Assignment 2 Data Science Tools and Methods

'Name: Erin Dane
Course: MSCI3230'

## [1] "Name: Erin Dane\nCourse: MSCI3230"

#Question 1
Housing <- read.csv("~/Desktop/R Studios /Table2.1HousePrices-NoID.csv")
SQFT <- Housing$SqFt
BNB <- Housing$Brick
function1 <- function(x,y) {
  z <- which(SQFT >= x & BNB == y)
  w <- mean(Housing$Price[z])
  print(paste('The average price of the home is',w))
}
function1(2000,"Yes")

## [1] "The average price of the home is 157986.956521739"

#Question 2
Housing <- read.csv("~/Desktop/R Studios /Table2.1HousePrices-NoID.csv")
SQFT <- Housing$SqFt
BNB <- Housing$Brick
NBH <- Housing$Neighborhood
function2 <- function(x,y,q) {
  z <- which(SQFT >= x & BNB == y & NBH == q)
  w <- mean(Housing$Price[z])
  print(paste('The average price of the home is',w))
}
function2(2000,"Yes","West")

## [1] "The average price of the home is 182620"

#Question 3
Housing <- read.csv("~/Desktop/R Studios /Table2.1HousePrices-NoID.csv")
hist(Housing$Price,
     main="Histogram of House Prices", 
     xlab="House Prices", 
     col="purple",
     las=1,
     breaks=20,)

#Question 4
Housing <- read.csv("~/Desktop/R Studios /Table2.1HousePrices-NoID.csv")
BEDR <- Housing$Bedrooms
PRICE <- Housing$Price
function3 <- function(x) {
  w <- x:x
  for (i in w) {
    z <- which(BEDR == x)
    print(mean(PRICE[z]))
  }
}
function3(2)

## [1] 115260

#Question 5
Housing <- read.csv("~/Desktop/R Studios /Table2.1HousePrices-NoID.csv")
BEDR <- Housing$Bedrooms
PRICE <- Housing$Price
COUNT <- 0
function3 <- function(x) {
  while (x > COUNT) {
      z <- which(BEDR == x)
      w <- mean(PRICE[z])
      print(paste('The average price of the home is',w))
      COUNT <- COUNT + x
  }
}
  
function3(3)

## [1] "The average price of the home is 125732.835820896"