** R Interview Questions**

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### All Interview Company Interview Technical Interview Web Interview PHP Interview .Net Interview Java Interview Database Interview R Interview Questions 1 What is R 2 Differentiate between vector, List, Matrix, and Data frame. 3 Give names of those packages which are used for data imputation. 4 Explain initialize function in R 5 How can we find the mean of one column with respect to another 6 What is a Random Walk model 7 What is a White Noise model 8 Give any five features of R. 9 Differentiate between R and Python in terms of functionality 10 What are the applications of R 11 Explain RStudio. 12 What are the advantages and disadvantages of R 13 What is the purpose behind R and Hadoop integration 14 Give the name of the Hadoop integration methods. 15 What will be the output of the expression allNANA 16 What is the difference bw sample and subset in R 17 Why do we use the command install.packagesfile.choose, reposNULL 18 Give the command to create a histogram and to remove a vector from the R workspace 19 Differentiate bw and . 20 Why do we use apply function in R 21 Differentiate between library and require functions. 22 What is the ttest in R 23 What is the use of with and by functions in R 24 Differentiate bw lapply and sapply. 25 Explain aggregate function. 26 Explain the doBy package 27 Explain the use of the table function. 28 Explain fitdistr function 29 What are GGobi and iPlots 30 Explain the lattice package. 31 Explain anova function. 32 Explain cv.lm and stepAIC function. 33 Explain leaps function. 34 Explain relaimpo and robust package. 35 Give full form of MANOVA and what is the use of it. 36 Explain mashapiro.test and barlett.test. 37 Explain the use of the forecast package. 38 Differentiate between qda and lda function. 39 Explain the auto.arima and principal function. 40 Explain FactoMineR. 41 What is the full form of SEM and CFA 42 Define cluster.stats and pvclust function. 43 Define MATLAB and party packages. 44 Explain S3 and S4 systems. 45 Give names of visualization packages. 46 Explain ChiSquare Test 47 Explain Random Forest. 48 Explain Time Series Analysis. 49 Explain Pie chart in R. 50 Explain Histogram. Javatpoint Services Training For College Campus Learn Tutorials Our Websites Our Services Contact

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### 100 Data Science in R Interview Questions and Answers for 2018

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Data Science Top 50 R Interview Questions You Must Prepare in 2020 R Interview Questions 1. What are the different data structures in R Briefly explain about them. 2. How can you load a .csv file in R...

