Stacked Bar Chart

A stacked bar chart visually compares multiple variables over time using horizontal bars. These are stacked upon one another, commonly used to showcase total value comparisons across various categories.

A stacked bar chart showing population forecast of Africa by region 1953-2098

When to use a Stacked Bar Chart?

Plotting total purchase value against basic demographics like age reveals clusters. This enables the creation of precise user personas for targeted marketing and personalized engagement strategies.

Digital marketers can use a stacked bar graph to visualize website traffic sources (direct, socials, search engines). It helps understand each source’s contribution and focus efforts on high-performing channels for optimized traffic generation.

Education researchers can use a stacked bar graph to examine the distribution of resources (such as funding, staffing, or technology) across schools or districts. This helps identify disparities in student resource allocation. 

Project managers can use splitted stacked charts to visually represent various tasks’ progress. This enables effective communication with project heads, streamlines status checks, and ensures timely task completion to meet project deadlines.

Economists and policymakers can use stacked bar charts to represent the distribution of demographics like population within a region. This helps inform economic policies and marketing strategies, enhancing economic analysis and decision-making. 

Tips & Tricks

Maximize the potential of stacked bar charts to reveal the complete narrative of your data with our expert insights. Let your data tell its story with precision and impact.

Ensure clear visualization: Keep the design of stacked bar charts simple by limiting the number of categories and segments. This ensures the chart is not overly cluttered and makes it easier for viewers to understand the data presented. Too many categories or segments can overwhelm viewers and make it difficult to observe meaningful patterns or trends in the data.

Start the x-axis at zero: In a stacked bar chart, each segment’s width reflects its contribution magnitude. The sum of these widths forms the cumulative total. Therefore, starting the x-axis at zero is essential to maintaining the integrity of both the totals and the series aligned with the vertical baseline. Moreover, when the x-axis doesn’t start at zero, it can exaggerate differences between values, leading to data misinterpretation.

Position important series on the y-axis: Place important series or categories on the y-axis to draw attention to specific data points that are relevant or significant. The y-axis provides a consistent baseline for the cumulative totals and the series directly stacked upon it. This setup lets readers precisely grasp values and easily compare heights between the totals and this particular series. As a result, viewers can quickly identify trends or outliers within the data. 

Stack levels consistently: Consistency in stacking levels ensures you represent each segment uniformly across different charts. This improves readability and facilitates comparison between different categories or segments. Inconsistent stacking can lead to confusion among viewers, making it difficult to interpret data presented in the chart accurately.

Choose a strategic order: Analyze your contributing categories to discern a natural order based on size, progression, classification, or significance. Use this order to stack the corresponding series on top of each other. Arranging categories or segments in a logical order is important for highlighting trends and guiding viewers' attention to the most relevant information.

Choose effective colors: While standard bar charts favor using a single color, the nature of a stacked bar chart requires using effective colors to map secondary variable levels. Select a color palette that aligns with the variable type. Qualitative palettes suit purely categorical variables, while sequential or diverging palettes are more suitable for variables with a meaningful order. Use a consistent color scheme across all charts to maintain visual consistency and help viewers associate colors with specific data categories.

Position legends out of the way: Stacked column charts often become visually cluttered. It is advised to position legends either to the left or to the right. Positioning legends outside the main chart area reduces visual clutter and maintains a clean and legible chart area. It helps viewers focus on the data patterns without distraction.

Avoid inappropriate comparison: Stacked bar charts are not suitable for comparing individual segments within a single bar due to potential difficulty in discerning relative sizes. When viewers compare individual segments within a single bar, they may struggle to accurately interpret the data and draw meaningful insights from the chart. It is important to choose appropriate chart types for comparing individual data points to ensure accurate data visualization and interpretation.

Avoid 3D effects: Avoid using 3D bars as they can induce optical illusions or distortions. For instance, some bars may appear longer or shorter than they are, and some may hide behind others. This can affect viewers’ ability to accurately compare and interpret the data. Opt for 2D bars in stacked bar charts for simplicity and transparency.

