column_wise

library(dplyr)

## 
## Attaching package: 'dplyr'

## The following objects are masked from 'package:stats':
## 
##     filter, lag

## The following objects are masked from 'package:base':
## 
##     intersect, setdiff, setequal, union

library(readxl)

## Warning: package 'readxl' was built under R version 3.4.4

fruits<-read_xlsx("E:/r/fruits.xlsx")
head(fruits)

## # A tibble: 6 x 3
##   fruits      weight  cost
##   <chr>        <dbl> <dbl>
## 1 mangoes       9.00 27.0 
## 2 apples       18.0  54.0 
## 3 oranges       4.00  8.00
## 4 bananas      12.0  76.0 
## 5 pineapples   14.0  50.0 
## 6 watermalons  26.0  18.0

# column wise percentage with dplyr
fruit_pct<-mutate(fruits,weight_pct=weight/sum(weight),
                  cost_pct=cost/sum(cost))

head(fruit_pct)

## # A tibble: 6 x 5
##   fruits      weight  cost weight_pct cost_pct
##   <chr>        <dbl> <dbl>      <dbl>    <dbl>
## 1 mangoes       9.00 27.0      0.0891   0.114 
## 2 apples       18.0  54.0      0.178    0.228 
## 3 oranges       4.00  8.00     0.0396   0.0338
## 4 bananas      12.0  76.0      0.119    0.321 
## 5 pineapples   14.0  50.0      0.139    0.211 
## 6 watermalons  26.0  18.0      0.257    0.0761

# by for() while() lapply() sapply
sapply(names(fruits)[-1],function(x){
  fruits[paste0(x,"pct")]<- fruits[x]/sum(fruits[x])
})

## $weight.weight
## [1] 0.08910891 0.17821782 0.03960396 0.11881188 0.13861386 0.25742574
## [7] 0.17821782
## 
## $cost.cost
## [1] 0.11416490 0.22832981 0.03382664 0.32135307 0.21141649 0.07610994
## [7] 0.01479915

for (col in names(fruits)[-1]) {
  fruits[paste0(col,"pct")] <- fruits[col]/sum(fruits[col])
}