### Data Science Top 50 R Interview Questions You Must Prepare in 2020 R Interview Questions 1. What are the different data structures in R Briefly explain about them. 2. How can you load a .csv file in R 4. What is Rmarkdown What is the use of it 5. How do you install a package in R 6. What are the steps to build and evaluate a linear regression model in R 10. Name some functions available in dplyr package. 11. How would you create a new R6 Class 12. What is a Random Forest How do you build and evaluate a Random Forest in R 13. Tell me something about shinyR. 14. What is advantage of using apply family of functions in R 15. What packages are used for data mining in R 16. What is clustering What is the difference between kmeans clustering and hierarchical clustering 17. Give examples of rbind and cbind functions in R 18. Give examples of while and for loop in R. 19. Give examples of select and filter functions from dplyr package. 20. What is the use of stringR package. Give some examples of the functions in Stringr. 21. What do you know about the rattle package in R 22. How would you make multiple plots onto a single page in R 23. How would you create a scatterplot using ggplot2 package 24. How would you facet the data using ggplot2 package 25. Given a vector of values, how would you convert it into a time series object 26. What is a White Noise model and how can you simulate it using R 27. What is a Random Walk model and how can you simulate it using R 28. What is Principal Component Analysis and how can you create a PCA model in R 29. How would you find out the mean of one column w.r.t another 30. Explain about initialize function in R 31. How would you fit a linear model over a scatterplot 32. What do you know about the evaluatemodel function from statisticalModeling Package 33. How would you build a Scatterplot using plotly 34. What is the difference between a barchart and a histogram Where would you use a barchart and where would you use a histogram 35. How would you create a boxplot using plotly 36. How would you do a left and right join in R 37. What is a factor How would you create a factor in R 38. Given a vector of numbers, how would you turn the values into scientific notation 41. What are the different import functions in R 42. Name some functions which can be used for debugging in R 43. How would you check the distribution of a categorical variable in R 44. How would you rename the columns of a dataframe 45. How would you find the number of missing values in a dataset and remove all of them 46. What is correlation How would you measure correlation in R 47. How would you extract one particular word from a string 48. From the below dataset, extract only those values where Age60 and SexF. 49. You have an employee dataset, which comprises of two columnsname and designation, add a third column which would indicate the current date and time. 50. How would you do a crossproduct of two tables in R Recommended videos for you Python Numpy Tutorial Arrays In Python Python Programming Learn Python Programming From Scratch Application of Clustering in Data Science Using RealTime Examples Sentiment Analysis In Retail Domain 3 Scenarios Where Predictive Analytics is a Must Mastering Python An Excellent tool for Web Scraping and Data Analysis Python List, Tuple, String, Set And Dictonary Python Sequences The Whys and Hows of Predictive ModelingII Python Loops While, For and Nested Loops in Python Programming The Whys and Hows of Predictive ModellingI Introduction to Business Analytics with R Python Classes Python Programming Tutorial Linear Regression With R Machine Learning with Python Android Development Using Android 5.0 Lollipop Know The Science Behind Product Recommendation With R Programming Business Analytics Decision Tree in R Web Scraping And Analytics With Python Python Tutorial All You Need To Know In Python Programming Business Analytics with R Recommended blogs for you What is Business Analytics All you Need to Know Data Analyst vs Data Engineer vs Data Scientist Skills, Responsibilities, Salary A Beginners Guide To Python Functions How to Implement Membership Operators in Python Top 10 Reasons to Learn R What are the Best Books for Data Science The Importance of Data Science with Cloud Computing Python Visual Studio Learn How To Make Your First Python Program How To Run A Python Script Scrapy Tutorial How To Make A WebCrawler Using Scrapy How To Run Python In Ubuntu Linux String Trimming in Python All you Need to Know Why Should a Statistical Professional Know R A Comprehensive Guide On How To Learn Data Science All You Need To Know About Statistics And Probability Top 10 Data Science Applications What are Sets in Python and How to use them Everything you Need to Know about Python Environment Big Data Analytics BigQuery, Impala, and Drill Top 50 R Interview Questions You Must Prepare in 2020 Join the discussionCancel reply Trending Courses in Data Science Data Science Certification Training with Pyth ... 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### Top 18 R Programming Interview Questions Answers

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All Interview Company Interview Technical Interview Web Interview PHP Interview .Net Interview Java Interview Database Interview R Interview Questions 1 What is R 2 Differentiate between vector, List,...

### All Interview Company Interview Technical Interview Web Interview PHP Interview .Net Interview Java Interview Database Interview R Interview Questions 1 What is R 2 Differentiate between vector, List, Matrix, and Data frame. 3 Give names of those packages which are used for data imputation. 4 Explain initialize function in R 5 How can we find the mean of one column with respect to another 6 What is a Random Walk model 7 What is a White Noise model 8 Give any five features of R. 9 Differentiate between R and Python in terms of functionality 10 What are the applications of R 11 Explain RStudio. 12 What are the advantages and disadvantages of R 13 What is the purpose behind R and Hadoop integration 14 Give the name of the Hadoop integration methods. 15 What will be the output of the expression allNANA 16 What is the difference bw sample and subset in R 17 Why do we use the command install.packagesfile.choose, reposNULL 18 Give the command to create a histogram and to remove a vector from the R workspace 19 Differentiate bw and . 20 Why do we use apply function in R 21 Differentiate between library and require functions. 22 What is the ttest in R 23 What is the use of with and by functions in R 24 Differentiate bw lapply and sapply. 25 Explain aggregate function. 26 Explain the doBy package 27 Explain the use of the table function. 28 Explain fitdistr function 29 What are GGobi and iPlots 30 Explain the lattice package. 31 Explain anova function. 32 Explain cv.lm and stepAIC function. 33 Explain leaps function. 34 Explain relaimpo and robust package. 35 Give full form of MANOVA and what is the use of it. 36 Explain mashapiro.test and barlett.test. 37 Explain the use of the forecast package. 38 Differentiate between qda and lda function. 39 Explain the auto.arima and principal function. 40 Explain FactoMineR. 41 What is the full form of SEM and CFA 42 Define cluster.stats and pvclust function. 43 Define MATLAB and party packages. 44 Explain S3 and S4 systems. 45 Give names of visualization packages. 46 Explain ChiSquare Test 47 Explain Random Forest. 48 Explain Time Series Analysis. 49 Explain Pie chart in R. 50 Explain Histogram. Javatpoint Services Training For College Campus Learn Tutorials Our Websites Our Services Contact

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Data Science Top 50 R Interview Questions You Must Prepare in 2020 R Interview Questions 1. What are the different data structures in R Briefly explain about them. 2. How can you load a .csv file in R...

