I have create marks of 15 students for 5 subjects. I have also create a vector of passmarks in each subject. I want to mutate each column of marks with Pass or Fail depending upon the values given in the vector passmarks... I have been able to manually, but I want to use some looping function so that it maps the passmarks to columns and then mutates creating a new column or new dataframe with Pass or Fail.

create a sample vector with 15 positions

x <- runif(15)

#convert to DF

marks <- as.data.frame(x)

marks[1:5] <- sapply(1:5, "+", rnorm(5,60,15))

names(marks) <- paste0("sub", 1:5)

marks

colMeans(marks)

lapply(marks, range)

lapply(marks, is.na)

colSums(is.na(marks))

marks1 = round(marks,2)

passmarks = c(60, 65, 62,70, 45)

names(marks1)

marks1 %>% mutate(sub1a = ifelse(sub1 <= passmarks[1], 'F','P'), sub2a = ifelse(sub2 <= passmarks[2], 'F','P'), sub3a = ifelse(sub3 <= passmarks[3], 'F','P'), sub4a = ifelse(sub4 <= passmarks[4], 'F','P'), sub5a = ifelse(sub5 <= passmarks[5], 'F','P'))





marks1 %>% summarise_at(vars(sub1:sub5), mean, na.rm=T)

marks1 %>% mutate_all(funs(./75))

Part-II of the problem::::
This stage of problem was resolved. I have to calculate SGPA for each student. If I have marks I have assign grades to each subject of students. This depends on mean of each subject and std dev of certain sequence. This grades depends on Mean of each column of marks and std value which are same for all columns.
Next if we have grades we have to calculate Total Grade Points secured. For each subject column there are credit points which is known. Also grade point wrt to each grade is also known. I want to calculate numerical sum of credit points for each student.. I have tried to code some part of it... I would seek your help to make it simpler and elegant...

#continued

#find mean of each subject

(meanx = colMeans(marks1))

#(sdx=apply(marks1,2,sd))

(sd1 = seq(1.5, -2,-.5)) #this pattern is same across all subjects

#these are the grades associated with each Std Dev

(names(sd1) = c('AP','A','AM','BP','B','BM','CP','C'))

sd1

sd1['AP']  #test for A+



    #this is sample vectorise function created: here meanx should be replace with respective mean of the subject 

    RgradeAssigned = function(x) { ifelse(x >= meanx * sd1['AP'],'AP', ifelse(x >= meanx + sd1['A'], 'A', ifelse(x >= meanx + sd1['AM'], 'AM', ifelse(x >= meanx + sd1['BP'], 'BP', ifelse(x >= meanx * sd1['B'], 'B',ifelse(x >= meanx + sd1['BM'], 'BM',ifelse(x >= meanx + sd1['CP'], 'CP',ifelse(x >= meanx + sd1['C'], 'C', 'F'))))))))}

    RgradeAssigned(marks1)

    #meanx should mean from the vector meanx : for sub1 it should be meanx[1]

    meanx



    #Calculate SGPA

    #credit for each subject 

    (subcredits = c(3,2,4,3,3))

    #gradepoints with wrt to each grade

    gradeName = c('AP','A','AM','BP','B','BM','CP','C','F')

    gradePoint = c(10,9,8,7,6,5,4,3,0)

    names(gradePoint) = gradeName

    gradePoint

    # if a particular grade, find grade point -> multiply by subject credit -> for each student -> find sum of grades ie sum each row

    # for eg row grade were

    #'AP','A','AM','BP','B' -> 10,9,8,7,6 -> 10*3 + 9*2+ 8*4 + 7*3 + 6*3 

    #subject credits : 3,2,4,3,3



    #Now Mapping of Grade to Point is available

You can use mapply , i.e.

mapply(`<`, passmarks, marks1)

which gives,

       [,1]  [,2]  [,3]  [,4] [,5]

 [1,] FALSE FALSE FALSE FALSE TRUE

 [2,] FALSE FALSE FALSE FALSE TRUE

 [3,] FALSE FALSE FALSE FALSE TRUE

 [4,]  TRUE  TRUE  TRUE FALSE TRUE

 [5,] FALSE FALSE FALSE FALSE TRUE

 [6,] FALSE FALSE FALSE FALSE TRUE

 [7,] FALSE FALSE FALSE FALSE TRUE

 [8,] FALSE FALSE FALSE FALSE TRUE

 [9,]  TRUE  TRUE  TRUE FALSE TRUE

[10,] FALSE FALSE FALSE FALSE TRUE

[11,] FALSE FALSE FALSE FALSE TRUE

[12,] FALSE FALSE FALSE FALSE TRUE

[13,] FALSE FALSE FALSE FALSE TRUE

[14,]  TRUE FALSE  TRUE FALSE TRUE

[15,] FALSE FALSE FALSE FALSE TRUE

To get a matrix with PASS and FAIL, then one way to do it could be

matrix(c('FAIL', 'PASS')[mapply(`<`, passmarks, marks1) + 1], ncol = ncol(marks1))