Stacked Area Chart: Examples, Best Practices, How to Create

A stacked area chart shows how a total changes over time while revealing how different categories contribute to that total. This guide covers when to use this chart type, how to read it correctly, common mistakes to avoid, and step-by-step instructions for building one in Excel.

Key findings about stacked area charts

A stacked area chart is a visualization that shows how a total changes over time while revealing how different categories contribute to that total. The bottom category sits on a fixed baseline, and each additional category stacks on top, creating colored bands. The top line represents the cumulative sum of all categories.

• Use this chart when: You need to track total volume over time while seeing which categories drive that total, like monitoring website traffic by source.
• Avoid this chart when: You need to compare exact values between categories that are not at the bottom of the stack.
• Primary decision it supports: Determining whether total volume is growing or shrinking and which broad categories are responsible.
• Most common misuse: Assuming a middle band grew because it looks thicker, when the band below it actually shrank.
• If you only remember one risk: The moving baseline makes it nearly impossible to judge individual category trends for any series not at the bottom.
• Best alternative if this fails: Use a line chart when precise category-to-category comparison matters more than seeing the cumulative total.

What is a stacked area chart?

A stacked area chart plots multiple data series as colored bands stacked vertically along a time axis. The bottom series sits directly on the x-axis, giving it a fixed baseline. Each additional series uses the top of the previous series as its starting point. The topmost boundary line shows the cumulative sum of all categories at each time point.

Think of it like stacking blocks. If Product A sells 30 units, its band stretches from 0 to 30. Product B sells 20 units, so its band sits on top, stretching from 30 to 50. Product C sells 10 units, stretching from 50 to 60. The top line sits at 60, showing total sales.

This structure differs from a basic area chart, which plots only a single series. It also differs from a line chart, which does not fill the space below the data points. The filled areas create a visual impression of volume and accumulation that lines alone cannot convey.

Data requirements for stacked area charts

Before building this chart, confirm your data fits the structural requirements. If it does not, the visualization will be mathematically incorrect.

Your data needs three elements: a time column (dates, months, quarters), a categorical dimension (product line, channel, region), and a numeric measure that is additive and non-negative (revenue, units, visits). You should have at least three time points to show a trend and at least two categories to justify stacking. Try to keep it to five to seven categories. Beyond that, the chart gets cluttered.

Watch for these boundary conditions where the chart renders but should not be trusted:

• Negative values: Stacking breaks when any number falls below zero. Bands will overlap or invert.
• Non-additive metrics: You cannot stack profit margins, bounce rates, or averages. Summing a 10 percent margin and a 20 percent margin to get 30 percent is meaningless.
• Missing data points: Gaps create misleading drops. Decide whether to interpolate or treat gaps as zeros.
• Wildly different magnitudes: If one category is in the millions and another in the hundreds, the smaller category becomes an invisible sliver.

If your data includes negatives or non-additive metrics, use a line chart instead.

When to use a stacked area chart

This chart fits when your primary question is about total volume over time and you also care about how categories contribute to that total. It works well for tracking total website traffic while seeing organic, paid, and referral sources. It also helps when showing how the mix of revenue sources shifts quarter over quarter.

The chart excels when the total trend line is the headline and category-level precision is secondary. Your data must be additive and non-negative, meaning all categories use the same unit and can be summed meaningfully.

When not to use a stacked area chart

The most common failure happens when someone misinterprets the moving baseline. A dashboard might show marketing spend by channel. The chief marketing officer (CMO) concludes that email marketing doubled because the band looks twice as thick. In reality, paid search below it dropped, pushing the email baseline down and distorting the visual.

Avoid this chart when comparing exact values between non-bottom categories. The moving baseline makes it nearly impossible to judge whether a middle band grew, shrank, or stayed flat. Also avoid it when you have more than seven categories, when categories frequently cross over in rank, or when negative values exist.

If you choose it, plan for questions. Gartner's CDAO Survey lists poor data literacy as a top-5 barrier to analytics success, and people often misread the moving baseline, so you may spend time clarifying the chart before you get to the business decision.

To mitigate these risks, limit categories to five to seven. Beyond that, bands become too thin to distinguish. Group smaller categories into an "Other" bucket. Place the most important or most stable category at the bottom where the baseline is fixed. Add a separate line chart as a companion view for precise comparison.

How to read a stacked area chart

Reading this chart requires a specific approach to avoid optical illusions.

Start by reading the top line first. It shows the cumulative total at each time point and is the most reliable trend in the chart. Ask yourself if the total is growing, shrinking, or staying flat.

Next, assess band thickness rather than position. For any category, the value at a given time point equals the vertical distance between its top and bottom boundaries. A band that appears higher is not necessarily larger; it is just stacked on top of larger categories.

Trust the bottom band most. It has a fixed baseline on the x-axis, so its trend is accurate. For all other bands, the baseline moves, making trend comparisons unreliable.

Watch for visual illusions. If a middle band looks like it grew, check whether the band below it shrank. The apparent growth may be an artifact of the shifting baseline rather than actual performance.

Stacked area chart variations

Standard stacked area chart

This is the default version. Bands show absolute values, and the top line shows the cumulative total. Use it when both absolute volume and category contribution matter. The tradeoff is that you see totals clearly but sacrifice precision for non-bottom categories.

100% stacked area chart

In this version, each time point is normalized to 100 percent. The top line is always flat. Bands show each category's share of the total rather than its absolute value.

Use this when the question is purely about composition, such as what percentage of traffic comes from mobile versus desktop. The tradeoff is that you cannot see whether the total grew or shrank. A category's band can shrink even if its absolute value doubled, simply because other categories grew faster.