### Data Science Top 50 R Interview Questions You Must Prepare in 2020 R Interview Questions 1. What are the different data structures in R Briefly explain about them. 2. How can you load a .csv file in R 4. What is Rmarkdown What is the use of it 5. How do you install a package in R 6. What are the steps to build and evaluate a linear regression model in R 10. Name some functions available in dplyr package. 11. How would you create a new R6 Class 12. What is a Random Forest How do you build and evaluate a Random Forest in R 13. Tell me something about shinyR. 14. What is advantage of using apply family of functions in R 15. What packages are used for data mining in R 16. What is clustering What is the difference between kmeans clustering and hierarchical clustering 17. Give examples of rbind and cbind functions in R 18. Give examples of while and for loop in R. 19. Give examples of select and filter functions from dplyr package. 20. What is the use of stringR package. Give some examples of the functions in Stringr. 21. What do you know about the rattle package in R 22. How would you make multiple plots onto a single page in R 23. How would you create a scatterplot using ggplot2 package 24. How would you facet the data using ggplot2 package 25. Given a vector of values, how would you convert it into a time series object 26. What is a White Noise model and how can you simulate it using R 27. What is a Random Walk model and how can you simulate it using R 28. What is Principal Component Analysis and how can you create a PCA model in R 29. How would you find out the mean of one column w.r.t another 30. Explain about initialize function in R 31. How would you fit a linear model over a scatterplot 32. What do you know about the evaluatemodel function from statisticalModeling Package 33. How would you build a Scatterplot using plotly 34. What is the difference between a barchart and a histogram Where would you use a barchart and where would you use a histogram 35. How would you create a boxplot using plotly 36. How would you do a left and right join in R 37. What is a factor How would you create a factor in R 38. Given a vector of numbers, how would you turn the values into scientific notation 41. What are the different import functions in R 42. Name some functions which can be used for debugging in R 43. How would you check the distribution of a categorical variable in R 44. How would you rename the columns of a dataframe 45. How would you find the number of missing values in a dataset and remove all of them 46. What is correlation How would you measure correlation in R 47. How would you extract one particular word from a string 48. From the below dataset, extract only those values where Age60 and SexF. 49. You have an employee dataset, which comprises of two columnsname and designation, add a third column which would indicate the current date and time. 50. How would you do a crossproduct of two tables in R Recommended videos for you Python Numpy Tutorial Arrays In Python Python Programming Learn Python Programming From Scratch Application of Clustering in Data Science Using RealTime Examples Sentiment Analysis In Retail Domain 3 Scenarios Where Predictive Analytics is a Must Mastering Python An Excellent tool for Web Scraping and Data Analysis Python List, Tuple, String, Set And Dictonary Python Sequences The Whys and Hows of Predictive ModelingII Python Loops While, For and Nested Loops in Python Programming The Whys and Hows of Predictive ModellingI Introduction to Business Analytics with R Python Classes Python Programming Tutorial Linear Regression With R Machine Learning with Python Android Development Using Android 5.0 Lollipop Know The Science Behind Product Recommendation With R Programming Business Analytics Decision Tree in R Web Scraping And Analytics With Python Python Tutorial All You Need To Know In Python Programming Business Analytics with R Recommended blogs for you What is Business Analytics All you Need to Know Data Analyst vs Data Engineer vs Data Scientist Skills, Responsibilities, Salary A Beginners Guide To Python Functions How to Implement Membership Operators in Python Top 10 Reasons to Learn R What are the Best Books for Data Science The Importance of Data Science with Cloud Computing Python Visual Studio Learn How To Make Your First Python Program How To Run A Python Script Scrapy Tutorial How To Make A WebCrawler Using Scrapy How To Run Python In Ubuntu Linux String Trimming in Python All you Need to Know Why Should a Statistical Professional Know R A Comprehensive Guide On How To Learn Data Science All You Need To Know About Statistics And Probability Top 10 Data Science Applications What are Sets in Python and How to use them Everything you Need to Know about Python Environment Big Data Analytics BigQuery, Impala, and Drill Top 50 R Interview Questions You Must Prepare in 2020 Join the discussionCancel reply Trending Courses in Data Science Data Science Certification Training with Pyth ... Python Programming Certification Training Machine Learning Certification Training Data Science Certification Course using R Data Analytics with R Certification Training Statistics Essentials for Analytics Advanced Predictive Modelling in R Certificat ... SAS Training and Certification Analytics for Retail Banks Decision Tree Modeling Using R Certification ... Browse Categories Subscribe to our Newsletter, and get personalized recommendations.

