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# LAB WEEK 5
#1. Read file marks1.csv
marks1 <- read.csv(file="D:/Documents/UM SEM1/WQD7004 PROGRAMMING/marks1.csv",
head=TRUE, sep=",")
marks1## X X.1 test asgn Prsnt Final q1 q2 q3 q4
## 1 60001 Ahmad 15 14 17 13 0.0 9 2 4.0
## 2 60003 Abu 26 13 18 22 3.0 5 8 6.0
## 3 60006 Samy 21 15 19 25 6.0 7 4 8.0
## 4 60008 Chong 25 10 17 14 2.0 3 4 5.0
## 5 60009 Paul 25 15 16 20 3.0 7 6 4.0
## 6 60011 John 18 15 19 22 4.0 7 4 7.0
## 7 60014 Devi 30 15 19 28 4.0 5 9 10.0
## 8 60015 Pillip 16 15 19 20 4.0 5 6 5.0
## 9 60023 Meilin 18 13 18 22 2.0 5 7 8.0
## 10 60025 Lily 30 14 18 24 5.5 6 5 7.5
## 11 60026 Jamil 12 10 12 12 1.0 5 1 6.0#2. Check the data frame info using a few available functions
View(marks1)
str(marks1)## 'data.frame': 11 obs. of 10 variables:
## $ X : int 60001 60003 60006 60008 60009 60011 60014 60015 60023 60025 ...
## $ X.1 : chr "Ahmad" "Abu" "Samy" "Chong" ...
## $ test : int 15 26 21 25 25 18 30 16 18 30 ...
## $ asgn : int 14 13 15 10 15 15 15 15 13 14 ...
## $ Prsnt: int 17 18 19 17 16 19 19 19 18 18 ...
## $ Final: int 13 22 25 14 20 22 28 20 22 24 ...
## $ q1 : num 0 3 6 2 3 4 4 4 2 5.5 ...
## $ q2 : int 9 5 7 3 7 7 5 5 5 6 ...
## $ q3 : int 2 8 4 4 6 4 9 6 7 5 ...
## $ q4 : num 4 6 8 5 4 7 10 5 8 7.5 ...class(marks1)## [1] "data.frame"typeof(marks1)## [1] "list"ncol(marks1)## [1] 10nrow(marks1)## [1] 11head(marks1)## X X.1 test asgn Prsnt Final q1 q2 q3 q4
## 1 60001 Ahmad 15 14 17 13 0 9 2 4
## 2 60003 Abu 26 13 18 22 3 5 8 6
## 3 60006 Samy 21 15 19 25 6 7 4 8
## 4 60008 Chong 25 10 17 14 2 3 4 5
## 5 60009 Paul 25 15 16 20 3 7 6 4
## 6 60011 John 18 15 19 22 4 7 4 7tail(marks1)## X X.1 test asgn Prsnt Final q1 q2 q3 q4
## 6 60011 John 18 15 19 22 4.0 7 4 7.0
## 7 60014 Devi 30 15 19 28 4.0 5 9 10.0
## 8 60015 Pillip 16 15 19 20 4.0 5 6 5.0
## 9 60023 Meilin 18 13 18 22 2.0 5 7 8.0
## 10 60025 Lily 30 14 18 24 5.5 6 5 7.5
## 11 60026 Jamil 12 10 12 12 1.0 5 1 6.0summary(marks1)## X X.1 test asgn
## Min. :60001 Length:11 Min. :12.00 Min. :10.00
## 1st Qu.:60007 Class :character 1st Qu.:17.00 1st Qu.:13.00
## Median :60011 Mode :character Median :21.00 Median :14.00
## Mean :60013 Mean :21.45 Mean :13.55
## 3rd Qu.:60019 3rd Qu.:25.50 3rd Qu.:15.00
## Max. :60026 Max. :30.00 Max. :15.00
## Prsnt Final q1 q2
## Min. :12.00 Min. :12.00 Min. :0.000 Min. :3.000
## 1st Qu.:17.00 1st Qu.:17.00 1st Qu.:2.000 1st Qu.:5.000
## Median :18.00 Median :22.00 Median :3.000 Median :5.000
## Mean :17.45 Mean :20.18 Mean :3.136 Mean :5.818
## 3rd Qu.:19.00 3rd Qu.:23.00 3rd Qu.:4.000 3rd Qu.:7.000
## Max. :19.00 Max. :28.00 Max. :6.000 Max. :9.000
## q3 q4
## Min. :1.000 Min. : 4.000
## 1st Qu.:4.000 1st Qu.: 5.000
## Median :5.000 Median : 6.000
## Mean :5.091 Mean : 6.409
## 3rd Qu.:6.500 3rd Qu.: 7.750
## Max. :9.000 Max. :10.000#3. Check the names of the variables in the data frame
names(marks1)## [1] "X" "X.1" "test" "asgn" "Prsnt" "Final" "q1" "q2" "q3"
## [10] "q4"#4. Rename the first variable X to ID
names(marks1)[1] <- "ID"
marks1## ID X.1 test asgn Prsnt Final q1 q2 q3 q4
## 1 60001 Ahmad 15 14 17 13 0.0 9 2 4.0
## 2 60003 Abu 26 13 18 22 3.0 5 8 6.0
## 3 60006 Samy 21 15 19 25 6.0 7 4 8.0
## 4 60008 Chong 25 10 17 14 2.0 3 4 5.0
## 5 60009 Paul 25 15 16 20 3.0 7 6 4.0
## 6 60011 John 18 15 19 22 4.0 7 4 7.0
## 7 60014 Devi 30 15 19 28 4.0 5 9 10.0
## 8 60015 Pillip 16 15 19 20 4.0 5 6 5.0
## 9 60023 Meilin 18 13 18 22 2.0 5 7 8.0
## 10 60025 Lily 30 14 18 24 5.5 6 5 7.5
## 11 60026 Jamil 12 10 12 12 1.0 5 1 6.0#5. Rename the second variable X.1 to StuName
names(marks1)[2] <- "StuName"
