Vertical Bar Charts: Examples, Types, Best Practices, and How to Build One

Vertical bar charts are a clear and effective way to compare values across categories. Their design makes it easy for viewers to understand comparisons and rankings, making them a staple in reports and data visualizations.

This guide covers vertical bar charts from their definition and use cases to mechanics, design tips, variations, examples, how to build them, and limitations. Use it to gain a clear, practical understanding of when and how to use this essential chart.

What is a vertical bar chart?

A vertical bar chart, also known as a column chart, is a tool for visualizing data by using rectangular vertical bars to represent and compare values across different categories. The length (or height) of each bar is proportional to the value it represents. These bars extend upward from a common zero baseline, making it easy to quickly compare values.

The main function of vertical bar charts is to display categorical data. The horizontal x-axis shows the discrete categories being compared, while the vertical y-axis represents the measured value. This structure allows you to see at a glance which category has the largest value, which has the smallest, and the relative difference between them.

How does it differ from a horizontal bar chart? The primary difference is orientation. A vertical bar chart plots categories along the horizontal axis and values along the vertical axis. A horizontal bar chart flips this, placing categories on the vertical axis and values on the horizontal axis. 

While they serve a similar purpose, horizontal bar charts are generally preferred when you have long category labels that would be difficult to read if placed on a horizontal axis. We’ll dive deeper into this comparison later.

When to use a vertical bar chart (and why)

Selecting the right chart type is key for clear data communication. Vertical bar charts excel when comparing values across categories, ranking items, or showing changes over time in discrete intervals. Use them for maximum clarity and impact in these scenarios.

Best use cases

• Comparing values across categories: This is the most common and powerful use of a vertical bar chart. Whether you are comparing sales figures for different products, website traffic from various marketing channels, or population sizes of several cities, a vertical bar chart makes these comparisons easy to see. The shared baseline allows for quick and accurate judgment of which bar is taller.
• Ranking items from lowest to highest: By arranging the bars in ascending or descending order, you can create a clear ranking. This is useful for showing performance leaderboards, such as top-selling products or most effective sales representatives. The visual hierarchy immediately draws attention to the extremes and the relative positions of everything in between.
• Showing changes across discrete time periods: When you want to show changes over time for distinct, non-continuous intervals like days, months, quarters, or years, a vertical bar chart is an excellent choice. For example, you could plot monthly revenue for the last year. Each month is a separate category, and the bar height shows the revenue for that period. This helps identify patterns, seasonality, or growth over time.

Advantages of using vertical bar charts

Vertical bar charts are intuitive and widely understood, making them an effective choice for clear comparisons. The shared zero baseline allows accurate judgment of bar lengths, reducing the risk of visual distortion seen in other chart types.

When not to use a vertical bar chart

While valuable, vertical bar charts aren’t always suitable.

• Long category labels: If your category names are long, they can become cluttered and unreadable when crammed along the horizontal axis. They might have to be abbreviated or rotated, which compromises readability. In these cases, a horizontal bar chart is a much better alternative.
• Too many categories: As the number of categories increases, the bars become thinner and more crowded, making the chart difficult to read. A general rule of thumb is to avoid using more than 10 to 12 categories in a single vertical bar chart. If you have more, consider a different chart type or grouping the categories.
• Precise trend analysis over continuous time: While vertical bar charts can show changes over discrete time periods, a line chart is superior for visualizing trends over continuous time. A line chart’s continuous line emphasizes the flow and rate of change between data points more effectively than a series of separate bars.

How vertical bar charts work

A vertical bar chart’s strength is in its straightforward structure. With categories on one axis and values on the other, it makes comparisons easy to see at a glance. Bars that are all the same width and clear axis labels ensure information is presented accurately and is easy to understand.

Key elements of a vertical bar chart

Axes

Every vertical bar chart is founded on two axes:

• The horizontal axis (or x-axis) displays the discrete categories you are comparing. These could be anything from product names and geographic regions to survey responses. 
• The vertical axis (or y-axis) represents the quantitative value for each category. This axis is marked with a numerical scale that indicates the measurement unit, such as dollars, percentages, or visitor counts.

