Data Manipulation in R for Apriori - r

Question

I have a part of the data-set as shown below in the form of csv,the number of rows and columns are more than what is shown.I want to implement apriori on this data-set,Say I have this:-
Maths Science C++ Java DC
[1] 75 44 55 56 88
[2] 56 88 54 78 44
the original dataset has total columns(representing subjects)=30 and serial number(representing students)=24,
DATASET:link
I want to covert this dataset in the form shown below:-
[1] {Maths,DC}
[2] {Science,Java}
i.e A list of list(I think this is what it is called) containing the colnames.A list for a student shows in which subject he/she scored more than or equal to 75 marks,rest of the subjects are dropped(The only condition of the problem)
eq:- first student scored 75+ marks in Dc and Maths and so his list includes only dc and maths.
I am sorry for posting this,but I searched a lot on stack,and found a few of the working suggestions ,but couldn't reach the final goal.
My goal is to get a form like this:-
[9834] {semi-finished bread,
bottled water,
soda,
bottled beer}
[9835] {chicken,
tropical fruit,
other vegetables,
vinegar,
shopping bags}
As given in :-
library(arules)
inspect(Groceries)
OR I WILL APPRECIATE IF ANYONE CAN SUGGEST A WAY TO REPRESENT THE DATA IN OTHER FORM WHICH APRIORI CAN UNDERSTAND,BUT IT SHOULD FOLLOW THE NECESSARY CONDITIONS AS STATED.
*(sorry for the long post,I hope this conversion of my dataset in this format may help me study the pattern in student-subject dataset,thnx a ton for all the help)

Answer 1

library(plyr)
library(arules)
df <- read.table(text =
" 75 44 55 56 88
56 88 54 78 44")
names(df) <- c("Maths", "Science", "C++", "Java", "DC")
transactions <- as(alply(df, 1, function(x) names(x)[x >= 75]), "transactions")
inspect(transactions)
# items transactionID
# [1] {DC,Maths} 1
# [2] {Java,Science} 2
Edit: It works with your example dataset, too:
library(plyr)
library(arules)
df <- read.csv(file = url("https://drive.google.com/uc?export=download&id=0B3kdblyHw4qLR0dpT24xWUZGcGs"))
transactions <- as(alply(df, 1, function(x) names(x)[x >= 75]), "transactions")
inspect(transactions)
# items transactionID
# [1] {CD,CG,CN,DA,Data.Struc} 1
# [2] {CD,CG,CO,ML,OS} 2
# [3] {CN,Data.Struc,DC,DM,DMS} 3
# [4] {CHE,DD,DM,EC,EE} 4
# [5] {CHE,CN,MATHS,PHY} 5
# [6] {Data.Science,DM,DMS,ML,OS} 6
# [7] {CD,DA,Data.Struc,EC,MATHS} 7
# [8] {CG,CHE,CN,CO,OS} 8
# [9] {CN,CO,Data.Science,DC,DMS} 9
# [10] {DC,DD,EC,EE,PHY} 10
# [11] {CHE,DD,DMS,MATHS,PHY} 11
# [12] {CN,Data.Science,DM,MATHS,ML} 12
# [13] {CD,CG,DA,Data.Science,Data.Struc} 13
# [14] {CG,CO,EE,MATHS,OS} 14
# [15] {CN,CO,DC,DMS,PHY} 15
# [16] {CN,CO,DD,EC,EE} 16
# [17] {CHE,DA,EE,MATHS,PHY} 17
# [18] {Data.Science,DD,DM,ML,PHY} 18
# [19] {CD,CO,DA,Data.Struc,DC} 19
# [20] {CG,CO,DD,DM,OS} 20
# [21] {CG,CN,DA,DC,DMS} 21
# [22] {DD,EC,EE,ML,OS} 22
# [23] {CHE,CN,Data.Struc,MATHS,PHY} 23
# [24] {CG,Data.Science,DM,EE,ML} 24