############################ R CODE FOR POWERBI + R WORSKHOP ##############################

############### EXERCISE 1 - OPTION 1

#Following workshop examples will use this dataset

data() #show a list of available datasets
mydataframe <- trees #copy the tree dataset to mydataframe

mytreetype <- sample (c("A","B","C"),nrow(trees),replace=TRUE)
mytreelocation <- sample(c("mountain","meadow"),nrow(trees),replace=TRUE)
mytreeID <- c(1:nrow(trees))

mydataframe$type <- mytreetype
mydataframe$location <- mytreelocation
mydataframe$ID <- mytreeID

############## EXERCISE 1 - OPTION 2

getwd()#tells you what your path currently is

#you will need to determine the correct path for your data location.
path <- "C:/Users/User/Desktop/PowerBI_demo_files/CityTables" #NOTE:forward slashes
setwd(path)

filename <- "myfilename.csv"
mydataframe <-  read.csv(filename) #read in file as a dataframe
head(mydataframe) #print the first few lines of the dataframe



############### EXERCISE 1 - OPTION 3

getwd() #to make sure at least one command is working

customer <- c("Jen","Steve","Deepthi","Gilles")
purchaseamount <- c(3100, 3340, 5800,45)
purchasetype <- c("fun","practical","fun","both")
purchasedate <- as.Date(c('2010-11-1','2008-3-25','2007-3-14','2012-01-01'))
customer_data <- data.frame(customer, purchaseamount, purchasedate,purchasetype)
customer_data$purchasetype <- as.character(customer_data$purchasetype)
mydataframe <- customer_data

############### EXERCISE 3 - PART 1

#this code assumes you have loaded the modified trees dataset
#from Exercise 1 Option 1 into the dataset variable
#if you are using a different dataset, you will need to change variable names

plot(dataset$Girth)#single variable simple visualization

#try with both a categorical variable and numeric variable if your dataset has a categorical variable

############### EXERCISE 3 - PART 2

#this code assumes you have loaded the modified trees dataset
#from Exercise 1 Option 1 into the dataset variable
#if you are using a different dataset, you will need to change variable names

plot(dataset$Girth, dataset$Height)#two variable simple visualization

#try with a categorical variable and numeric variable if your dataset has these variables

############### EXERCISE 5 - PART 1

dataset$season <- sample(c("summer","winter"),nrow(trees),replace=TRUE)
output <- dataset #if you don't have this, you will overwrite the data with an empty dataset

############### EXERCISE 5 - PART 2

#This is going to replace your existing data with new data
customer <- c("Jen","Steve","Deepthi","Gilles")
purchaseamount <- c(3100, 3340, 5800,45)
purchasetype <- c("fun","practical","fun","both")
purchasedate <- as.Date(c('2010-11-1','2008-3-25','2007-3-14','2012-01-01'))
output <- data.frame(customer, purchaseamount, purchasedate,purchasetype)

############### WIDE SAMPLE DATA

customer <- c("Jen","Steve","Deepthi","Gilles")
purchasedate <- as.Date(c('2010-11-1','2008-3-25','2007-3-14','2012-01-01'))
purchaseamount.fun <- c(3100,567,5800,1234)
purchaseamount.practical <-c(4800,3340,2800,1000)
purchaseamount.both <- c(72,18,67,45)
wide_customer_data <- data.frame(customer, purchasedate, purchaseamount.fun,purchaseamount.practical,purchaseamount.both)