classht=c(177,169,175,165,171)
sum(classht)
## [1] 857
length(classht)
## [1] 5
classht[1]
## [1] 177
classht[5]
## [1] 171
sum(classht)/length(classht)
## [1] 171.4
mean(classht)
## [1] 171.4
sort(classht)
## [1] 165 169 171 175 177
sort(classht)[1]
## [1] 165
sort(classht)[0.5+length(classht)/2]
## [1] 171
median(classht)
## [1] 171
ajayfun=function(x,y){
x*2+y^3
}
ajayfun(3,5)
## [1] 131
for (i in 1:10){print(ajayfun(3,i))}
## [1] 7
## [1] 14
## [1] 33
## [1] 70
## [1] 131
## [1] 222
## [1] 349
## [1] 518
## [1] 735
## [1] 1006
ajayobj=NULL
for (i in 1:10){ajayobj[i]=ajayfun(3,i)}
ajayobj
## [1] 7 14 33 70 131 222 349 518 735 1006
33%%2
## [1] 1
32%%2
## [1] 0
ajayfun2=function(x){
ifelse(x%%2==0,"EVEN","ODD")
}
ajayfun2(45)
## [1] "ODD"
ajayfun2(32)
## [1] "EVEN"
for(i in 1:20){print(ajayfun2(i))}
## [1] "ODD"
## [1] "EVEN"
## [1] "ODD"
## [1] "EVEN"
## [1] "ODD"
## [1] "EVEN"
## [1] "ODD"
## [1] "EVEN"
## [1] "ODD"
## [1] "EVEN"
## [1] "ODD"
## [1] "EVEN"
## [1] "ODD"
## [1] "EVEN"
## [1] "ODD"
## [1] "EVEN"
## [1] "ODD"
## [1] "EVEN"
## [1] "ODD"
## [1] "EVEN"
newmedian=function(x){
ifelse(length(x)%%2==1,
sort(x)[0.5+length(x)/2],
0.5*(sort(x)[length(x)/2]+sort(x)[1+length(x)/2])
)}
ajay1=c(23,56,78,45)
newmedian(ajay1)
## [1] 50.5
median(ajay1)
## [1] 50.5
ajay2=c(31,33,35,37,39)
newmedian(ajay2)
## [1] 35
median(ajay2)
## [1] 35
plot(ajay1)
plot(sort(ajay1))
#Q
#CREATE A FUNCTION THAT TAKES IN TWO INPUTS
# AND RETURNS THE SUM OF THEIR CUBES
#APPLY THE FUNCTION TO 1000 numbers
#AND STORE THEM in an object
#A
myfun=function(a,b)#inputs are two
{
a^3+b^3 #function
}
myfun(2,3) #testing function
## [1] 35
newobj=NULL #creating null object
newobj=data.frame(newobj) #changing it to data frame
#Example of Nested Loop
for(i in 1:10){
for (j in 1:10)
{
newobj[i,j]=myfun(i,j)
}
}
newobj
## V1 V2 V3 V4 V5 V6 V7 V8 V9 V10
## 1 2 9 28 65 126 217 344 513 730 1001
## 2 9 16 35 72 133 224 351 520 737 1008
## 3 28 35 54 91 152 243 370 539 756 1027
## 4 65 72 91 128 189 280 407 576 793 1064
## 5 126 133 152 189 250 341 468 637 854 1125
## 6 217 224 243 280 341 432 559 728 945 1216
## 7 344 351 370 407 468 559 686 855 1072 1343
## 8 513 520 539 576 637 728 855 1024 1241 1512
## 9 730 737 756 793 854 945 1072 1241 1458 1729
## 10 1001 1008 1027 1064 1125 1216 1343 1512 1729 2000
newobj
## V1 V2 V3 V4 V5 V6 V7 V8 V9 V10
## 1 2 9 28 65 126 217 344 513 730 1001
## 2 9 16 35 72 133 224 351 520 737 1008
## 3 28 35 54 91 152 243 370 539 756 1027
## 4 65 72 91 128 189 280 407 576 793 1064
## 5 126 133 152 189 250 341 468 637 854 1125
## 6 217 224 243 280 341 432 559 728 945 1216
## 7 344 351 370 407 468 559 686 855 1072 1343
## 8 513 520 539 576 637 728 855 1024 1241 1512
## 9 730 737 756 793 854 945 1072 1241 1458 1729
## 10 1001 1008 1027 1064 1125 1216 1343 1512 1729 2000
mean(newobj$V1)
## [1] 303.5
mean(newobj$V2)
## [1] 310.5
newobj2=as.list(newobj)
newobj2=unlist(newobj)
newobj2
## V11 V12 V13 V14 V15 V16 V17 V18 V19 V110 V21 V22
## 2 9 28 65 126 217 344 513 730 1001 9 16
## V23 V24 V25 V26 V27 V28 V29 V210 V31 V32 V33 V34
## 35 72 133 224 351 520 737 1008 28 35 54 91
## V35 V36 V37 V38 V39 V310 V41 V42 V43 V44 V45 V46
## 152 243 370 539 756 1027 65 72 91 128 189 280
## V47 V48 V49 V410 V51 V52 V53 V54 V55 V56 V57 V58
## 407 576 793 1064 126 133 152 189 250 341 468 637
## V59 V510 V61 V62 V63 V64 V65 V66 V67 V68 V69 V610
## 854 1125 217 224 243 280 341 432 559 728 945 1216
## V71 V72 V73 V74 V75 V76 V77 V78 V79 V710 V81 V82
## 344 351 370 407 468 559 686 855 1072 1343 513 520
## V83 V84 V85 V86 V87 V88 V89 V810 V91 V92 V93 V94
## 539 576 637 728 855 1024 1241 1512 730 737 756 793
## V95 V96 V97 V98 V99 V910 V101 V102 V103 V104 V105 V106
## 854 945 1072 1241 1458 1729 1001 1008 1027 1064 1125 1216
## V107 V108 V109 V1010
## 1343 1512 1729 2000
mean(newobj2)
## [1] 605
sd(newobj2)
## [1] 463.4832