Use negative values wisely: Use negative values carefully and with a clear explanation to avoid confusion. When negative values are included in a stacked bar chart, it is important to provide context and explain their significance to viewers. Wise use of negative values ensures that viewers accurately understand and interpret the data presented in the chart.

Limit tick marks and gridlines: Minimize the number of tick marks and gridlines in a stacked chart to reduce visual clutter and provide sufficient guidance for reading the data. Excessive tick marks and gridlines can detract from the chart's clarity and make it more difficult for viewers to focus on the data.

Test for accessibility: Ensure stacked chart accessibility for all users when creating stacked bar charts. This involves testing the chart with assistive technologies to ensure compatibility and providing clear labeling and descriptive text for images. Accessibility testing and consideration help ensure the chart is usable by individuals with visual impairments or other disabilities.

Stacked Bar Chart FAQ

How to create a stacked bar chart?

To create a stacked bar chart, you'll first need to organize your data into a structured format. This involves arranging your data into a table with three or more columns. The first column indicates levels of the primary categorical variable, while subsequent columns correspond to levels of the secondary categorical variable. Main cell values denote the length of each sub-bar in the plot. When generating the stacked bar chart, bars are constructed across rows, with each primary bar's total length being the sum across its corresponding row.

How to read a stacked bar chart?

To read a stacked chart, assess the absolute length of each bar by referencing the scale along an axis or a value label. Use grid lines to compare the parts of the stack against one another. Analyze all bars and stacks, observing variations in size to gauge the significance of each component. While it's straightforward to evaluate the lengths of the bottom colored bars on the baseline, the starting points of stacked bars often vary across the chart. This complicates comparisons between components across all categories.

How to add totals to a stacked bar chart?

To add totals into a stacked bar graph, add two data series to the graph. The first acts as a spacer segment, creating distance between the last segment and the total value. It is crucial for clarity if segment labels extend beyond boundaries. The second series contains the total values. Configure spacer segments and total series to be invisible. Position data labels for the total segment at the Inside Base to align with the segment's left side. Adjust the maximum on the horizontal axis to 10-20% more than the highest total value to remove extra space. Consider using a visual legend for improved clarity.

How to create a stacked bar chart in Google Sheets?

To create a stacked bar chart in Google Sheets, organize your data into categories and subcategories in a spreadsheet. Then, select the data to be added to the chart and click on the “Insert” menu. Choose “Chart” from the dropdown menu and select the “Stacked bar chart” from the chart type. Google Sheets will generate the chart based on your selected data. Alternatively, you can use Vizzu, which is a data visualization tool. It lets you import data and customize visualizations. 

How to build a stacked bar chart in Excel?

Building a stacked chart in Excel is similar to creating one in Google Sheets. Organize your data into categories and subcategories in a spreadsheet, select the data range, and navigate to the "Insert" tab. Choose the "Stacked Bar" chart option. It will generate the stacked bar graph based on your data, and you can further customize it using the Chart Tools options.

How to insert a stacked bar chart in PowerPoint?

There are two methods to create a stacked bar chart in PowerPoint. First, if your data is extensive or frequently updated, it's best to use Excel. Create the chart in Excel and then copy and paste it into PowerPoint, ensuring it remains linked to the original Excel file for real-time updates. Alternatively, you can create a chart directly in PowerPoint by clicking Insert > Chart, selecting your desired chart type, replacing the placeholder data with your own, and using the Chart Elements and Chart Styles buttons for customization.

A 100% stacked bar chart displays which distributions?

A 100% stacked bar chart displays the relative proportions of different categories while also showing the distribution of each category as a percentage of the whole. In this type of chart, the total width of each bar represents 100%, and each segment within the bar represents the percentage of that total contributed by a specific subcategory. This allows viewers to easily compare the relative proportions of different categories across the entire dataset.

When to use a clustered stacked bar chart?

You can use a clustered stacked bar chart when you need to compare multiple categories across different groups. It is useful for comparing subcategories within groups and tracking changes over time. You can also use it for highlighting differences between groups and visualizing data values across multiple groups and time periods simultaneously.