R Programming Questions With Their Solutions

CONTENT

  1. WAP to create a vector and perform task on that in R:
    1. Combine numerical values, numerical values in a sequence.
    2. Length of vector, sort a vector, access a particular index value in the vector.
  2. WAP to create a list and perform following task on that in R:
    1. Access lists, change item value, list length, check if item exists.
    2. Add list items, remove list items.
    3. Range of indexes, loop through a list, join two lists.
  3. WAP to create a 4X4 matrix and perform following task on that in R:
    1. Access matrix items, access more than one row and for access more than one column.
    2. Add rows and columns, remove rows and columns.
    3. Check if an item exists, amount of rows and columns, matrix length.
    4. Loop through a matrix, combine two matrices.
  4. WAP to create an array and perform following task on that in R:
    1. Access array items, check if an item exists.
    2. Amount of rows and columns, array length, loop through an array.
  5. WAP to create a data frame and perform following task on that in R:
    1. Summarize the data, access items, add rows, add columns.
    2. Remove rows and columns, amount of rows and columns.
    3. Data frame length, combining data frames.
  6. WAP to calculate the summary of any dataset in R.
  7. WAP to create factors and perform all possible tasks on factors in R.
  8. WAP to calculate statistical measures (mean, median, min and max) in R.
  9. WAP to import a data set from the internet directly or through a file in R.
  10. WAP to find the outliers in R.
  11. WAP to implement data visualization using Histogram and Box plot in R.
  12. WAP to implement the data manipulation with dplyr package in R.
  13. WAP to implement the data visualization with ggplot2.
  14. WAP to develop an application to perform classification using a decision tree in R.
  15. WAP to perform classification using KNN in R.
  16. WAP to perform clustering using K-means in R.
  17. WAP to fill missing values in a dataset using mean in R.
  18. WAP to extract association rules using Apriori Algorithm in R.
  19. WAP to develop an application to design star schemas from fact tables in R.

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8.A: Write a program to create a vector and combines numerical values, numerical values in a sequence.
Will be written soon...

8.B: Write a program to create a vector and find length of vector, sort a vector, access a perticular index value in vector.
Will be written soon...

9.A: Write a program to create a list and access lists, change item value, list length, check if item exists.

9.B: Write a program to create a list and add list items, remove list items.

9.C: Write a program to create a list and range of indexes, loop through a list, join two lists.

10.A: Write a program to create a 4X4 matrix and access matrix items, access more than one row and for access more than one column.
Will be Written soon..

10.B: Write a program to create a 4X4 matrix and add rows and columns, remove rows and columns.
Will be written soon...

10.C: Write a program to create a 4X4 matrix and check if an item exists, amount of rows and columns, matrix length.

10.D: Write a program to create a 4X4 matrix and loop through a matrix, combine two matrices.

11.A: Write a program to create an array and access array items, check if an item exists.

11.B: Write a program to create an array and amount of rows and columns, array length, loop through an array.

12.A: Write a program to create a data frame and summarize the data, access items, add rows, add columns.

12.B: Write a program to create a data frame and remove rows and columns, amount of rows and columns.

12.C: Write a program to create a data frame and data frame length, combining data frames.

13. Write a program to calculate the summary of any dataset.

14. Write a program to create factors and perform all possible tasks on factors.

15. WAP to calculate statistical measures (mean, median, min and max) in R.

16. WAP to import a data set from the internet directly or through a file in R.

17. WAP to find the outliers in R.

18. WAP to implement data visualization using Histogram and Box plot in R.

19. WAP to implement the data manipulation with dplyr package in R.

20. WAP to implement the data visualization with ggplot2.

21. WAP to develop an application to perform classification using a decision tree in R.

22. WAP to perform classification using KNN in R.

23. WAP to perform clustering using K-means in R.

24. WAP to fill missing values in a dataset using mean in R.

25. WAP to extract association rules using Apriori Algorithm in R.

26. WAP to develop an application to design star schemas from fact tables in R.

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