############  UE 2  ############
library(tidyverse)
install.packages("tidyverse")
##1.)
#a)
float<-3.0
newfloat<-float
float<-1.0
float
newfloat

#newfloat still has its original value
#b)
string<-"hello"
newString<-string
string<-"world"
newString
string
#same as for a
#e)
list1<-list(1:3)
list2<-list1
list1<-list(1:4)
list2
list1
#R uses pass-by-value semantics

##2.)
#a)
keys<-list("a","a","a","a","a","a","a")
seq<-c(1:length(keys))
names(seq)=keys

#b)
seq<-replace(seq,,NA) #compiler warning can be ignored :^)
seq

#c)
seq[1]="Cool"
seq[2]="Stuff"
replace(seq,1,"Boring")


#d)
seq[which(!is.na(seq))] # to get the index and the name

#e)
givenKey<-"Cool"
givenKey %in% seq

#f)
#1. Dictionaries in python musst always have a key value pair.
#In R the key can be NA
#2. In dictionaries the key must always be unique
#3.


##4.)
#a)
number<-floor(runif(1,1,10))
number
#b)
print("make your guess")
#c)
guess<-readline("Enter your number: ")
guess
#d)
guess<-as.integer(guess)
if(is.na(guess)){
  print("Wrong type. Please provide a number")
}  else {
  paste0("My number: ",number,". My guess: ",guess)
  if(guess==number) {
    print("You won. Gz")
  }else{
    print("loser.")
  }
}

##5.)
myFunc<- function(withNA=TRUE,...){

  args<-list(...)
  numberInput<-sapply(args,simplify2array)
#a)
  paste("Number of arguments: ", length(args))
  #b)
  paste("Min: ",min(numberInput,na.rm = withNA)," Max: ",max(numberInput,na.rm = withNA))
  #c)
  paste("Sum of arugments:", sum(numberInput,na.rm = withNA))
  #d)
  paste("Mean of arguemnts: ", mean(numberInput,na.rm = withNA))
}


myFunc(withNA=TRUE,1,2,3,4,5)

##7.)
target_temp_1 <- c(21.9485903842751, 22.0784102698089, 21.9961920387344, 22.0888801363402,
                   21.7593642619783, 22.0733746321091, 20.0650945334316, 22.2239271878111,
                   22.0009439997692, 21.9857914565644)
target_temp_2 <- c(-4.86905373694365, -4.80753142788851, -5.01604866437737, -5.04518643042135,
                   -4.7522254125673, -5.14586954359958, -6.94227853304683, -5.00661640454364,
                   -4.99321895338312, -5.32219568456159)
target_temp_3 <- c(9.96164369257947, 10.2791653162905, 10.0121926692844, 10.0902680418902,
                   10.082372143524, 10.2616048271993, 7.97374718604113, 9.70072495469742,
                   9.99002115411479, 9.72302091276975)
target_temp_4 <- c(39.1663079568986, 39.1015313287077, 39.0140282858949, 38.9695153382043,
                   39.1154016526277, 38.997730939927, 37.0125229951796, 38.8548037473053,
                   38.9950516925261, 38.9622025227075)

#a)
temp1<-mean(target_temp_1)
temp1

temp2<-mean(target_temp_2)
temp2
temp3<-mean(target_temp_3)
temp3
temp4<-mean(target_temp_4)
temp4
#b)

absoluteDeviation<-function(x){
  return(x-temp1)
}


lapply(target_temp_1,absoluteDeviation)