How to Create a Column Chart
A column chart is used to compare values across categories, displaying data as vertical bars.
Overview
In this tutorial, we’ll learn how to create a column chart in R using the ggplot2 package. Here’s a brief overview of what we’ll cover:
How to create a column chart 
Step 1: Create a base layer
Start with the
ggplot function and specify the data frame. Step 2: Add aesthetics
Use the
aes function to map the variables (x and y axes). Step 3: Add geometric objects
Use
geom_col() to create the column chart. Step 4: Format axes
Adjust the x and y axes for better readability.
Step 5: Add labels and titles
Add alt text, title, subtitle, and caption to the plot.
Step 6: Apply a theme and format text
Use a minimal theme and customize text appearance.
Step 7: Add color
Customize the color of the columns and make final adjustments.
Getting started
We’ll use the candy dataset throughout this tutorial. Here’s how the dataset looks:
| name | sales | price | rating | year | category |
|---|---|---|---|---|---|
| Jelly Beans | 300 | 2.5 | 4.5 | 2019 | Chewy |
| Gummy Bears | 150 | 1.5 | 3.8 | 2020 | Chewy |
| Lollipop | 200 | 1 | 4 | 2021 | Hard |
| Cotton Candy | 100 | 2 | 4.2 | 2022 | Soft |
| Jolly Ranchers | 250 | 1.8 | 4.7 | 2023 | Hard |
| Marshmallow | 180 | 1.2 | 3.5 | 2024 | Soft |
To view the code to create the candy dataset, click the button below:
What we’ll create
We’ll create a column chart that shows the rating of candy over the years.
Column chart of candy ratings over the years
Steps to create a column chart
Let’s go through the process of creating this column chart step by step.
Step 1: Start a ggplot and specify the data
ggplot(candy) 
Step 2: Add aesthetics
ggplot(candy) +
aes(x = year, y = rating) 
Step 3: Add geometric objects
ggplot(candy) +
aes(x = year, y = rating) +
geom_col() 
Exercise 3.1
Try running the code below to see a column chart with the ratings of candy over the years:
Exercise 3.2
Change the y-axis to sales to create a column chart showing sales over the years.
Step 4: Format axes
Now, let’s improve our column chart by formatting the axes, adding labels, and applying a theme.
We’ll use scale_x_continuous() and scale_y_continuous() to adjust the axes.
The breaks argument in scale_x_continuous() specifies the tick marks on the x-axis, while the limits argument in scale_y_continuous() sets the range of the y-axis.
The position argument in scale_y_continuous() moves the y-axis to the right side.
ggplot(candy) +
aes(x = year, y = rating) +
geom_col() +
scale_x_continuous(breaks = 2019:2024) +
scale_y_continuous(limits = c(0, 5), position = "right") 
Step 5: Add labels and titles
ggplot(candy) +
aes(x = year, y = rating) +
geom_col() +
scale_x_continuous(breaks = 2019:2024) +
scale_y_continuous(limits = c(0, 5), position = "right") +
labs(alt = "Column chart of year and rating",
title = "Candy ratings over the years",
subtitle = "Ratings (1 - 5)",
caption = "Source: The School of Data",
x = NULL, y = NULL) +
theme(plot.title.position = "plot") 
Step 6: Apply a theme and format text
ggplot(candy) +
aes(x = year, y = rating) +
geom_col() +
scale_x_continuous(breaks = 2019:2024) +
scale_y_continuous(limits = c(0, 5), position = "right") +
labs(alt = "Column chart of year and rating",
title = "Candy ratings over the years",
subtitle = "Ratings (1 - 5)",
caption = "Source: The School of Data",
x = NULL, y = NULL) +
theme_minimal() +
theme(text = element_text(family = "PT Sans"),
panel.grid.major.x = element_blank(),
panel.grid.minor.x = element_blank(),
plot.title.position = "plot",
plot.title = element_text(face = "bold", size = 16),
plot.subtitle = element_text(face = "italic", 12),
axis.text.y = element_text(size = 12)) 
Step 7: Add color
Finally, let’s add color to our column chart.
ggplot(candy) +
aes(x = year, y = rating) +
geom_col(fill = "rosybrown") +
scale_x_continuous(breaks = 2019:2024) +
scale_y_continuous(limits = c(0, 5), position = "right") +
labs(alt = "Column chart of year and rating",
title = "Candy ratings over the years",
subtitle = "Ratings (1 - 5)",
caption = "Source: The School of Data",
x = NULL, y = NULL) +
theme_minimal() +
theme(text = element_text(family = "PT Sans"),
panel.grid.major.x = element_blank(),
panel.grid.minor.x = element_blank(),
plot.title.position = "plot",
plot.caption.position = "plot",
plot.title = element_text(face = "bold", size = 16),
plot.subtitle = element_text(face = "italic", 12),
axis.text = element_text(size = 12)) Exercise 3.3
Let’s create a column chart showing the price of candy over the years. Use the code below as a starting point and make the following changes:
- Change the y-axis to
price - Update the title and subtitle to reflect the new data
- Adjust the y-axis limits to fit the price data (hint: use
limits = c(0, 3)) - Change the fill color to “skyblue”
Quiz
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Review
In this tutorial, we learned how to create a column chart in R using the ggplot2 package. We covered the following steps:
Step 1: Start a ggplot and specify the data frame.
Step 2: Add aesthetics using the aes function.
Step 3: Add geometric objects using geom_col() .
Step 4: Format the axes using scale_x_continuous() and scale_y_continuous() .
Step 5: Add labels and titles using labs() .
Step 6: Apply a theme and format text using theme() .
Step 7: Add color to the chart using the fill argument in geom_col() .
In the next section, we’ll create a line graph in R. Let’s continue learning!