages And Library||
R Commander is used to importing data in R language. To start the GUI R commander, the user must type the Rcmdr command into the console. There are three different alternates to import data in the R programming language.
|Data Structure||Detailed Description|
|Vector||It is a sequence of some basic types of data elements and vector members known as components.|
|List||It refers to R objects which include different types of elements such as strings, numbers vectors, or sub-lists.|
|Matrix||It is a two-dimensional structure that is used to bind multiple vectors from the same length. Elements included in the same types are logical, complex, numeric, characters.|
|Dataframe||It is more generic than matrix, i.e., different columns include different types of data such as character, numeric and logical, etc. It also combines the main features of matrix and rectangular list.|
There are different components available in the grammar of graphics.
|Require ()||Library ()|
|Used for inside function and informs while sending message whenever particular packages are founded||It gives an error message display if the desired package is not loaded.|
|The checks loaded the package and loaded the unloaded packages.||Loads all the packages whether they are ready or not|
R Markdown refers to documents that provide reproductive and quick reporting from the R. Professionals write documents in markdown to embed executable R code chunks with the advanced knitr syntax. R Markdown allows users to update the document at any time with the help of re-knitting the code chunks. After creating and updating, the user can convert the document into multiple formats.
There are three different types of the output format of R markdown, and those are
There are three popular and effective steps to merge and combine dataset in R, and those strategies are
There are some of the packages available in R that is used for data imputation, and those are
A confusion matrix refers to the procedure that evaluates the accuracy of the building model. The confusion matrix calculates a cross-tabulation of predicted and observed classes. This procedure can be done by using the “confusion matrix()” function from the “caTools” package.
It gives you a tabular representation of lists that is divided into two values, and those are
|Dataframe stores data tables that include multiple data types in various columns called fields.||Matrix refers to the collection of the dataset that arranges rectangular organization into two dimensional.|
|It refers to a vector list of equal lengths that is the generalized form of the matrix||It refers to the m*n array with a similar data type.|
|It has a variable number of columns and rows||It has a fixed number of columns and rows.|
|The data stored must be a numeric, factor, or character type.||The data stored in columns should be the same data type.|
|DataFrames are heterogeneous.||The matrix is homogeneous.|
Dplyr is a primary collection of functions that are designed to enable manipulative data frames in a user-friendly and intuitive way. It is one of the key packages of the tidyverse in the R language. Data investigators or analysts prefer using dplyr to transform or convert existing datasets into a better-suited format for some particular type of data visualization and analysis.
There are some of the particular function provided in dplyr packages, which includes
Use Of The By () Functions - The by( ) function applies a function to each level of factor or factor, which is similar to BY processing in SAS.
Use Of The With () Functions - The with( ) function applies an expression to a dataset, which is similar to DATA= in SAS.
All the packages available in R include the collection of data. R packages functions and compiles code in a well-defined and organized format that is usually stored in the library. One of the strong strengths of R is the user-written function in the R programming language.
Workspace refers to a current R working environment that includes many user-friendly objects such as data frames, functions, vectors, lists, matrices. At the end of the R session, the working user can save the current workspace image that automatically reloaded R the next time when R is started.
In Object-Oriented Programming, encapsulation refers to the binding of method and data inside the class. The R6 package provides an implementation of encapsulated OOP systems for the R language. The R6 package presents an R6 class that is similar to the R reference class, but they are independent of the S4 classes. Along with the public and private members, R6 classes support inheritance even if the classes are defined in various packages.
To create a new R6 class, following specific steps are important. building an object template is the first step that consists of the ‘’Class Functions’’ and ‘’Data Members’’ presents in the class
An R6 object template includes three parts, and those are
To install packages in R following and applying a specific command and that command is
There are five different types of sorting algorithms are available, and those are
Loading a .csv file in R language is quite an easy process to achieve. You just need to follow one simple step to load the file using the “read.csv()” function and just specifying the file’s path.
For an example -
Transpose refers to a process of reshaping the data that will be used for analysis. It is performed by the t() function. Transposing in R, reverse the columns and the rows, which is considered one of the simple reshaping methods in a dataset.
A cluster refers to a collection of objects that always belongs to a similar class. Clustering is the process of making a group of abstract objects or unlabeled examples into classes of similar objects. It includes two different types of clustering, and those are
There are more than 100 types of clustering algorithms, but some of the important algorithms are very popular, and those are
The t-test is a process, which is used to determine whether two different groups are equal or not. It is one of the common tests in statistics to check that both the groups are normally distributed with equal variances or not by using the t-tests function.
There are separate functions to produce covariance and correlation, and that can be produced by functions such as
|Indicate both the strength and direction of the linear relationship between two variables||Indicate the direction of the linear relationship between variables|
|Correlation values are standardized.||Covariance values are not standard|
|Either it brings a strong positive correlation, or it brings a negative correlation.||A positive number brings a positive relationship, and a negative number brings a negative relationship.|
|Value remains strictly between -1 to 1.||Values between positive infinity to negative infinity|
There is not a huge difference when it comes to differentiating these two terms. Both are used to show inputs but in different forms.
The R Commander provides an open-source, and free user interface for R software, focusing on helping learners learn R commands by point-and-clicking their way through analyses. The R Commander is available for various devices such as Linux, Windows, and Mac as there is no server version.
Memory limit totally depends on a bit system. A large-bit system will provide a better memory limit. Mostly it comes in two different bit systems, and those are 32-bit system and 64cbit system.
To aggregate the data, professionals need to specify three points in the code.
Then there are two methods to collapse all the data that should be aggregated, and those two methods are by using.
The functions that are used to merge two horizontal data frame or two vertical data frame are
Power analysis refers to a process where multiple statistical parameters are calculated. It is used to define experimental designs used to determine the actual effect of provided sample data size with given sample size or expected size, alpha, and power.
The package name that is used for power analytics in R is known as the Pwr package.
There are several ways to export the data into various formats, such as
The package used to export the data in R is the xlsReadWrite package which is used for formats that include.
GGobi is made for inactive data visualization, which is free statistical software, allows users to explore extensive data with interactive dynamic graphics. It is also known as a multivariate data tool. R uses this in sync through rggobi with GGobi. This software can be embedded as a library in program packages and other packages using API or as an add-on to scripting environments and existing languages.
The full form of MANOVA is a multivariate analysis of variance, which is used to test more than one dependent variable simultaneously.
Here, we Wissenhive covered the top 50 questions with answers from beginner to advanced level to give the candidate a strong idea about interview questions that they might encounter during the R interview.
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