R Interview Questions


  1. Data Frames
    1. How to “merge” data frames in R
    2. How do you search/replace text in a data frame
    3. How can you add columns to a data frame in R
    4. How can you add rows to a data frame in R
    5. How to delete columns from a data frame in R
    6. How to delete rows from a data frame in R
    7. How to remove all rows in a data frame with NAs in R
    8. How to remove particular values from a data frame in R
    9. How to remove duplicate rows from a data frame in R
  2. Vectors
    1. Vector Recycling in R
    2. How to find out elements in one vector that are not in another vector
  3. Graphics ( EDA )
    1. How to create a pie chart in R
    2. How to create a histogram in R
    3. How to create a box plot in R
    4. Why are box plots used
    5. How to view scatter plots for more than 2 variables in R
    6. How to add grids to plots in R
    7. How to make interactive plots in R
    8. How to visualize multi-dimensional data in R
  4. Data Manipulation
    1. what is ‘Stack’ing and ‘Unstack’ing in R
    2. What is the difference between sapply vs lapply functions
    3. What is the difference between apply vs for loop
  5. Subset data
    1. How to subset a Dataframe
    2. How to subset a Vector
    3. How to subset a List
    4. How to subset a Matrix
  6. Data Structures
    1. What are the basic data structures in R
    2. What is the difference between dataframe and matrix
    3. How to find out the unique elements in a vector
    4. What is the difference between data frame and data table
    5. What is the difference between a dataframe and a list
  7. Commonly used Statistics functions
    1. How is skewness of a distribution calculated in R
    2. How is kurtosis of a distribution calculated in R
    3. How do you calculate mean, median, MAD and SD in R
    4. How to get correlation matrix (or coefficients) for a set of variables in R
    5. How to generate the same set of random numbers in R
    6. What is the difference between runif () and rnorm () functions in R
    7. How to get samples from a data set
    8. What is confusion matrix
  8. Packages
    1. How to install a package in R
    2. What is the difference between ilbrary() and require() functions in R
    3. What are the R packages you used most in your previous projects
    4. How to search for packages in R that suit your requirements
  9. Data Loading
    1. What are the most used data import functions in R
    2. What are the most commonly found issues with data import
    3. How to read JSON files
    4. How to load HTML table into R
  10. Data Cleansing
    1. How did you eliminate outliers in R
    2. Why is which () function used
    3. How to convert a factor variable to a numeric variable
    4. What strategies did you use to eliminate NAs
  11. Modularization
    1. How to split your program across multiple files in R
    2. How to write a function in R
  12. Functions
    1. What is the use of … ( ellipsis ) in functions in R
    2. How to write recursive functions in R
    3. How to specify default values in function parameters in R
    4. How to see the source code of a function in R
  13. Version Management
    1. What kind of version management did you use in your previous projects
  14. ML – Regression
    1. How to do Linear Regression in R
    2. How to do multi linear regression in R
    3. How do you specify the formula for a logarithmic regression in R
    4. How to you specify powers in polynomial regression formula
    5. How did you split the data into training and test data
    6. What plots in R did you produce to communicate your linear regression test results
    7. What packages did you use in R to find out significant variables in multi linear regression
  15. ML – Classification
    1. What packages did you use for KNN classification in R
    2. How to do confusion matrix in R

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