You can use the following methods to calculate the standard deviation of values in a data frame in dplyr:

**Method 1: Calculate Standard Deviation of One Variable**

library(dplyr) df %>% summarise(sd_var1 = sd(var1, na.rm=TRUE))

**Method 2: Calculate Standard Deviation of Multiple Variables**

library(dplyr) df %>% summarise(sd_var1 = sd(var1, na.rm=TRUE), sd_var2 = sd(var2, na.rm=TRUE))

**Method 3: Calculate Standard Deviation of Multiple Variables, Grouped by Another Variable**

library(dplyr) df %>% group_by(var3) %>% summarise(sd_var1 = sd(var1, na.rm=TRUE), sd_var2 = sd(var2, na.rm=TRUE))

This tutorial explains how to use each method in practice with the following data frame in R:

**#create data frame
df <- data.frame(team=c('A', 'A', 'A', 'A', 'B', 'B', 'B', 'B'),
points=c(12, 15, 18, 22, 14, 17, 29, 35),
assists=c(4, 4, 3, 6, 7, 8, 3, 10))
#view data frame
df
team points assists
1 A 12 4
2 A 15 4
3 A 18 3
4 A 22 6
5 B 14 7
6 B 17 8
7 B 29 3
8 B 35 10
**

**Example 1: Calculate Standard Deviation of One Variable**

The following code shows how to calculate the standard deviation of the **points** variable:

library(dplyr) #calculate standard deviation of points variable df %>% summarise(sd_points = sd(points, na.rm=TRUE)) sd_points 1 7.995534

From the output we can see that the standard deviation of values for the **points** variable is **7.995534**.

**Example 2: Calculate Standard Deviation of Multiple Variables**

The following code shows how to calculate the standard deviation of the **points** and the **assists** variables:

library(dplyr) #calculate standard deviation of points and assists variables df %>% summarise(sd_points = sd(points, na.rm=TRUE), sd_assists = sd(assists, na.rm=TRUE)) sd_points sd_assists 1 7.995534 2.559994

The output displays the standard deviation for both the **points** and **assists** variables.

**Example 3: Calculate Standard Deviation of Multiple Variables, Grouped by Another Variable**

The following code shows how to calculate the standard deviation of the **points** and the **assists** variables:

library(dplyr) #calculate standard deviation of points and assists variables df %>% group_by(team) %>% summarise(sd_points = sd(points, na.rm=TRUE), sd_assists = sd(assists, na.rm=TRUE)) # A tibble: 2 x 3 team sd_points sd_assists 1 A 4.27 1.26 2 B 9.91 2.94

The output displays the standard deviation for both the **points** and **assists** variables for team A and team B.

**Note**: You can include a list of several variables in the **group_by()** function if you would like to group by multiple variables.

**Additional Resources**

The following tutorials explain how to perform other common tasks in R:

How to Filter for Unique Values Using dplyr

How to Filter by Multiple Conditions Using dplyr

How to Count Number of Occurrences in Columns in R