# creating data frame
df <- data.frame(Sub = c('Math', 'Math', 'Phy', 'Phy', 
                         'Phy', 'Che', 'Che'),
                 Marks = c(8, 2, 4, 9, 9, 7, 1),
                 Add_on = c(3, 1, 9, 4, 7, 8, 2))
  
# view dataframe
df

Sub    Marks    Add_on
Math    8    3
Math    2    1
Phy    4    9
Phy    9    4
Phy    9    7
Che    7    8
Che    1    2

# creating data frame
df <- data.frame(Sub = c('Math', 'Math', 'Phy', 'Phy', 
                         'Phy', 'Che', 'Che'),
                 Marks = c(8, 2, 4, 9, 9, 7, 1),
                 Add_on = c(3, 1, 9, 4, 7, 8, 2))
  
aggregate(dfMarks, list(dfSub), FUN=sum)
aggregate(dfAdd_on, list(dfSub), FUN=sum)

Group.1    x
Che    8
Math    10
Phy    22

Group.1    x
Che    10
Math    4
Phy    20

library(dplyr) 
df %>%                                       
  group_by(Sub) %>%
  summarise_at(vars(Marks),
               list(name = sum))

Sub    name
Che    8
Math    10
Phy    22

library(data.table) 
  
# convert data frame to data table 
setDT(df)
  
# find sum of points scored by sub 
df[ ,list(sum=sum(Marks)), by=Sub]

Sub sum
Math 10
Phy 22
Che 8