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How to find the sin of each value in columns if some columns are categorical in R data frame?
To find the sin of each value in columns 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 sin of each value in columns if some columns are categorical.
Example
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<-sample(1:5,25,replace=TRUE)
DV2<-sample(1:5,25,replace=TRUE)
df<-data.frame(Level,Group,DV1,DV2)
dfOutput
On executing, the above script generates the below output(this output will vary on your system due to randomization) −
Level Group DV1 DV2 1 low first 1 1 2 low second 1 5 3 medium first 5 3 4 low first 4 1 5 low second 2 5 6 low first 3 3 7 high second 3 1 8 low second 1 1 9 high first 2 4 10 low second 1 3 11 high first 2 5 12 low first 3 2 13 medium second 5 4 14 low second 5 4 15 low second 3 4 16 medium first 5 5 17 high second 4 5 18 high second 4 1 19 low first 4 4 20 medium second 1 3 21 high second 4 3 22 medium first 1 3 23 medium second 2 3 24 high second 3 3 25 medium first 4 3
Find the sin of each value in columns if some columns are categorical
Using numcolwise function from plyr package to find the sin of each value in columns if some columns are categorical in the data frame df −
Level<-sample(c("low","medium","high"),25,replace=TRUE)
Group<-sample(c("first","second"),25,replace=TRUE)
DV1<-sample(1:5,25,replace=TRUE)
DV2<-sample(1:5,25,replace=TRUE)
df<-data.frame(Level,Group,DV1,DV2)
library(plyr)
numcolwise(sin)(df)Output
DV1 DV2 1 0.9092974 0.1411200 2 -0.9589243 -0.7568025 3 0.9092974 0.1411200 4 0.1411200 -0.7568025 5 -0.7568025 -0.7568025 6 -0.7568025 0.8414710 7 0.8414710 0.1411200 8 0.8414710 0.8414710 9 0.1411200 -0.9589243 10 -0.7568025 -0.9589243 11 -0.9589243 0.1411200 12 -0.9589243 0.8414710 13 -0.7568025 0.9092974 14 0.8414710 0.1411200 15 0.8414710 -0.7568025 16 0.1411200 0.8414710 17 0.1411200 0.1411200 18 0.9092974 0.9092974 19 0.9092974 0.1411200 20 -0.9589243 0.8414710 21 0.9092974 0.1411200 22 -0.7568025 0.9092974 23 -0.7568025 -0.9589243 24 -0.7568025 0.9092974 25 -0.7568025 0.1411200
Updated on: 15-Nov-2021
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