#Question 1
# a.	Write a SAS program to create a temporary SAS data set called Vote. 
# Use the variable name State, Party and Age. Age should be stored as a numeric variable, 
# State and Party should be stored as character variables. 
# b.	Include a procedure to list the observations in this data set.
# c.	Include a procedure to compute frequencies for Party.
# d.	Repeat problem above (a to c) using R programming
library(readr) #to read csv file
setwd("D:/Rstudio Project")
Vote2 <- read.csv(file = 'D:/Rstudio Project/Sas Week 12/political.csv', header =FALSE , sep=',')
colnames(Vote2) <- c("State" , "Party", "Age") #change column names
View(Vote2) #list all observation
print(Vote2) #list all observation

#calculate frequency
#Method 1
table(Vote2$Party)
#Method 2
p <- as.data.frame(table(Vote2$Party))
names(p)[1] = "Party"
View(p)

summary(p$Party) #View summary



# Question 2
# Using the Bicycle data set (SAS native dataset), list all the 
# observations for Road Bike that cost more than $2,500 or Hybrid 
# that cost more than $660. The variable Model contains the type of bike 
# and UnitCost contains the cost.

#teachers way, using sa7bdat library
library(sas7bdat)
bicycles2 <- read.sas7bdat(file = 'D:/Rstudio Project/Sas Week 12/bicycles.sas7bdat')
outpl <- subset(bicycles2, (Model=='Road Bike' & UnitCost > 2500 | Model=='Hybrid' & UnitCost > 660), select=Country:Manuf)
print(outpl)

#own way
bicycles <- read_sas("bicycles.sas7bdat", + NULL)
View(bicycles)
library(sqldf)
sqldf("select * from bicycles where Model = 'Road Bike' and UnitCost > 2500 or Model = 'Hybrid' and Unitcost >660") #get the result using sql

RoadBike <- bicycles[bicycles$UnitCost > 2500 & bicycles$Model == "Road Bike" ,] #get the result for roadbike
Hybrid <- bicycles[bicycles$UnitCost > 660 & bicycles$Model == "Hybrid" ,] #get the result for roadbike
Mergedbike <- merge(Hybrid,RoadBike, all = TRUE) #merge both datsets together
View(Mergedbike)

#Question 3
# Create a temporary SAS data set called Bank using this data file. Use using formatted 
# input to read the data values. Include in this data set a variable called Interest 
# computed by multiplying Balance by Rate. List the contents of this data set using 
# PROC PRINT.
library(readr)
library(tidyr)
bankdata <- read_table2("bankdata.txt", col_names = FALSE)                      
View(bankdata)
bankdata <- unite(bankdata, Name, X1, X2, sep = " ")
bankdata$Rate <- 0
colnames(bankdata) <- c("Name" , "Acct", "Balance", "Rate")
View(bankdata)
bankdata$Interest <- bankdata$Balance * bankdata$Rate
View(bankdata)

#teachers solution
bankR <- read.fwf('D:/Rstudio Project/Sas Week 12/bankdata.txt', width=c(15,5,6,4), col.names = c("Name" , "Acct", "Balance", "Rate"))
bankR$interest = bankR$balance = bankR$rate
print(bankR)