What Is a Bar Chart?

Written by Coursera Staff • Updated on

This vital data analysis tool has various use cases across multiple industries. Explore the different types of bar charts and their uses, the pros and cons of bar charts and graphs, and the steps you can take to learn more about working with them.

[Featured Image] A business professional removes their glasses to examine a bar chart on a laptop.

Key takeaways

A bar chart is a data visualization tool that can help showcase or summarize the content within your data set in a visual form. 

  • Depending on your specific data set, you can use a bar graph or chart to represent numbers or percentages.

  • The two main types of bar charts are horizontal and vertical. 

Discover what a bar chart is, how it differs from a histogram, its various types, applications, and more. If you’re ready to explore data visualization tools right away, consider enrolling in IBM’s Data Analysis and Visualization Foundations Specialization. You’ll have the opportunity to learn how to create various types of charts and plots in Excel as well as work with Cognos Analytics to generate interactive dashboards.

What is a bar chart? 

Bar charts, sometimes called “bar graphs,” are among the most common data visualizations. It’s a helpful tool that showcases or summarizes the content within your data set in a visual form. In turn, using it empowers your audience to understand the insights and ideas suggested by the data. 

Bar charts use one quantitative measure, expressed as a number, and a qualitative measure, known as the categorical variable or label. This variable represents each category or subcategory receiving a numeric amount. These two types of measures go on opposite axes on the graph.

For example, your qualitative measure or label may be every shirt size that a clothing store sells (small, medium, and large), and your quantitative measure is how many shirts of each size the store has sold. To effectively utilize bar charts to showcase important data, you may find it helpful to understand the different types of bar charts, their various uses, their pros and cons, and how you can start learning more about creating them. 

Read more: 5 Types of Data Visualization

Histogram vs. bar chart

Histograms and bar charts look similar, but whereas a bar chart demonstrates qualitative or numerical values, a histogram demonstrates how those values are distributed. For example, if you taught a class of students, you could create a bar chart to visualize students' exam scores, where each student had a corresponding rectangle marking their total score. Or, you could create a histogram of scores that visualizes how many students scored 100 percent, how many scored 90 percent, and so on. 

Types of bar charts

In general, bar charts exist in two standard forms: horizontal and vertical. However, other variations exist. Each subset of bar charts has nuances and differs in the type of data best suits it.

Vertical bar chart

In a vertical bar chart, the x-axis serves as the beginning point for the bars. Vertical bar charts are typically the default and a basic option. You might also see this type of graph called a column chart. 

Horizontal bar chart

Opposite to a vertical bar chart, the horizontal bar chart has the starting point for the bars on the y-axis. These types of charts prove useful when the names of your categories are lengthy because the horizontal setup allows for the full names to fit in place and not squeeze in at the bottom, below the x-axis.

Clustered bar chart

Multiple series of data appear in clustered bar charts. It’s critical to lay this type of chart out in an organized fashion to make it easy to read and understand. Clustered bars can be designed with a horizontal or vertical layout. An example of this type of chart could be a graph showing the number of apples and oranges each of your friends has. One axis would have the names of your friends, and two different bars, one for apples and one for oranges, would appear for each name, representing the number of fruits they possess. 

Stacked bar chart

Similar to clustered bars, stacked bar charts can be vertical or horizontal. These types of charts stack multiple subcategories on top of each other, creating one large bar representing the entire category. Taking our clustered bars example, a stacked bar could use the same data, but the bars for apples and oranges would connect to each other, creating one long bar for each name. 

100 percent stacked bar chart

Like the standard stacked bar chart, the 100 percent stacked variation showcases the relative percentage of a data grouping rather than the total amount. This type of graph creates two consistent end lines, on the left and right, enabling you to compare and contrast the data based on how much of each side fills in. 

For example, if data grouping includes three groups of students and their preference for chocolate or vanilla ice cream, each of the three bars would have an equivalent total length. However, the percentage of the bar colored brown for chocolate and white for vanilla would vary based on the relative percentage of each option for each group of students. 

Waterfall bar chart

The waterfall variation of the bar chart is more complex and less common than the others. This graph's first and last bars represent the starting and ending points for some data grouping. All of the bars in between the start and end showcase the change as time progresses. The bars in the middle are visually smaller in length because they do not represent the total value but rather the amount that a value has fluctuated. 

