You can use the following basic syntax to calculate the standard deviation of rows in R:
row_stdev rm=TRUE)
The following example shows how to use this syntax in R.
Example: Calculate Standard Deviation of Rows in R
Suppose we have the following data frame in R:
#create data frame df frame(game1=c(12, 15, 15, 18, 29, 30, 31), game2=c(15, 17, 17, 16, 29, 8, 14), game3=c(8, 22, 27, 35, 29, 22, 17)) #view data frame df game1 game2 game3 1 12 15 8 2 15 17 22 3 15 17 27 4 18 16 35 5 29 29 29 6 30 8 22 7 31 14 17
We can use the following syntax to calculate the standard deviation of the values in each row:
#calculate standard deviation of each row row_stdev rm=TRUE) #view standard deviation of each row row_stdev [1] 3.511885 3.605551 6.429101 10.440307 0.000000 11.135529 9.073772
From the output we can see:
- The standard deviation of values in the first row is 3.511885.
- The standard deviation of values in the second row is 3.605551.
- The standard deviation of values in the third row is 6.429101.
And so on.
If we’d like, we can also use the transform() function to add a new column to the data frame that shows the standard deviation of values in each row:
#add column that displays standard deviation of each row df rm=TRUE)) #view updated data frame df game1 game2 game3 row_stdev 1 12 15 8 3.511885 2 15 17 22 3.605551 3 15 17 27 6.429101 4 18 16 35 10.440307 5 29 29 29 0.000000 6 30 8 22 11.135529 7 31 14 17 9.073772
The new column called row_stdev displays the standard deviation of values in each row.
Note: The standard deviation of values in row 5 is equal to zero because each of the values is the same, thus there is no “deviation” at all in the values.
Related: How to Interpret a Standard Deviation of Zero
Additional Resources
The following tutorials explain how to perform other common functions in R:
How to Calculate Standard Deviation Using dplyr
How to Calculate Weighted Standard Deviation in R
How to Calculate Pooled Standard Deviation in R