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### 60 R Interview Questions and Answers New Clear your technical round DataFlair

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R Interview Questions R Interview Questions for Beginners Q1 Describe the R environment Features Q2 Who and what are the uses of the R software environment Q3 What are the statistical features of R Q4...

### R Interview Questions R Interview Questions for Beginners Q1 Describe the R environment Features Q2 Who and what are the uses of the R software environment Q3 What are the statistical features of R Q4 Explain the evolution of the language R Q5 Explain the application of R Programming in the real world Q6 Please state alternatives to the R programming Q7 Explain the programming features of R Q8 Explain the role of packages in R Q9 Explain RStudio Q10 What is the role of variables in the R programming language Q11 Explain different Robjects Q12 Explain RVariables Q13 Provide examples of various invalid and valid variables and state the reason for validation Q14 What is a variable assignment Q15 Explain the functionality of the data type of variable Q16 What are the functions of finding and deleting variables Q17 List various graphical representations present in the R programming language Q18 Explain statistical functions performed by R Q19 Which data object in the language R is utilized to store and process categorized data Q20 Explain the R base package

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R Programming Interview Questions Programming Beginner 1.Given data related to specific parameter for a country for a particular year is mentioned in Table 1. Provide an approach or write a program fu...

### R Programming Interview Questions Programming Beginner 1.Given data related to specific parameter for a country for a particular year is mentioned in Table 1. Provide an approach or write a program function using R to reshape the data in the way it is expected in Table 2 which is the desired layout. Explain briefly with your response.Table 1 Given input data 2.Given sample data below in table 1 has 4 columns including a date column in Col4. Provide an approach using separate function in R to convert the data to be reflected in desired layout as provided in Table 2. Explain briefly.Table1 Input data layout 3.Given below is sample input dataset and the code snippet. When we execute the code mentioned in Figure2 using the dataset in Figure1, is the desired output same as input data Explain with your response.Figure1 input dataset 4.When to use the following functions apply, lapply, sapply, tapply in R Explain. 5.Are the following code snippets same or different Explain why to support your response.flightsmutate1 flights mutatespeeddistanceairtime60 selectcarrier,arrdelay,speedflightsmutate2 flights selectcarrier,arrdelay,speed mutatespeeddistanceairtime60 6.We have a sample dataset related to pollution which can be described as below. How do we use R functions to come up with median and variance of that dataset. Secondly, what changes to the code snippet that you need to perform to add another information which will display the number of observations in the dataset. 7. What is the difference between n and ndistinct functions in R Explain with an example. 8. What is tidy data in R Explain with an example. Advanced 1.What is the difference between and 2. Which function is used to derive new variables using the dplyr package in R from existing variables Explain with an example. 3.What does kable perform in R Lets say if we use the airlines sample dataset and perform below operations in R console, do we expect any differences or are they same 4.Consider flights dataset in R. How can you find out how many flights go from a particular source to a particular destination The flights dataset looks like below. You can use in R console as it is a sample dataset available from any R console provided the packages are installed appropriately. 5.We have an untidy dataset as shown below. Provide your approach to make it tidy and a format that you would like to analyze using R 6.The sample dataset cases in R has the following data. Write a code or approach and explain to tidy the data in the desired format expected format shown belowDataset sampleExpected format of dataset 7.We have a sample dataset on tuberculosis tb from EDAWR package. What do you think about below two approaches written in code will they provide same or different results Explain why you feel either case.Code snippet 1EDAWRtb gatherage,cases,46 arrangecountry, year, sex, ageCode snippet 2EDAWRtb gatherage,cases,childelderly arrangecountry, year, sex, ageInformation on dataset 1.Given data related to specific parameter for a country for a particular year is mentioned in Table 1. Provide an approach or write a program function using R to reshape the data in the way it is expected in Table 2 which is the desired layout. Explain briefly with your response.Table 1 Given input dataCountry201120122013Japan230031006800China270033005400India480062009500Assume this data exists in your data frame in R as mydfTable 2 Expected desired layout as outputCountryYearnJapan20112300China20112700India20114800Japan20123100China20123300India20126200Japan20136800China20135400India20139500Here objective is to get the count n captured in a separate row for every year for every country. 2.Given sample data below in table 1 has 4 columns including a date column in Col4. Provide an approach using separate function in R to convert the data to be reflected in desired layout as provided in Table 2. Explain briefly.Table1 Input data layoutCol1Col2Col3Col4AA110100720020811BB45100919990812CC65100520020413DD40101320010814EE50101020020115FF45101020020716Assume this data exists in your data frame in R as mydfTable 2 Expected desired layout as outputCol1Col2Col3yearmonthdayAA110100720020811BB45100919990812CC65100520020413DD40101320010814EE50101020020115FF45101020020716 3.Given below is sample input dataset and the code snippet. When we execute the code mentioned in Figure2 using the dataset in Figure1, is the desired output same as input data Explain with your response.Figure1 input datasetCol1Col2Col3Col4AA110100720020811BB45100919990812CC65100520020413DD40101320010814EE50101020020115FF45101020020716Assume this data exists in your data frame in R as mydfFigure2 code snippetmydf separateCol4,cyear,month,day uniteCol4,month,day,year,sep 4.When to use the following functions apply, lapply, sapply, tapply in R Explain. 5.Are the following code snippets same or different Explain why to support your response.flightsmutate1 flights mutatespeeddistanceairtime60 selectcarrier,arrdelay,speedflightsmutate2 flights selectcarrier,arrdelay,speed mutatespeeddistanceairtime60 6.We have a sample dataset related to pollution which can be described as below. How do we use R functions to come up with median and variance of that dataset. Secondly, what changes to the code snippet that you need to perform to add another information which will display the number of observations in the dataset. 7.What is the difference between n and ndistinct functions in R Explain with an example. 8. What is tidy data in R Explain with an example. 1.What is the difference between and 2.Which function is used to derive new variables using the dplyr package in R from existing variables Explain with an example. 3.What does kable perform in R Lets say if we use the airlines sample dataset and perform below operations in R console, do we expect any differences or are they same 4.Consider flights dataset in R. How can you find out how many flights go from a particular source to a particular destination The flights dataset looks like below. You can use in R console as it is a sample dataset available from any R console provided the packages are installed appropriately. 5.We have an untidy dataset as shown below. Provide your approach to make it tidy and a format that you would like to analyze using RCountry201120122013FR700069007000DE580060006200US150001400013000P.S This above data has case count year wise for every country but represented in above untidy format. 6.The sample dataset cases in R has the following data. Write a code or approach and explain to tidy the data in the desired format expected format shown belowDataset sampleExpected format of dataset 7.We have a sample dataset on tuberculosis tb from EDAWR package. What do you think about below two approaches written in code will they provide same or different results Explain why you feel either case.Code snippet 1EDAWRtb gatherage,cases,46 arrangecountry, year, sex, ageCode snippet 2EDAWRtb gatherage,cases,childelderly arrangecountry, year, sex, ageInformation on dataset Description Related Interview Questions Useful links

