How to find n number of quartiles for every row in R?\\n

To find the n number of quartiles for every row in an R data frame, we can use apply function along with quantile function.

For example, if we have a data frame called df that contains hundred rows and we want to find two quartiles say first and third for each row then we can use the below mentioned command −

apply(df,1,quantile,c(0.25,0.75))

Example 1

Following snippet creates a sample data frame −

x1<-rpois(20,1) x2<-rpois(20,2) x3<-rpois(20,5) x4<-rpois(20,10) df1<-data.frame(x1,x2,x3,x4) df1

The following dataframe is created −

   x1 x2 x3 x4 1  0  2  5  12 2  0  2  5  11 3  2  1  6   9 4  3  1  6   8 5  1  1  9  11 6  0  4  3   8 7  1  2  5   7 8  1  0  5  10 9  1  4  8  11 10 4  2  5  14 11 0  5  7   9 12 1  2  9  10 13 1  2  8  11 14 0  1  2   9 15 1  0  3  10 16 1  3  6  11 17 0  1  3  11 18 2  1  1   7 19 1  1  7   8 20 0  3  5   9

To find the first quartile, second quartile, and third quartile for each row in df1, add the following code to the above snippet −

x1<-rpois(20,1) x2<-rpois(20,2) x3<-rpois(20,5) x4<-rpois(20,10) df1<-data.frame(x1,x2,x3,x4) apply(df1,1,quantile,c(0.25,0.50,0.75))

Output

If you execute all the above given snippets as a single program, it generates the following output −

    [,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10] [,11] [,12] [,13] [,14] 25% 1.50 1.5  1.75 2.5  1.0  2.25 1.75 0.75 3.25 3.50  3.75  1.75  1.75  0.75 50% 3.50 3.5  4.00 4.5  5.0  3.50 3.50 3.00 6.00 4.50  6.00  5.50  5.00  1.50 75% 6.75 6.5 6.75 6.5 9.5 5.00 5.50 6.25 8.75 7.25 7.50 9.25 8.75 3.75   [,15] [,16] [,17] [,18] [,19] [,20] 25% 0.75 2.50 0.75  1.00  1.00  2.25 50% 2.00 4.50 2.00  1.50  4.00  4.00 75% 4.75 7.25 5.00  3.25  7.25  6.00

Example 2

Following snippet creates a sample data frame −

y1<-round(rnorm(20),2) y2<-round(rnorm(20),2) y3<-round(rnorm(20),2) df2<-data.frame(y1,y2,y3) df2

The following dataframe is created −

     y1     y2     y3 1  -1.41   1.96  -0.23 2  -0.27  -0.05  -0.51 3   0.72   0.40  -0.93 4   1.07   1.68  -0.82 5   0.34  -0.86  -0.29 6   1.67  -0.13   1.60 7   0.38   0.57  -0.28 8  -0.91   0.39   0.61 9   0.99   0.75   0.21 10  0.40   0.74  -2.61 11  1.52   0.97   0.92 12  1.35   0.14   0.04 13 -0.51   0.49  -0.29 14  0.46   0.07  -1.62 15 -0.51  -1.55   0.81 16 -0.65  -0.20   0.96 17  0.68  -0.75   0.65 18 -0.34   0.22  -0.26 19 -0.59  -0.28  -0.09 20  1.98   0.85   0.15

To find the first quartile, second quartile, and third quartile for each row in df1, add the following code to the above snippet −

apply(df1,1,quantile,c(0.25,0.75)) 

Output

If you execute all the above given snippets as a single program, it generates the following output −

    [,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10] [,11] [,12] [,13] [,14] 25% 1.50 1.5  1.75 2.5  1.0  2.25 1.75 0.75 3.25 3.50  3.75  1.75  1.75  0.75 75% 6.75 6.5  6.75 6.5  9.5  5.00 5.50 6.25 8.75 7.25  7.50  9.25  8.75  3.75      [,15] [,16] [,17] [,18] [,19] [,20] 25% 0.75  2.50   0.75  1.00  1.00  2.25 75% 4.75  7.25   5.00  3.25  7.25  6.00