For example, a waterfall bar chart can represent your bank account from the beginning of the month to the end. The first bar shows your starting balance on the first of the month. Then, each bar in between would represent some fluctuations to your total, such as receiving a paycheck, paying your credit card, and depositing cash into your account. The last bar considers the sum of all the changes and represents your final balance at the end of the month.

What is a bar chart used for?

Bar charts are helpful in many situations, including those that call for analyzing or graphing categorical data. Bar charts are simple to understand and process for audiences. In any situation where data is split into multiple groups, a bar chart may be an excellent way to represent it visually. 

Depending on your specific data set, you can use a bar graph or chart to represent numbers or percentages. Larger numerical values appear as longer bars within the graph to create a simple comparison between the frequency of data within each grouping. When creating a bar chart, the base or beginning value of each bar should start at zero, and the width of each bar should remain consistent. Doing so allows an interpreter of your chart to compare the lengths of the bars to one another to extract insights.

Bar charts can showcase data and its fluctuations over a set period. For example, each category or grouping is a year, month, or day. As mentioned, the qualitative variable resides on either the y-axis or x-axis, and the quantitative variable, or numeric variable, goes on the other, allowing the chart to reflect any patterns or relationships between the two variables. 

Who uses bar charts?

Various industries and professions rely on bar charts as a means to visualize data for sales, investments, forecasts, and company budgets. 

Professionals within the business and financial industries often utilize bar charts for multiple purposes to succinctly showcase complex information and data. For example, a volume chart can depict fluctuations in trading volume over time. Due to the complexity of the data these industries deal with and the need to pass along information clearly and as fast as possible, bar charts provide an excellent option to simplify the data and make it easier to understand.

Bar charts appear in medical contexts, depicting one isolated variable and multiple categories or groupings. These groupings may represent different subsets of patients in a hospital, and the variable could be the overall concentration of some substance present in the body, for example.

Bar charts appear in many other professional contexts, as well. A small business owner can use a bar chart to break down their monthly costs. A brick-and-mortar store may create multiple bar graphs to analyze the sales it receives within each department over the course of a calendar year. 

Pros and cons of using bar charts

Bar charts enable professionals to showcase data in an appealing visual format when created correctly. However, the pros and cons of using bar charts may help you learn these factors.

Pros of using bar charts

The pros of bar charts for data visualization include:

  • Easily understood by diverse audiences

  • Users can quickly compare groupings of data by the height of each bar.

  • Shows the main trends within a set of data clearly.

  • Tracks the fluctuations in a data set through time.

  • Takes large data sets and makes the information easier to understand.

Cons of using bar charts

The cons of bar charts as a data visualization include:

  • Additional commentary may be necessary to explain patterns seen within the data fully

  • Audiences may misinterpret the data shown in a bar chart.

  • Including too many bars could lead to the bar chart becoming overcrowded.

  • Confusion may result from not properly sorting the groupings of data.

  • The causation of a trend or pattern in a set of data is not evident.

How to get started with learning about bar charts

Beginning to utilize bar charts in your profession may help you identify the tools you can use to build them, the best practices to keep in mind, and any common mistakes related to utilizing this visual. 

Tools for creating bar charts

In general, any visualization tool or software you use to build graphs from a data set should have a built-in capability to construct bar charts. Common types of tools include spreadsheets, such as Microsoft Excel, Google Sheets, and Airtable, and business intelligence (BI) tools. While many popular BI tools exist in the marketplace today, Power BI and Tableau are popular among many professionals.

Many programming libraries can create bar charts. Many programming languages allow you to create data visualizations, but Python is one of the most popular and frequently used in data science. Common programming libraries in Python for data science are Matplotlib, seaborn, and Plotly. 

Best practices for creating bar charts

Following best practices ensures that your visualizations are coherent and well-received by your audience. A few best practices to keep in mind include:

Remain consistent with setting the baseline for your quantities at zero. Doing this lets your audience compare and contrast each bar quickly and efficiently. If starting with another number, label the axis clearly.

Place your bars in order based on their represented quantity. For example, if you are creating a bar graph to show the population of each state in the US, placing each state in order from largest to smallest population allows your audience to interpret the graph and understand the overall trend quickly. 

Always make the bars on your graph rectangular in shape rather than using rounded edges. Additionally, be conscious about your use of color and make any changes to the colors of the bars. Since varied colors could capture your viewer's attention, only use them to highlight key information related to the main trend you aim to showcase. 

Check out our free resources on data visualization

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