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### eBook eBook Product Management Course Overview eBook eBook eBook Product Management Course Overview eBook Top 33 R Interview Questions Introduction Que 1 What is R Que 2 What are some of the advantages of R Que 3 What are some of the disadvantages of R programming Que 4 How are R commands written Que 5 Name the different objects or data types used in R. Que 6 What is the difference between R and Python in terms of functionality Que 7 How are missing and impossible values represented in R Que 8 What is the workspace in R Que 9 What is the memory limit in R Que 10 How do you import data in R Que 11 Name different types of sorting algorithms available in R. Que 12 What are R packages and how are they installed Que 13 Name some of the packages used for data imputation Que 14 Could you explain the difference between sample and subset in R. Que 15 How do you call a function in R Que 16 How do you assign a variable in R Que 17 What are some of your favorite functions in R Que 18 Explain the use of with and by function in R. Que 19 Which function do you use to add datasets in R Que 20 Why would one use a factor variable Que 21 Can you differentiate between matrix and data frames Que 22 Why is apply family of functions used in R Que 23 What do you mean by transpose Que 24 When do you use the next statement in R Que 25 What does a runif function do in R Que 26 What function is used for joining multiple strings together Que 27 What do you understand by ttests in R Que 28 How will you replace all the missing values of a vector v with the sum of elements of that vector Que 29 How do you list down the data sets available in all the packages Que 30 What function is used to create axes in the graph Que 31 What is the uses of shiny Rpackage Que 32 Why is doBY package used Que 33 How do you define correlation and how does one measure it in R Conclusion ALSO READ PEOPLE ALSO READ In the news

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35 R Programming Interview Questions and Answers To Help You Prepare What can you expect from an R programmer interview General questions Questions about experience and background Indepth questions Co...

