You can use the following syntax to calculate the geometric mean of a set of numbers in R:

exp(mean(log(x)))

The following examples show how to use this function in practice.

**Example 1: Calculate Geometric Mean of Vector**

The following code shows how to calculate the geometric mean for a single vector in R:

#define vector x <- c(4, 8, 9, 9, 12, 14, 17) #calculate geometric mean of values in vector exp(mean(log(x))) [1] 9.579479

**Example 2: Calculate Geometric Mean of Vector with Zeros**

If your vector contains zeros or negative numbers, the formula above will return a 0 or a NaN.

To ignore zeros and negative numbers when calculating the geometric mean, you can use the following formula:

#define vector with some zeros and negative numbers x <- c(4, 8, 9, 9, 12, 14, 17, 0, -4) #calculate geometric mean of values in vector exp(mean(log(x[x>0]))) [1] 9.579479

**Example 3: Calculate Geometric Mean of Columns in Data Frame**

The following code shows how to calculate the geometric mean of a column in a data frame:

#define data frame df <- data.frame(a=c(1, 3, 4, 6, 8, 8, 9), b=c(7, 8, 8, 7, 13, 14, 16), c=c(11, 13, 13, 18, 19, 19, 22), d=c(4, 8, 9, 9, 12, 14, 17)) #calculate geometric mean of values in column 'a' exp(mean(log(df$a))) [1] 4.567508

And the following code shows how to calculate the geometric mean of multiple columns in a data frame:

#define data frame df <- data.frame(a=c(1, 3, 4, 6, 8, 8, 9), b=c(7, 8, 8, 7, 13, 14, 16), c=c(11, 13, 13, 18, 19, 19, 22), d=c(4, 8, 9, 9, 12, 14, 17)) #calculate geometric mean of values in column 'a', 'b', and 'd' apply(df[ , c('a', 'b', 'd')], 2, function(x) exp(mean(log(x)))) a b d 4.567508 9.871128 9.579479

**Additional Resources**

How to Calculate the Mean by Group in R

How to Calculate a Weighted Mean in R

How to Calculate Standard Error of Mean in R