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How to find the position of minimum of each numerical column if some columns are categorical in R data frame?
To find the position of minimum of each numerical column if some columns are categorical in R data frame, we can follow the below steps −
First of all, create a data frame.
Then, use numcolwise function from plyr package to find the minimum of each numerical column if some columns are categorical.
Example 1
Create the data frame
Let’s create a data frame as shown below −
factor1<-sample(c("Super","Lower","Medium"),25,replace=TRUE)
factor2<-sample(c("I","II","III"),25,replace=TRUE)
v1<-rnorm(25)
v2<-rnorm(25)
df1<-data.frame(factor1,factor2,v1,v2)
df1Output
On executing, the above script generates the below output(this output will vary on your system due to randomization) −
factor1 factor2 v1 v2 1 Medium III -2.14379228 -0.75943453 2 Super I -1.47939801 1.59666611 3 Lower III 1.23368296 -1.38936623 4 Lower III 0.20952920 -0.04218399 5 Medium III 0.05884382 -0.84164117 6 Super II 1.96347308 0.88664585 7 Lower II 0.31493547 -1.27612944 8 Super III -1.51226987 1.29224755 9 Medium III 1.52328734 1.32171715 10 Medium I -0.16912317 0.46726813 11 Medium I 0.24834413 -0.70308350 12 Super I -1.16519280 -0.04263700 13 Medium III 0.17775948 -1.24434106 14 Super II 0.60504839 -0.50105846 15 Medium II -1.65936651 -1.57653244 16 Medium III 0.96991787 -0.62284764 17 Medium I 0.67194953 0.72451047 18 Lower III 0.73096741 -0.93229961 19 Super III -0.75207261 -1.34829579 20 Lower I -0.19563701 0.06724962 21 Lower I 0.15769044 1.08397200 22 Lower III -1.01078566 0.34309269 23 Medium I -0.16170496 0.29763892 24 Lower III 2.54521045 0.14029670 25 Lower I 0.96949903 -0.43465951
Find the minimum of each column if some columns are categorical
Using numcolwise function from plyr package to find the minimum of each numerical column if some columns are categorical in data frame df1 −
factor1<-sample(c("Super","Lower","Medium"),25,replace=TRUE)
factor2<-sample(c("I","II","III"),25,replace=TRUE)
v1<-rnorm(25)
v2<-rnorm(25)
df1<-data.frame(factor1,factor2,v1,v2)
library(plyr)
numcolwise(which.min)(df1)Output
v1 v2 1 1 15
Example 2
Create the data frame
Let’s create a data frame as shown below −
Level<-sample(c("low","medium","high"),25,replace=TRUE)
Group<-sample(c("first","second"),25,replace=TRUE)
DV1<-rpois(25,5)
DV2<-rpois(25,10)
df2<-data.frame(Level,Group,DV1,DV2)
df2Output
On executing, the above script generates the below output(this output will vary on your system due to randomization) −
Level Group DV1 DV2 1 medium second 6 12 2 medium second 5 8 3 high first 8 7 4 high second 4 17 5 medium second 4 7 6 high second 7 11 7 high second 6 12 8 medium second 8 6 9 high first 5 10 10 medium first 3 6 11 low first 5 12 12 medium second 9 15 13 low second 7 14 14 low first 5 11 15 low first 7 7 16 high second 5 11 17 high second 10 13 18 high first 7 10 19 high first 2 11 20 low second 8 9 21 medium first 4 5 22 medium first 11 13 23 low second 2 12 24 medium first 7 10 25 high first 5 10
Find the minimum of each column if some columns are categorical
Using numcolwise function from plyr package to find the minimum of each numerical column if some columns are categorical in data frame df2 −
Level<-sample(c("low","medium","high"),25,replace=TRUE)
Group<-sample(c("first","second"),25,replace=TRUE)
DV1<-rpois(25,5)
DV2<-rpois(25,10)
df2<-data.frame(Level,Group,DV1,DV2)
library(plyr)
numcolwise(which.min)(df2)Output
DV1 DV2 1 19 21
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