How to find the maximum of each row in an R data frame?

Sometimes we need maximum values, it helps us to identify which case or subject occurs at the greatest point hence we can understand the limit for the sample or population under study. If we want to find the maximum of values two or more columns for each row in an R data frame then pmax function can be used.

Example

Consider the below data frame −

 Live Demo

set.seed(1997) x1<-rpois(20,5) x2<-rpois(20,5) df1<-data.frame(x1,x2) df1

Output

  x1 x2 1  3 4 2  6 3 3  7 3 4  6 2 5  3 0 6  6 5 7  5 6 8  8 4 9  2 5 10 4 3 11 5 2 12 4 9 13 8 5 14 1 3 15 6 4 16 4 9 17 2 8 18 5 4 19 2 4 20 4 3

Finding maximum value in each row −

Example

df1$Max<-pmax(df1$x1,df1$x2) df1

Output

  x1 x2 Max 1  3 4    4 2  6 3    6 3  7 3    7 4  6 2    6 5  3 0    3 6  6 5    6 7  5 6    6 8  8 4    8 9  2 5    5 10 4 3    4 11 5 2    5 12 4 9    9 13 8 5    8 14 1 3    3 15 6 4    6 16 4 9    9 17 2 8    8 18 5 4    5 19 2 4    4 20 4 3    4

Example

 Live Demo

y1<-rnorm(20,5,1) y2<-rnorm(20,5,1) y3<-rnorm(20,5,1) df2<-data.frame(y1,y2,y3) df2

Output

      y1       y2       y3 1 4.099478 4.230448 3.953806 2 4.053187 4.903182 2.858545 3 3.520492 3.852665 3.435332 4 4.543452 3.686695 2.866868 5 4.515121 5.801454 5.242125 6 3.672339 3.837319 4.184841 7 3.632277 5.192438 4.906935 8 4.964407 6.336687 2.883110 9 4.701393 5.669657 5.752201 10 6.110260 6.242568 3.745174 11 5.344662 6.180198 3.678958 12 4.460156 5.141577 7.177730 13 5.290277 5.068554 6.742803 14 5.574233 3.745219 5.408872 15 4.618122 4.796491 5.568271 16 4.957128 4.904917 3.739419 17 5.006405 3.974164 5.190001 18 5.475608 4.734856 5.781379 19 4.794981 5.272916 4.832726 20 5.165257 6.440599 4.406399

Finding maximum value in each row −

Example

df2$Max<-pmax(df2$y1,df2$y2,df2$y3) df2

Output

      y1       y2       y3       Max 1 4.099478 4.230448 3.953806 4.230448 2 4.053187 4.903182 2.858545 4.903182 3 3.520492 3.852665 3.435332 3.852665 4 4.543452 3.686695 2.866868 4.543452 5 4.515121 5.801454 5.242125 5.801454 6 3.672339 3.837319 4.184841 4.184841 7 3.632277 5.192438 4.906935 5.192438 8 4.964407 6.336687 2.883110 6.336687 9 4.701393 5.669657 5.752201 5.752201 10 6.110260 6.242568 3.745174 6.242568 11 5.344662 6.180198 3.678958 6.180198 12 4.460156 5.141577 7.177730 7.177730 13 5.290277 5.068554 6.742803 6.742803 14 5.574233 3.745219 5.408872 5.574233 15 4.618122 4.796491 5.568271 5.568271 16 4.957128 4.904917 3.739419 4.957128 17 5.006405 3.974164 5.190001 5.190001 18 5.475608 4.734856 5.781379 5.781379 19 4.794981 5.272916 4.832726 5.272916 20 5.165257 6.440599 4.406399 6.440599