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### 20 Common R Interview Questions Answers for 2019

20 Common R Interview Questions Answers for 2021 Prepare for a Career of the Future Leave a comment Cancel reply Post navigation Our Trending Data Science Courses Editors Picks Accelerate Your Career...

### 20 Common R Interview Questions Answers for 2021 Prepare for a Career of the Future Leave a comment Cancel reply Post navigation Our Trending Data Science Courses Editors Picks Accelerate Your Career with upGrad Our Popular Data Science Course Related Articles Introduction to Linear Search Algorithm Introduction FeaturesWith Examples 10 Best Paying Jobs in Technology in USA 2021 Python lambda Functions with Practical Examples Register for a Demo Course Register for a Demo Course Register for a Demo Course Talk to our Counselor to find a best course suitable to your Career Growth

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eBook eBook Product Management Course Overview eBook eBook eBook Product Management Course Overview eBook Top 33 R Interview Questions Introduction Que 1 What is R Que 2 What are some of the advanta...

### eBook eBook Product Management Course Overview eBook eBook eBook Product Management Course Overview eBook Top 33 R Interview Questions Introduction Que 1 What is R Que 2 What are some of the advantages of R Que 3 What are some of the disadvantages of R programming Que 4 How are R commands written Que 5 Name the different objects or data types used in R. Que 6 What is the difference between R and Python in terms of functionality Que 7 How are missing and impossible values represented in R Que 8 What is the workspace in R Que 9 What is the memory limit in R Que 10 How do you import data in R Que 11 Name different types of sorting algorithms available in R. Que 12 What are R packages and how are they installed Que 13 Name some of the packages used for data imputation Que 14 Could you explain the difference between sample and subset in R. Que 15 How do you call a function in R Que 16 How do you assign a variable in R Que 17 What are some of your favorite functions in R Que 18 Explain the use of with and by function in R. Que 19 Which function do you use to add datasets in R Que 20 Why would one use a factor variable Que 21 Can you differentiate between matrix and data frames Que 22 Why is apply family of functions used in R Que 23 What do you mean by transpose Que 24 When do you use the next statement in R Que 25 What does a runif function do in R Que 26 What function is used for joining multiple strings together Que 27 What do you understand by ttests in R Que 28 How will you replace all the missing values of a vector v with the sum of elements of that vector Que 29 How do you list down the data sets available in all the packages Que 30 What function is used to create axes in the graph Que 31 What is the uses of shiny Rpackage Que 32 Why is doBY package used Que 33 How do you define correlation and how does one measure it in R Conclusion ALSO READ PEOPLE ALSO READ In the news

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### Top 40 Data Science with R Interview Questions and Answers 2021

Interview Questions Data Science with R Interview Questions and Answers Data Science with R Interview Questions and Answers Top Categories Recent Post Trending Courses Master Program Related Blogs Onl...

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Top 100 R Interview Questions and Answers for 2021...

### Top 100 R Interview Questions and Answers for 2021

### https://www.upgrad.com/blog/r-interview-questions-answ...

### 20 Common R Interview Questions Answers for 2019

20 Common R Interview Questions Answers for 2021 Prepare for a Career of the Future Leave a comment Cancel reply Post navigation Our Trending Data Science Courses Editors Picks Accelerate Your Career...

### 20 Common R Interview Questions Answers for 2021 Prepare for a Career of the Future Leave a comment Cancel reply Post navigation Our Trending Data Science Courses Editors Picks Accelerate Your Career with upGrad Our Popular Data Science Course Related Articles Introduction to Linear Search Algorithm Introduction FeaturesWith Examples 10 Best Paying Jobs in Technology in USA 2021 Python lambda Functions with Practical Examples Register for a Demo Course Register for a Demo Course Register for a Demo Course Talk to our Counselor to find a best course suitable to your Career Growth

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### Top R Programming Interview Questions and Answers

What Are the Top AI Projects Google Is Working on These Days Best Artificial Intelligence Books to Read Data Engineer Interview Guide How AI and Automation Are Changing the Nature of Work Applications...