Streamgraph

A streamgraph uses a wiggling, centered baseline instead of a fixed x-axis. The result looks like a flowing river. Some people call this a sand chart.

Use this only when aesthetics and general pattern recognition matter more than precise reading, such as in editorial data journalism. The centered baseline makes it even harder to read exact values. Avoid this for business dashboards.

Stacked versus 100% stacked area chart

The choice between these two versions comes down to a tradeoff between seeing absolute values and seeing proportions.

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If you need to report total revenue growth to the board, choose standard stacked. The rising top line is the key message. If you are analyzing market share between competitors, choose 100% stacked. The total market size matters less than who is winning the slice.

Stacked area chart best practices

Place the largest or most stable category at the bottom. This gives your most significant data point a fixed baseline, making its trend readable. If you violate this, your most important category becomes impossible to interpret accurately.

Limit categories to five to seven. Research shows the eye can only process five to seven colors pre-attentively, and beyond that, bands become too thin to distinguish. Group smaller categories into an "Other" bucket.

Order remaining categories consistently. Use a logical order, such as largest to smallest, and keep it consistent across charts. Random ordering creates visual noise.

Use distinct, colorblind-accessible colors. Many widely-used color sequences are not accessible to colorblind individuals, and similar hues make adjacent bands indistinguishable.

Add direct labels when space permits. Legends force the eye to travel back and forth. If bands are wide enough, label them directly.

Validate that values sum correctly before publishing. Pick one time point and manually add the category values. The sum should match the height of the top line.

Stacked area chart examples

Website traffic by source over 12 months

A marketing team tracks total monthly sessions broken down by organic search, paid search, social, and direct traffic. The stacked area chart shows total traffic grew steadily, but the composition shifted. Organic search expanded as a share while paid search stayed flat. A line chart would show each channel's trend but would not communicate the total or the parts-to-whole relationship.

Revenue by product line over quarters

A software as a service (SaaS) company visualizes quarterly revenue from three product tiers: Basic, Pro, and Enterprise. The chart shows total revenue doubled over two years, driven almost entirely by Enterprise growth. Basic and Pro remained flat. A grouped bar chart would show each tier's quarterly value but would require mental math to see the total trend.

Support tickets by category over weeks

A customer success team monitors weekly ticket volume by category: billing, technical, onboarding, and feature requests. The chart shows total ticket volume spiked after a product launch, with technical issues driving the spike. A simple area chart of total tickets would show the spike but not its cause.

How to explain a stacked area chart in 30 seconds

Use this talk track when presenting to stakeholders:

"This chart shows total revenue over time, broken down by product category. The key comparison is how the total changes and which categories contribute most. The main takeaway is that total revenue grew, driven primarily by Enterprise sales. Do not conclude that a middle category grew just because its band looks thicker. The baseline shifts, so only the bottom category's trend is fully reliable. If we need to answer which specific category grew the most, we should use a line chart instead."

How to create a stacked area chart in Excel

Your data needs a time column in Column A and one column per category with numeric values in Columns B, C, and D.

1. Open your data in Excel and ensure the time column is in Column A.
2. Select the entire data range including headers.
3. Navigate to Insert, then Charts, then Area, then Stacked Area.
4. Verify the legend matches your category columns and the x-axis shows your time periods.
5. Right-click the chart and select Select Data to confirm the series order. The series listed first will appear at the bottom.
6. Format the chart by setting the y-axis minimum to zero and adjusting colors for accessibility.
7. Validate by picking one time point and manually adding the category values. The sum should match the top line height.

A common mistake is including a Total column in your data selection. Excel will stack the total on top of the categories, doubling the values. Always exclude any total column.

Excel can add a total line and re-order series, but it usually takes a few extra steps. If you need interactive dashboards with filters and drill-downs, a BI tool such as Domo can be easier to maintain.

Stacked area chart checklist

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For any month, add the three product values. The sum should equal the height of the top line. For January: 100 plus 50 plus 30 equals 180.

This chart should show total revenue growing from 180 to 215 over three months, with Product A contributing the largest share.

Watch for this misleading pattern: Product B's band may appear to grow between February and March because Product C shrank below it. Check the actual values before drawing conclusions.

Limitations of stacked area charts and alternatives

The moving baseline problem is the primary limitation. Only the bottom category has a fixed reference. All other categories stack on shifting baselines, making their individual trends unreliable.

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If you need to compare the exact growth rate of five different sales regions, choose a line chart. If you have 15 different product categories, choose small multiples. If your data includes negative profit margins, choose a line chart because it handles negative values naturally.

How stacked area charts change decisions

Allocating budget across categories becomes easier when total spend is capped. The chart shows which categories are growing their share, helping you decide where to shift resources.

Determining whether a specific category's absolute performance improved becomes harder. The moving baseline obscures individual trends, making it risky to base category-specific investments on this chart alone.

Teams often overcorrect after seeing one category's band shrink. They cut investment without checking whether the shrinkage was relative or absolute.

This chart tempts teams to ask whether Category X outperformed Category Y. It cannot reliably answer that question. Use a line chart or bar chart instead.

Final thoughts

A stacked area chart shows how a total changes over time while revealing how categories contribute to that total. It excels when the cumulative trend is the primary story and category-level precision is secondary.

Choose this chart when you have additive, non-negative data with a limited number of categories. Avoid it when precise category-to-category comparison matters or when negative values exist.

Before building, validate that your data fits the requirements. After building, sanity-check that values sum correctly. When presenting, guide your audience through the reading protocol: top line first, band thickness second, and a warning about the moving baseline.

If the stacked area chart does not fit your question, reach for a line chart, small multiples, or a stacked bar chart instead. The right chart makes the right decision obvious—want a second set of eyes (or a few smart shortcuts) before you ship it to stakeholders?