Easy Way to Take Means of Rows in R

How to find the row mean for selected columns in R data frame?

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To find the row mean for selected columns in R data frame, we can use mutate function of dplyr package along with rowMeans function.

For Example, if we have a data frame called df that contains three columns say X, Y, and Z then mean of each row for columns X and Y can be found by using the below command −

df %% mutate(X_Y_Mean=select(.,c("X","Y")) %% rowMeans())

Example 1

Following snippet creates a sample data frame −

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

The following dataframe is created

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

To load dplyr package and find the row means for columns x1 and x2 on the above created data frame, add the following code to the above snippet −

x1<-rpois(20,1) x2<-rpois(20,2) x3<-rpois(20,2) x4<-rpois(20,5) df1<-data.frame(x1,x2,x3,x4) library(dplyr) df1 %% mutate(X1_X2_Mean=select(.,c("x1","x2")) %% rowMeans())

Output

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

  x1 x2 x3 x4 X1_X2_Mean 1  1  1  0  2   1.0 2  2  1  4  7   1.5 3  1  0  3  4   0.5 4  2  2  3  2   2.0 5  2  1  1  5   1.5 6  0  3  1  5   1.5 7  0  2  6  5   1.0 8  0  3  5  7   1.5 9  1  2  2  4   1.5 10 3  1  3  7   2.0 11 1  1  1  4   1.0 12 3  2  0  7   2.5 13 0  2  1  3   1.0 14 1  5  3  3   3.0 15 1  2  0  4   1.5 16 0  3  1  6   1.5 17 0  2  3  4   1.0 18 3  0  1  3   1.5 19 0  3  3  1   1.5 20 2  2  2  1   2.0

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  -1.77  0.25 -0.85 2   0.38 -0.53  0.01 3  -0.87  0.56  0.06 4   0.37  1.55  0.44 5  -0.01  0.29 -0.35 6  -1.22 -0.40  1.55 7  -0.51 -0.28 -0.04 8   0.24  1.85  0.60 9   0.50  0.50 -0.38 10  0.97  1.06  1.98 11  0.88 -0.83 -1.00 12 -1.31  0.56 -1.06 13  0.41 -0.28  1.57 14 -1.66 -1.30  0.56 15 -2.15 -0.47  0.84 16 -0.27 -2.58 -0.44 17 -2.45  0.90 -2.49 18 -1.82 -1.39 -0.31 19  0.15  0.19 -0.70 20  1.00  0.97  0.05

To find the row means for columns y2 and y3 on the above created data frame, add the following code to the above snippet −

y1<-round(rnorm(20),2) y2<-round(rnorm(20),2) y3<-round(rnorm(20),2) df2<-data.frame(y1,y2,y3) df2 %% mutate(y2_y3_Mean=select(.,c("y2","y3")) %% rowMeans())

Output

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

     y1   y2    y3  y2_y3_Mean 1  -1.77  0.25 -0.85 -0.300 2   0.38 -0.53  0.01 -0.260 3  -0.87  0.56  0.06  0.310 4   0.37  1.55  0.44  0.995 5  -0.01  0.29 -0.35 -0.030 6  -1.22 -0.40  1.55  0.575 7  -0.51 -0.28 -0.04 -0.160 8   0.24  1.85  0.60  1.225 9   0.50  0.50 -0.38  0.060 10  0.97  1.06  1.98  1.520 11  0.88 -0.83 -1.00 -0.915 12 -1.31  0.56 -1.06 -0.250 13  0.41 -0.28  1.57  0.645 14 -1.66 -1.30  0.56 -0.370 15 -2.15 -0.47  0.84  0.185 16 -0.27 -2.58 -0.44 -1.510 17 -2.45  0.90 -2.49 -0.795 18 -1.82 -1.39 -0.31 -0.850 19  0.15  0.19 -0.70 -0.255 20  1.00  0.97  0.05  0.510

Updated on 01-Nov-2021 09:56:41

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