### What Are the Top AI Projects Google Is Working on These Days Best Artificial Intelligence Books to Read Data Engineer Interview Guide How AI and Automation Are Changing the Nature of Work Applications of Data Science, Deep Learning, and Artificial Intelligence Hadoop Technology Data Science vs. Big Data vs. Data Analytics Data Science vs. Data Analytics vs. Machine Learning Expert Talk Top 11 Artificial Intelligence Interview Questions to Prepare Data Analyst vs. Data Scientist Whats the Difference Top R Programming Interview Questions and Answers 10 R Programming Questions and Answers 1. Define R Programming. What Are Some of the R Functions That Exist 2. What Cant You Do with R Programming 3. In the R Programming Language, How Are Missing Values and Impossible Values Represented 4. How Do You Solve a Problem in R 5. What Objects Do You Use Most Often in R 6. Can You Write a Specific Code to Accomplish a Task 7. How Is R Similar to Python How Are the Two Different 8. What Are Some of the Pros and Cons of R 9. What Are Some of Your Favorite R Programming Functions 10. How Many Data Structures Are Available in R Programming Conclusion Find our Data Science with R Programming Online Classroom training classes in top cities About the Author Recommended Programs Top 30 C Programming Interview Question With Answers In 2021 Recommended Resources

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### Top R Programming Interview Questions Answers of 2021

R Programming Interview Questions Programming Beginner 1.Given data related to specific parameter for a country for a particular year is mentioned in Table 1. Provide an approach or write a program fu...

### R Programming Interview Questions Programming Beginner 1.Given data related to specific parameter for a country for a particular year is mentioned in Table 1. Provide an approach or write a program function using R to reshape the data in the way it is expected in Table 2 which is the desired layout. Explain briefly with your response.Table 1 Given input data 2.Given sample data below in table 1 has 4 columns including a date column in Col4. Provide an approach using separate function in R to convert the data to be reflected in desired layout as provided in Table 2. Explain briefly.Table1 Input data layout 3.Given below is sample input dataset and the code snippet. When we execute the code mentioned in Figure2 using the dataset in Figure1, is the desired output same as input data Explain with your response.Figure1 input dataset 4.When to use the following functions apply, lapply, sapply, tapply in R Explain. 5.Are the following code snippets same or different Explain why to support your response.flightsmutate1 flights mutatespeeddistanceairtime60 selectcarrier,arrdelay,speedflightsmutate2 flights selectcarrier,arrdelay,speed mutatespeeddistanceairtime60 6.We have a sample dataset related to pollution which can be described as below. How do we use R functions to come up with median and variance of that dataset. Secondly, what changes to the code snippet that you need to perform to add another information which will display the number of observations in the dataset. 7. What is the difference between n and ndistinct functions in R Explain with an example. 8. What is tidy data in R Explain with an example. Advanced 1.What is the difference between and 2. Which function is used to derive new variables using the dplyr package in R from existing variables Explain with an example. 3.What does kable perform in R Lets say if we use the airlines sample dataset and perform below operations in R console, do we expect any differences or are they same 4.Consider flights dataset in R. How can you find out how many flights go from a particular source to a particular destination The flights dataset looks like below. You can use in R console as it is a sample dataset available from any R console provided the packages are installed appropriately. 5.We have an untidy dataset as shown below. Provide your approach to make it tidy and a format that you would like to analyze using R 6.The sample dataset cases in R has the following data. Write a code or approach and explain to tidy the data in the desired format expected format shown belowDataset sampleExpected format of dataset 7.We have a sample dataset on tuberculosis tb from EDAWR package. What do you think about below two approaches written in code will they provide same or different results Explain why you feel either case.Code snippet 1EDAWRtb gatherage,cases,46 arrangecountry, year, sex, ageCode snippet 2EDAWRtb gatherage,cases,childelderly arrangecountry, year, sex, ageInformation on dataset 1.Given data related to specific parameter for a country for a particular year is mentioned in Table 1. Provide an approach or write a program function using R to reshape the data in the way it is expected in Table 2 which is the desired layout. Explain briefly with your response.Table 1 Given input dataCountry201120122013Japan230031006800China270033005400India480062009500Assume this data exists in your data frame in R as mydfTable 2 Expected desired layout as outputCountryYearnJapan20112300China20112700India20114800Japan20123100China20123300India20126200Japan20136800China20135400India20139500Here objective is to get the count n captured in a separate row for every year for every country. 2.Given sample data below in table 1 has 4 columns including a date column in Col4. Provide an approach using separate function in R to convert the data to be reflected in desired layout as provided in Table 2. Explain briefly.Table1 Input data layoutCol1Col2Col3Col4AA110100720020811BB45100919990812CC65100520020413DD40101320010814EE50101020020115FF45101020020716Assume this data exists in your data frame in R as mydfTable 2 Expected desired layout as outputCol1Col2Col3yearmonthdayAA110100720020811BB45100919990812CC65100520020413DD40101320010814EE50101020020115FF45101020020716 3.Given below is sample input dataset and the code snippet. When we execute the code mentioned in Figure2 using the dataset in Figure1, is the desired output same as input data Explain with your response.Figure1 input datasetCol1Col2Col3Col4AA110100720020811BB45100919990812CC65100520020413DD40101320010814EE50101020020115FF45101020020716Assume this data exists in your data frame in R as mydfFigure2 code snippetmydf separateCol4,cyear,month,day uniteCol4,month,day,year,sep 4.When to use the following functions apply, lapply, sapply, tapply in R Explain. 5.Are the following code snippets same or different Explain why to support your response.flightsmutate1 flights mutatespeeddistanceairtime60 selectcarrier,arrdelay,speedflightsmutate2 flights selectcarrier,arrdelay,speed mutatespeeddistanceairtime60 6.We have a sample dataset related to pollution which can be described as below. How do we use R functions to come up with median and variance of that dataset. Secondly, what changes to the code snippet that you need to perform to add another information which will display the number of observations in the dataset. 7.What is the difference between n and ndistinct functions in R Explain with an example. 8. What is tidy data in R Explain with an example. 1.What is the difference between and 2.Which function is used to derive new variables using the dplyr package in R from existing variables Explain with an example. 3.What does kable perform in R Lets say if we use the airlines sample dataset and perform below operations in R console, do we expect any differences or are they same 4.Consider flights dataset in R. How can you find out how many flights go from a particular source to a particular destination The flights dataset looks like below. You can use in R console as it is a sample dataset available from any R console provided the packages are installed appropriately. 5.We have an untidy dataset as shown below. Provide your approach to make it tidy and a format that you would like to analyze using RCountry201120122013FR700069007000DE580060006200US150001400013000P.S This above data has case count year wise for every country but represented in above untidy format. 6.The sample dataset cases in R has the following data. Write a code or approach and explain to tidy the data in the desired format expected format shown belowDataset sampleExpected format of dataset 7.We have a sample dataset on tuberculosis tb from EDAWR package. What do you think about below two approaches written in code will they provide same or different results Explain why you feel either case.Code snippet 1EDAWRtb gatherage,cases,46 arrangecountry, year, sex, ageCode snippet 2EDAWRtb gatherage,cases,childelderly arrangecountry, year, sex, ageInformation on dataset Description Related Interview Questions Useful links