Bars

Each category on the x-axis has a corresponding vertical bar. The height of this bar aligns with its value on the y-axis, and all bars start from a common baseline, which is usually set to zero. This shared starting point is critical because it allows people to accurately compare the bar lengths. Starting the baseline at a higher value would exaggerate the differences between the bars and mislead the viewer.

Bar width spacing

To keep comparisons clear and fair, the bar width and the spacing between them should be uniform. While bar width doesn’t encode any data—it’s purely aesthetic—using consistent widths keeps the viewer focused on the height of the bars. The space between bars helps to distinguish one category from another. Generally, the space between bars should be about half the width of a single bar.

Labeling

Finally, clear labeling is essential. Both the x-axis and y-axis should have descriptive titles that explain what’s being measured. The scale on the y-axis should have clear tick marks and labels at regular intervals so the viewer can gauge the values accurately. Without proper labeling, a chart is just a collection of shapes with no meaning.

Types and variants

Vertical bar charts come in several variations, each suited for different data needs. Understanding these types enables you to select the most effective option for clear and meaningful visualization.

Simple vertical bar chart

This is the standard form we have been discussing, featuring a single data series where each bar represents the value for one category. It’s perfect for straightforward comparisons, like showing the number of employees in different company departments.

Grouped vertical bar chart

A grouped vertical bar chart, also known as a clustered bar chart, is used to compare values across two categorical variables. For each primary category on the x-axis, there are multiple bars clustered together, with each bar in the cluster representing a sub-category. 

For example, you could compare quarterly sales figures for two different products. The x-axis would show the quarters (Q1, Q2, Q3, Q4), and for each quarter, there would be two bars side by side: one for Product A and one for Product B. This format is excellent for comparing the sub-categories within each primary category and observing how their relationship changes.

Stacked vertical bar chart

A stacked vertical bar chart is used to show how a larger category is divided into smaller subcategories and what the total value is for each larger category. Each bar represents a primary category, and the bar is segmented into parts that represent the values of its subcategories. The total height of the bar shows the total value for that category. 

For instance, you could show total annual sales for several regions, with each regional bar stacked to show the contribution of different product lines. This chart type is useful for part-to-whole analysis but can make it difficult to compare the individual segments across different bars, except for the bottom-most segment which shares a common baseline.

The 100% stacked vertical bar chart

Similar to a stacked bar chart, the 100% stacked version also shows part-to-whole relationships. However, instead of the y-axis representing an absolute value, it represents a percentage from 0% to 100%. All the bars are the same height (100%), and the segments within each bar show the relative proportion of each sub-category. 

This format is ideal when you want to compare the percentage composition of different categories, rather than their total values. For example, you could use it to compare the market share of different competitors across several years, showing how the proportions shift over time.

Design best practices and pitfalls

A well-designed vertical bar chart is clear, accurate, and easy to read. To create effective charts, follow these best practices.

• Start the y-axis at zero: This is the golden rule of bar charts. Truncating the y-axis by starting it at a value other than zero distorts the visual proportions of the bars and misrepresents the data. A small difference can look like a massive one, leading to incorrect conclusions.
• Keep bar widths consistent: The width of the bars carries no data value, so all bars should have the same width. Varying the widths can distract the viewer and imply a meaning that doesn’t exist.
• Limit the number of categories: To maintain readability, avoid overloading your chart with too many bars. If you have more than 10 or 12 categories, the bars will become too thin and the labels too crowded. Consider grouping smaller categories into an “Other” category or choosing a different chart type.
• Use color sparingly: Color should be used purposefully, not for decoration. Use a single color for all bars unless you want to highlight a specific category. You can use a contrasting color to draw attention to a key data point, like the bar representing your company’s performance vs competitors.
• Avoid unnecessary gridlines and effects: Clutter is the enemy of clarity. Faint gridlines can help viewers trace bar heights to the y-axis, but heavy or dark gridlines can be distracting. Avoid 3D effects, shadows, and other decorative elements that add no informational value and can make the chart harder to read.
• Sort bars intentionally: If your categories have no natural order, consider sorting the bars by value, either in ascending or descending order. This creates a clean visual progression and makes it easier for viewers to see rankings and compare values.

Examples and storytelling tips

A chart is more than just a picture of data. It’s a tool to highlight what you’ve learned. By using effective techniques and making deliberate choice, such as selecting the right chart type, sorting data effectively, and highlighting key elements, you can direct your audience to the most important findings.

