1. #Question 1
2. # a.    Write a SAS program to create a temporary SAS data set called Vote.
3. # Use the variable name State, Party and Age. Age should be stored as a numeric variable,
4. # State and Party should be stored as character variables.
5. # b.    Include a procedure to list the observations in this data set.
6. # c.    Include a procedure to compute frequencies for Party.
7. # d.    Repeat problem above (a to c) using R programming
8. library(readr) #to read csv file
9. setwd("D:/Rstudio Project")
10. Vote2 <- read.csv(file = 'D:/Rstudio Project/Sas Week 12/political.csv', header =FALSE , sep=',')
11. colnames(Vote2) <- c("State" , "Party", "Age") #change column names
12. View(Vote2) #list all observation
13. print(Vote2) #list all observation
14.  
15. #calculate frequency
16. #Method 1
17. table(Vote2$Party)
18. #Method 2
19. p <- as.data.frame(table(Vote2$Party))
20. names(p)[1] = "Party"
21. View(p)
22.  
23. summary(p$Party) #View summary
24.  
25.  
26.  
27. # Question 2
28. # Using the Bicycle data set (SAS native dataset), list all the
29. # observations for Road Bike that cost more than $2,500 or Hybrid
30. # that cost more than $660. The variable Model contains the type of bike
31. # and UnitCost contains the cost.
32.  
33. #teachers way, using sa7bdat library
34. library(sas7bdat)
35. bicycles2 <- read.sas7bdat(file = 'D:/Rstudio Project/Sas Week 12/bicycles.sas7bdat')
36. outpl <- subset(bicycles2, (Model=='Road Bike' & UnitCost > 2500 | Model=='Hybrid' & UnitCost > 660), select=Country:Manuf)
37. print(outpl)
38.  
39. #own way
40. bicycles <- read_sas("bicycles.sas7bdat", + NULL)
41. View(bicycles)
42. library(sqldf)
43. sqldf("select * from bicycles where Model = 'Road Bike' and UnitCost > 2500 or Model = 'Hybrid' and Unitcost >660") #get the result using sql
44.  
45. RoadBike <- bicycles[bicycles$UnitCost > 2500 & bicycles$Model == "Road Bike" ,] #get the result for roadbike
46. Hybrid <- bicycles[bicycles$UnitCost > 660 & bicycles$Model == "Hybrid" ,] #get the result for roadbike
47. Mergedbike <- merge(Hybrid,RoadBike, all = TRUE) #merge both datsets together
48. View(Mergedbike)
49.  
50. #Question 3
51. # Create a temporary SAS data set called Bank using this data file. Use using formatted
52. # input to read the data values. Include in this data set a variable called Interest
53. # computed by multiplying Balance by Rate. List the contents of this data set using
54. # PROC PRINT.
55. library(readr)
56. library(tidyr)
57. bankdata <- read_table2("bankdata.txt", col_names = FALSE)                      
58. View(bankdata)
59. bankdata <- unite(bankdata, Name, X1, X2, sep = " ")
60. bankdata$Rate <- 0
61. colnames(bankdata) <- c("Name" , "Acct", "Balance", "Rate")
62. View(bankdata)
63. bankdata$Interest <- bankdata$Balance * bankdata$Rate
64. View(bankdata)
65.  
66. #teachers solution
67. bankR <- read.fwf('D:/Rstudio Project/Sas Week 12/bankdata.txt', width=c(15,5,6,4), col.names = c("Name" , "Acct", "Balance", "Rate"))
68. bankR$interest = bankR$balance = bankR$rate
69. print(bankR)
70.