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### Top 40 Data Science with R Interview Questions and Answers 2021

Interview Questions Data Science with R Interview Questions and Answers Data Science with R Interview Questions and Answers Top Categories Recent Post Trending Courses Master Program Related Blogs Onl...

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What Are the Top AI Projects Google Is Working on These Days Best Artificial Intelligence Books to Read Data Engineer Interview Guide How AI and Automation Are Changing the Nature of Work Applications...

### What Are the Top AI Projects Google Is Working on These Days Best Artificial Intelligence Books to Read Data Engineer Interview Guide How AI and Automation Are Changing the Nature of Work Applications of Data Science, Deep Learning, and Artificial Intelligence Hadoop Technology Data Science vs. Big Data vs. Data Analytics Data Science vs. Data Analytics vs. Machine Learning Expert Talk Top 11 Artificial Intelligence Interview Questions to Prepare Data Analyst vs. Data Scientist Whats the Difference Top R Programming Interview Questions and Answers 10 R Programming Questions and Answers 1. Define R Programming. What Are Some of the R Functions That Exist 2. What Cant You Do with R Programming 3. In the R Programming Language, How Are Missing Values and Impossible Values Represented 4. How Do You Solve a Problem in R 5. What Objects Do You Use Most Often in R 6. Can You Write a Specific Code to Accomplish a Task 7. How Is R Similar to Python How Are the Two Different 8. What Are Some of the Pros and Cons of R 9. What Are Some of Your Favorite R Programming Functions 10. How Many Data Structures Are Available in R Programming Conclusion Find our Data Science with R Programming Online Classroom training classes in top cities About the Author Recommended Programs Top 30 C Programming Interview Question With Answers In 2021 Recommended Resources

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35 R Programming Interview Questions and Answers To Help You Prepare What can you expect from an R programmer interview General questions Questions about experience and background Indepth questions Co...

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Data Science with R Programming Training in Atlanta Worlds 1 Online Bootcamp Data Science with R Course Overview R Certification Training Key Features Skills Covered Benefits Training Options SelfPace...

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R Interview Questions R Interview Questions for Beginners Q1 Describe the R environment Features Q2 Who and what are the uses of the R software environment Q3 What are the statistical features of R Q4...