empid = c(1,2,3,4,5,6,7,8,9,10,11,12,13,14,15)
empid
## [1] 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15
age = c(30,37,45,32,50,60,35,32,34,43,32,30,43,50,60)
age
## [1] 30 37 45 32 50 60 35 32 34 43 32 30 43 50 60
gender = c(0,1,0,1,1,1,0,0,1,0,0,1,1,0,0)
gender
## [1] 0 1 0 1 1 1 0 0 1 0 0 1 1 0 0
status = c(1,1,2,2,1,1,1,2,2,1,2,1,2,1,2)
status
## [1] 1 1 2 2 1 1 1 2 2 1 2 1 2 1 2
empinfo <- data.frame(empid,age,gender,status)
empinfo
## empid age gender status
## 1 1 30 0 1
## 2 2 37 1 1
## 3 3 45 0 2
## 4 4 32 1 2
## 5 5 50 1 1
## 6 6 60 1 1
## 7 7 35 0 1
## 8 8 32 0 2
## 9 9 34 1 2
## 10 10 43 0 1
## 11 11 32 0 2
## 12 12 30 1 1
## 13 13 43 1 2
## 14 14 50 0 1
## 15 15 60 0 2
empinfo$gender = factor(empinfo$gender, labels = c("male","female"))
empinfo$gender
## [1] male female male female female female male male female male
## [11] male female female male male
## Levels: male female
empinfo$status = factor(empinfo$status, labels = c("staff","faculty"))
empinfo$status
## [1] staff staff faculty faculty staff staff staff faculty faculty
## [10] staff faculty staff faculty staff faculty
## Levels: staff faculty
male = subset(empinfo,gender == "male")
female = subset(empinfo,gender == "female")
summary(empinfo)
## empid age gender status
## Min. : 1.0 Min. :30.00 male :8 staff :8
## 1st Qu.: 4.5 1st Qu.:32.00 female:7 faculty:7
## Median : 8.0 Median :37.00
## Mean : 8.0 Mean :40.87
## 3rd Qu.:11.5 3rd Qu.:47.50
## Max. :15.0 Max. :60.00
summary(male)
## empid age gender status
## Min. : 1.000 Min. :30.00 male :8 staff :4
## 1st Qu.: 6.000 1st Qu.:32.00 female:0 faculty:4
## Median : 9.000 Median :39.00
## Mean : 8.625 Mean :40.88
## 3rd Qu.:11.750 3rd Qu.:46.25
## Max. :15.000 Max. :60.00
summary(female)
## empid age gender status
## Min. : 2.000 Min. :30.00 male :0 staff :4
## 1st Qu.: 4.500 1st Qu.:33.00 female:7 faculty:3
## Median : 6.000 Median :37.00
## Mean : 7.286 Mean :40.86
## 3rd Qu.:10.500 3rd Qu.:46.50
## Max. :13.000 Max. :60.00
summary(age)
## Min. 1st Qu. Median Mean 3rd Qu. Max.
## 30.00 32.00 37.00 40.87 47.50 60.00
table1 = table(empinfo$gender)
table1
##
## male female
## 8 7
table2 = table(empinfo$status)
table2
##
## staff faculty
## 8 7
table3 = table(empinfo$gender, empinfo$status)
table3
##
## staff faculty
## male 4 4
## female 4 3
plot(empinfo$age, type = 'l', main = 'Age of Employess', xlab = "Employee ID", ylab = "Age ( Years)", col = "blue")
pie(table1)
barplot(table3,beside = T,xlim=c(1,15),ylim=c(0,5),col = c("blue","red"))
legend('topright',legend=rownames(table3),fill =c("blue","red"),bty="n")
boxplot(empinfo$age~empinfo$status,col = c('red','blue'))
