# ggplot2: How to Plot Mean Values with geom_bar

`geom_bar()`

is a function in the ggplot2 package which widely used for creating barplots.

Many times you need to visualize the mean of the data using the barplot. The `geom_bar()`

is particularly useful for visualizing
the mean of the data without manually calculating it.

The basic command of `geom_bar()`

to visualize the mean using barplot is:

```
# load package
library(ggplot2)
ggplot(df, aes(group, value)) + geom_bar(stat='summary')
```

By default, the `stat='summary'`

argument in `geom_bar()`

calculates the mean for each group in
the data frame.

The following example demonstrates how to use `geom_bar()`

to visualize the mean using barplot.

## 1 Plot mean values with geom_bar

Create a sample data frame for two groups,

```
# create sample data frame
df <- data.frame(
groups = rep(c("drug", "placebo"), each = 10),
value = c(rnorm(10, mean = 5),
rnorm(10, mean = 12))
)
# view data
head(df)
groups value
1 drug 4.750353
2 drug 2.511782
3 drug 5.547362
4 drug 5.610277
5 drug 3.518247
6 drug 5.725951
```

The data frame `df`

has two groups drug and placebo, and their measured values.

We want to use this data frame to create the barplot with the mean value for each group.

```
# load package
library(ggplot2)
# create barplot
ggplot(data=df, aes(groups, value)) + geom_bar(stat='summary')
```

We have created the barplot using mean values using the `geom_bar()`

function.

Now, let’s calculate the mean for each group and compare it with the barplot.

You can use the built-in `aggregate()`

function in R to calculate the mean of each group in a data frame.

```
# calculate the mean of each group
aggregate(value ~ groups, df, mean)
groups value
1 drug 4.642326
2 placebo 11.995898
```

The mean value of drug and placebo groups are 4.64 and 11..99, respectively. These mean values for each group match to the height of the bars