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How to divide each value in a data frame by column total in R?
To divide each value in a data frame by column total, we can use apply function and define the function for the division. For example, if we have a data frame called df that contains five columns then we can divide each value of these columns by column total using the command apply(df,2,function(x){x/sum(x)})
Example
Consider the below data frame −
x1<-rpois(40,5) x2<-rpois(40,2) x3<-rpois(40,8) df1<-data.frame(x1,x2,x3) df1
Output
x1 x2 x3 1 4 3 9 2 9 5 8 3 4 2 6 4 8 3 9 5 3 2 10 6 8 0 8 7 3 3 7 8 6 2 10 9 9 1 8 10 3 2 3 11 4 2 7 12 4 3 6 13 1 3 11 14 6 2 7 15 5 2 10 16 5 2 11 17 3 0 13 18 4 0 7 19 4 2 15 20 4 3 10 21 6 3 9 22 5 3 2 23 7 3 6 24 3 5 9 25 1 7 8 26 1 3 7 27 4 2 7 28 4 1 5 29 3 1 8 30 8 1 10 31 7 1 8 32 5 0 5 33 3 3 3 34 2 2 9 35 5 2 4 36 6 4 9 37 3 1 8 38 7 4 11 39 5 2 5 40 6 0 11
Dividing each value by column total in df1 −
Example
apply(df1,2,function(x){x/sum(x)})Output
x1 x2 x3 [1,] 0.021276596 0.03333333 0.028213166 [2,] 0.047872340 0.05555556 0.025078370 [3,] 0.021276596 0.02222222 0.018808777 [4,] 0.042553191 0.03333333 0.028213166 [5,] 0.015957447 0.02222222 0.031347962 [6,] 0.042553191 0.00000000 0.025078370 [7,] 0.015957447 0.03333333 0.021943574 [8,] 0.031914894 0.02222222 0.031347962 [9,] 0.047872340 0.01111111 0.025078370 [10,] 0.015957447 0.02222222 0.009404389 [11,] 0.021276596 0.02222222 0.021943574 [12,] 0.021276596 0.03333333 0.018808777 [13,] 0.005319149 0.03333333 0.034482759 [14,] 0.031914894 0.02222222 0.021943574 [15,] 0.026595745 0.02222222 0.031347962 [16,] 0.026595745 0.02222222 0.034482759 [17,] 0.015957447 0.00000000 0.040752351 [18,] 0.021276596 0.00000000 0.021943574 [19,] 0.021276596 0.02222222 0.047021944 [20,] 0.021276596 0.03333333 0.031347962 [21,] 0.031914894 0.03333333 0.028213166 [22,] 0.026595745 0.03333333 0.006269592 [23,] 0.037234043 0.03333333 0.018808777 [24,] 0.015957447 0.05555556 0.028213166 [25,] 0.005319149 0.07777778 0.025078370 [26,] 0.005319149 0.03333333 0.021943574 [27,] 0.021276596 0.02222222 0.021943574 [28,] 0.021276596 0.01111111 0.015673981 [29,] 0.015957447 0.01111111 0.025078370 [30,] 0.042553191 0.01111111 0.031347962 [31,] 0.037234043 0.01111111 0.025078370 [32,] 0.026595745 0.00000000 0.015673981 [33,] 0.015957447 0.03333333 0.009404389 [34,] 0.010638298 0.02222222 0.028213166 [35,] 0.026595745 0.02222222 0.012539185 [36,] 0.031914894 0.04444444 0.028213166 [37,] 0.015957447 0.01111111 0.025078370 [38,] 0.037234043 0.04444444 0.034482759 [39,] 0.026595745 0.02222222 0.015673981 [40,] 0.031914894 0.00000000 0.034482759
Example
y1<-rnorm(20) y2<-rnorm(20) df2<-data.frame(y1,y2) df2
Output
y1 y2 1 1.52398233 0.423204080 2 0.48580249 -0.902605575 3 2.67630858 0.007436699 4 0.68410093 0.147904838 5 -1.40680934 1.223015890 6 -2.58064644 1.573868810 7 -0.82872756 -1.663446039 8 0.62632080 -0.478541658 9 -0.52795034 -0.236118274 10 1.68900397 -1.692100343 11 -1.37090356 -0.693266887 12 0.27027656 1.206031106 13 -1.40924870 2.025970432 14 1.06878458 -0.421947510 15 -1.18499758 0.152058450 16 0.85252095 0.520451585 17 0.33823672 0.003101624 18 -0.01792139 0.160589590 19 0.50504901 -0.370946479 20 0.37809177 -1.276916712
Dividing each value by column total in df2 −
Example
apply(df2,2,function(x){x/sum(x)})Output
y1 y2 [1,] 0.8603878 -1.44805767 [2,] 0.2742673 3.08840341 [3,] 1.5109514 -0.02544581 [4,] 0.3862198 -0.50607909 [5,] -0.7942360 -4.18473645 [6,] -1.4569439 -5.38523353 [7,] -0.4678710 5.69173576 [8,] 0.3535991 1.63740368 [9,] -0.2980625 0.80791489 [10,] 0.9535533 5.78978085 [11,] -0.7739648 2.37211898 [12,] 0.1525888 -4.12662041 [13,] -0.7956132 -6.93216857 [14,] 0.6033989 1.44375812 [15,] -0.6690087 -0.52029131 [16,] 0.4813039 -1.78080492 [17,] 0.1909568 -0.01061268 [18,] -0.0101178 -0.54948191 [19,] 0.2851332 1.26925027 [20,] 0.2134576 4.36916638
Updated on: 17-Mar-2021
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