使用数据框R中行的最后一列的最后一个值添加每列

Question

I want to add each column of dataframe with the last column of the row in R. My dataframe-

L   E   B1  P   B2  M   Value
5   5   0   20  2   5   100
10  6   0   40  15  2   150
6   15  0   50  6   10  160
1   10  0   55  5   20  160
0   20  0   80  0   20  200
10  1   20  80  10  10  250
8   2   40  30  5   10  300
5   3   60  30  5   20  350
5   4   30  75  5   20  400
1   0   50  80  0   10  400
2   0   40  60  5   20  500
0   0   60  50  0   30  500

So 1st row will be like-

L   E   B1  P   B2  M   Value
5*100   5*100   0*100   20*100  2*100   5*100   100
10  6   0   40  15  2   150
6   15  0   50  6   10  160
1   10  0   55  5   20  160
0   20  0   80  0   20  200
10  1   20  80  10  10  250
8   2   40  30  5   10  300
5   3   60  30  5   20  350
5   4   30  75  5   20  400
1   0   50  80  0   10  400
2   0   40  60  5   20  500
0   0   60  50  0   30  500

I tried to use lapply

lapply(df1, function(x) x * tail(x,1) )

But it takes the row value , so how to get each row last column value or any specific column to add with all other column values in R

Answer 1

Using dplyr and assuming your dataframe is df:

library(dplyr)

df %>% mutate_each(funs(. * Value), -Value)

Answer 2

Not clear if you want to multiply or divide (there seems to be a contradiction between what you ask for and your own attempt) but here's an approach for multiplication:

cbind(mydf[-length(mydf)] * mydf[[length(mydf)]], mydf[length(mydf)])
#       L    E    B1     P   B2     M Value
# 1   500  500     0  2000  200   500   100
# 2  1500  900     0  6000 2250   300   150
# 3   960 2400     0  8000  960  1600   160
# 4   160 1600     0  8800  800  3200   160
# 5     0 4000     0 16000    0  4000   200
# 6  2500  250  5000 20000 2500  2500   250
# 7  2400  600 12000  9000 1500  3000   300
# 8  1750 1050 21000 10500 1750  7000   350
# 9  2000 1600 12000 30000 2000  8000   400
# 10  400    0 20000 32000    0  4000   400
# 11 1000    0 20000 30000 2500 10000   500
# 12    0    0 30000 25000    0 15000   500

The basic idea is to just multiply all the columns except for the last one by the values in the last column. Since that column has been dropped, you add it back in with cbind .

Answer 3

Here's another base R option:

n <- ncol(df)
df[-n] <- df[-n] * df[[n]]

Note: running this code will modify your existing data.frame. If you want to create a new data.frame and keep the old one as is, you'd better use the answer by Ananda Mahto or one of the others.

Answer 4

Just to complete the picture, you could also update the data by reference using data.table package

library(data.table)
setDT(df)[, names(df)[-length(df)] := 
            lapply(.SD, "*", df$Value), 
            .SDcols = -"Value"]
df
#        L    E    B1     P   B2     M Value
#  1:  500  500     0  2000  200   500   100
#  2: 1500  900     0  6000 2250   300   150
#  3:  960 2400     0  8000  960  1600   160
#  4:  160 1600     0  8800  800  3200   160
#  5:    0 4000     0 16000    0  4000   200
#  6: 2500  250  5000 20000 2500  2500   250
#  7: 2400  600 12000  9000 1500  3000   300
#  8: 1750 1050 21000 10500 1750  7000   350
#  9: 2000 1600 12000 30000 2000  8000   400
# 10:  400    0 20000 32000    0  4000   400
# 11: 1000    0 20000 30000 2500 10000   500
# 12:    0    0 30000 25000    0 15000   500