Example 1: Sales by product category

Imagine you are presenting monthly sales figures for five product categories. A simple vertical bar chart can quickly show which category is performing best and which is lagging. To enhance the story, you could sort the bars from highest to lowest sales, immediately creating a performance ranking. Now the message is obvious without any explanation: the best-selling category is on the left, and the weakest is on the right. You can also focus the discussion by using colors to highlight the top-performing category or the category you want to discuss further.

Example 2: Website traffic by channel

Suppose you want to show where your website traffic comes from: Organic Search, Social Media, Direct, Referral, and Paid Ads. A vertical bar chart makes it easy to compare the volume from each channel. To tell a story, you could use a grouped bar chart to compare this month’s traffic to last month’s for each channel, revealing growth or decline. Now each channel shows not just size, but direction: up or down. By adding an annotation, you could point out a significant spike in social media traffic and explain it was due to a successful campaign. The chart now gives a complete, concrete story: where traffic comes from, what changed, and why one channel stands out.

Storytelling tips

• Call out the highest and lowest values: Your audience will naturally look for the extremes. Make their job easier by explicitly mentioning the highest and lowest points and what they signify.
• Use annotations for key insights: A short text box pointing to a specific bar can provide context that the data alone can’t. For example, you might add a note like, “New product launch” next to a bar showing a sales spike.
• Highlight outliers without clutter: If one data point is particularly important or unexpected, make it stand out. Changing its color is an effective way to do this without adding visual noise.

How to create a vertical bar chart

Creating a vertical bar chart is simple in most spreadsheet and business intelligence tools. Here is how to do it:

Data preparation

First, you have to organize your data. You’ll need at least two columns: one for your categorical data (like “Product A” or “Product B”) and one for your numerical data (like “Sales”). Make sure your data is clean, with no missing values or inconsistencies in naming.

Steps in spreadsheets or BI tools

1. Select your data: Highlight the columns containing your categories and values.
2. Insert the chart: Go to the “Insert” menu and choose “Chart” as an option. Select the vertical bar chart (often called a column chart) option. The software will generate a basic chart for you.
3. Assign axes correctly: Most tools will automatically assign the categories to the x-axis and values to the y-axis. If not, you may need to go into the chart editor to assign the correct data to each axis.
4. Format and customize: Now you can refine your chart. Add a clear title, label your axes, and adjust the colors to match your brand or highlight key information. Check that the y-axis starts at zero. You can also format the numbers on the y-axis (e.g., as currency or percentages) and adjust the spacing between bars.

For more complex charts like grouped or stacked bars, your data set will need additional columns. For a grouped bar chart, you’ll need a category column and separate value columns for each sub-group. For a stacked bar chart, you’ll need a category column and value columns for each segment of the stack. The creation process remains largely the same: select all the relevant data and choose the appropriate chart type.

Limitations and when to use alternatives

Vertical bar charts aren’t always ideal. They struggle with long labels or too many categories, becoming crowded and hard to read. In these cases, other chart types may be a better fit.

• Long labels or many categories: As mentioned earlier, vertical bar charts aren’t ideal for a large number of categories or categories with long names. The horizontal axis becomes too crowded, making the labels illegible.
• Hard to read when bars are packed: When you have many bars, they become very thin, which can make it difficult to compare their heights accurately.

Alternatives to consider

• Horizontal bar charts: These are the perfect alternative when you have long category labels. The vertical orientation gives you plenty of space to write out each label clearly. They are also effective for a larger number of categories than vertical bar charts.
• Line charts: When you want to show a trend over continuous time, a line chart is the superior choice. The connecting line emphasizes the rate of change and flow of the data over time, which is something a bar chart can’t do as effectively.
• Dot plots: If you want to make very precise comparisons between values, a dot plot can be more effective than a bar chart. A dot plot uses a dot for each value on a single scale, which can make it easier to see small differences, especially when the values are very close.

Conclusion and key takeaways

Vertical bar charts provide straightforward category comparisons and clear insights for any audience. By following essential design principles, you can use them to communicate data effectively and accurately.

Always start your value axis at zero, keep the design simple, and sort data logically. Vertical bar charts excel at clear, quick category comparisons, making them a top choice for reports and presentations when you want to deliver information efficiently.

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