marks1## ID StuName test asgn Prsnt Final q1 q2 q3 q4
## 1 60001 Ahmad 15 14 17 13 0.0 9 2 4.0
## 2 60003 Abu 26 13 18 22 3.0 5 8 6.0
## 3 60006 Samy 21 15 19 25 6.0 7 4 8.0
## 4 60008 Chong 25 10 17 14 2.0 3 4 5.0
## 5 60009 Paul 25 15 16 20 3.0 7 6 4.0
## 6 60011 John 18 15 19 22 4.0 7 4 7.0
## 7 60014 Devi 30 15 19 28 4.0 5 9 10.0
## 8 60015 Pillip 16 15 19 20 4.0 5 6 5.0
## 9 60023 Meilin 18 13 18 22 2.0 5 7 8.0
## 10 60025 Lily 30 14 18 24 5.5 6 5 7.5
## 11 60026 Jamil 12 10 12 12 1.0 5 1 6.0#6. Remove the first two column from the data frame
newmarks1 <- marks1[c(-1,-2)]
newmarks1## test asgn Prsnt Final q1 q2 q3 q4
## 1 15 14 17 13 0.0 9 2 4.0
## 2 26 13 18 22 3.0 5 8 6.0
## 3 21 15 19 25 6.0 7 4 8.0
## 4 25 10 17 14 2.0 3 4 5.0
## 5 25 15 16 20 3.0 7 6 4.0
## 6 18 15 19 22 4.0 7 4 7.0
## 7 30 15 19 28 4.0 5 9 10.0
## 8 16 15 19 20 4.0 5 6 5.0
## 9 18 13 18 22 2.0 5 7 8.0
## 10 30 14 18 24 5.5 6 5 7.5
## 11 12 10 12 12 1.0 5 1 6.0#7. Use apply() function to sum all the marks in the data frame and put them in
# a new vector called Total and bind the vector to the data frame
newmarks1$Total <- apply(newmarks1, 1, function(newmarks1)sum(newmarks1))
newmarks1## test asgn Prsnt Final q1 q2 q3 q4 Total
## 1 15 14 17 13 0.0 9 2 4.0 74
## 2 26 13 18 22 3.0 5 8 6.0 101
## 3 21 15 19 25 6.0 7 4 8.0 105
## 4 25 10 17 14 2.0 3 4 5.0 80
## 5 25 15 16 20 3.0 7 6 4.0 96
## 6 18 15 19 22 4.0 7 4 7.0 96
## 7 30 15 19 28 4.0 5 9 10.0 120
## 8 16 15 19 20 4.0 5 6 5.0 90
## 9 18 13 18 22 2.0 5 7 8.0 93
## 10 30 14 18 24 5.5 6 5 7.5 110
## 11 12 10 12 12 1.0 5 1 6.0 59#8. Using a user defined function called function(), use the apply() function to
# add variable 1 to variable 3, and write to a new variable in the data frame
# called CW.
# The function is defined as the following
# function(x) {x[1]+x[2]+x[3]}
newmarks1$CW <- apply(newmarks1, 1, function(newmarks1){newmarks1[1]+newmarks1[2]
+newmarks1[3]})
newmarks1## test asgn Prsnt Final q1 q2 q3 q4 Total CW
## 1 15 14 17 13 0.0 9 2 4.0 74 17
## 2 26 13 18 22 3.0 5 8 6.0 101 18
## 3 21 15 19 25 6.0 7 4 8.0 105 19
## 4 25 10 17 14 2.0 3 4 5.0 80 17
## 5 25 15 16 20 3.0 7 6 4.0 96 16
## 6 18 15 19 22 4.0 7 4 7.0 96 19
## 7 30 15 19 28 4.0 5 9 10.0 120 19
## 8 16 15 19 20 4.0 5 6 5.0 90 19
## 9 18 13 18 22 2.0 5 7 8.0 93 18
## 10 30 14 18 24 5.5 6 5 7.5 110 18
## 11 12 10 12 12 1.0 5 1 6.0 59 12mynewmarks1 <- cbind(marks1[1:2], newmarks1)
mynewmarks1## ID StuName test asgn Prsnt Final q1 q2 q3 q4 Total CW
## 1 60001 Ahmad 15 14 17 13 0.0 9 2 4.0 74 17
## 2 60003 Abu 26 13 18 22 3.0 5 8 6.0 101 18
## 3 60006 Samy 21 15 19 25 6.0 7 4 8.0 105 19
## 4 60008 Chong 25 10 17 14 2.0 3 4 5.0 80 17
## 5 60009 Paul 25 15 16 20 3.0 7 6 4.0 96 16
## 6 60011 John 18 15 19 22 4.0 7 4 7.0 96 19
## 7 60014 Devi 30 15 19 28 4.0 5 9 10.0 120 19
## 8 60015 Pillip 16 15 19 20 4.0 5 6 5.0 90 19
## 9 60023 Meilin 18 13 18 22 2.0 5 7 8.0 93 18
## 10 60025 Lily 30 14 18 24 5.5 6 5 7.5 110 18
## 11 60026 Jamil 12 10 12 12 1.0 5 1 6.0 59 12Note that the echo = FALSE parameter was added to the code chunk to prevent printing of the R code that generated the plot.