How to make a bar graph in Excel (and when you need something better)

Bar charts are probably the most common chart in business. Revenue by quarter, signups by channel, support tickets by category — if you're comparing values across categories, a bar chart is almost always the right call.

Excel makes them straightforward to create. This guide walks through the exact steps, covers the different bar chart types and when to use each one, and flags the mistakes that make charts harder to read than they should be.

We'll also cover the point where Excel's charting starts to feel limiting — and what to do about it.

How to make a bar graph in Excel

The whole process takes about two minutes once you know where everything is.

Step 1: Set up your data

Your data needs two things: a column of categories and a column of values. If you're comparing multiple series (like revenue across regions for multiple years), add one column per series.

Keep headers in the first row. Excel uses them as labels automatically. Avoid merged cells, blank rows, or subtotal rows in the middle of your range — they confuse the chart engine and produce unexpected results.

One thing worth noting: your categories should be text, not numbers. If your categories are numeric (like year values), Excel may treat them as data points instead of labels. Formatting the category column as Text before creating the chart avoids this.

Step 2: Select your data range

Click and drag to highlight all the cells you want in the chart, including headers. If your data is in a contiguous range (no blank rows or columns), you can click any cell inside it and Excel will usually detect the full range.

Tip: If your data has gaps or you only want specific columns, hold Ctrl (or Cmd on Mac) while clicking to select non-adjacent ranges. Excel will still build the chart from the combined selection.

Step 3: Insert a bar chart

Go to the Insert tab on the ribbon. In the Charts group, click the bar chart icon. You'll see a dropdown with several options.

For a standard horizontal bar chart, choose Clustered Bar under the 2-D Bar section. If you want vertical bars, look under Column instead — Excel calls vertical bar charts "column charts."

You can also use the Recommended Charts button, which suggests chart types based on your data structure. It's useful if you're not sure whether a bar, column, or line chart fits best.

Step 4: Choose your chart type

Excel gives you several options:

• Clustered bar — bars side by side for each category. Best for direct comparison.
• Stacked bar — bars stacked on top of each other. Shows total and composition.
• 100% stacked bar — every bar fills the full width, showing proportions. Good for comparing percentages across categories.

Pick clustered if you're not sure. It's the most readable for most use cases.

Step 5: Add a title and labels

Excel drops in a generic "Chart Title" placeholder. Click it and type something descriptive — "Q1 vs Q2 revenue by region" tells people exactly what they're looking at.

To add data labels (the actual numbers on each bar), click the chart, then click the + icon that appears next to it. Check Data Labels. You can position them inside the bar, outside, or at the base.

You should also consider adding axis titles. The + menu has an Axis Titles option — use it to label what each axis represents. "Revenue (USD)" is more useful than a naked number scale.

At this point you have a working bar chart. Everything from here is refinement.

How to customize your bar graph

The default chart is functional but plain. Here's how to make it clearer and more polished.

Change colors and styles. Click any bar to select the series, then right-click and choose Format Data Series. Under Fill, pick a solid color. You can also apply a preset style from the Chart Design tab — but most of the presets are heavy-handed. Picking two or three clean colors manually usually looks better.

Add or adjust data labels. Click the chart, hit the + button, and toggle Data Labels. Click the arrow next to it for placement options. For horizontal bars, "Outside End" is usually the most readable.

Adjust axis scale. Right-click the value axis (the numbers) and select Format Axis. You can set minimum and maximum bounds, change the interval between tick marks, or switch to a logarithmic scale if your values span several orders of magnitude.

Reorder bars. Excel plots categories in the order they appear in your data, but the vertical axis displays them bottom-to-top by default. To reverse this (so the first row in your data appears at the top of the chart), right-click the category axis, choose Format Axis, and check Categories in reverse order.

If you want bars sorted by value (largest to smallest), sort your source data first. There's no built-in "sort chart" button — the chart follows the data.

Add a secondary axis. If you're plotting two metrics with very different scales (like revenue in thousands and conversion rate as a percentage), select one data series, right-click, and choose Format Data Series → Secondary Axis. This adds a second value axis on the right side of the chart so both series are readable.

Remove chart clutter. Gridlines, legends, and borders all add visual noise. If your chart only has one data series, you don't need a legend. If your data labels are visible, you might not need gridlines. Use the + button to toggle these elements on and off. Fewer elements usually means a clearer chart.

Format numbers on the axis. Right-click the value axis, choose Format Axis, and look for the Number section. You can switch to currency format, add thousands separators, or reduce decimal places. If your values are in the millions, consider displaying them as "1.2M" instead of "1,200,000" — right-click the axis, go to Format Axis → Number → Custom, and use a format like #,##0,,"M".

Bar graph variations in Excel

Excel offers several bar chart variations. Knowing when to use each one saves you from picking the wrong chart and confusing your audience.

Clustered bar chart

Bars sit side by side for each category. Use this when you want to compare individual values directly — like revenue across four regions, or performance across three products.

Works best with 2-4 data series. More than that and the bars get too thin to read. If you have more series, consider splitting into separate charts or using a different visualization.

Good for: "How does each region compare on Q1 vs Q2 revenue?"

Stacked bar chart

Each bar is a single stack made up of segments. Use this when you care about both the total and the breakdown. For example, total support tickets per month, broken down by priority level.

The catch: only the bottom segment has a consistent baseline, so it's hard to compare middle or top segments across categories. If precise comparison between segments matters more than the total, use clustered instead.

Good for: "What's total revenue per quarter, and how much came from each product line?"

100% stacked bar chart

Every bar extends to 100%, showing proportional composition. Use this when the absolute values don't matter and you want to compare how something is distributed. For example, what percentage of each team's time goes to different project types.

Good for: "What share of each department's budget goes to software vs hardware vs services?"

Horizontal vs vertical (bar vs column)

Excel treats these as separate chart types. "Bar chart" is horizontal; "Column chart" is vertical. They show the same data — the choice is mostly practical:

• Use horizontal bars when your category labels are long (they're easier to read along the vertical axis).
• Use vertical columns when you have a time-based axis (months, quarters, years), since people naturally read time left to right.

Common mistakes to avoid

A few things that make bar charts harder to read than they need to be.

Too many categories. Once you pass 10-12 bars, the chart becomes a wall of color. If you have 30 categories, show the top 10 and group the rest into "Other," or split into multiple charts.

Missing or vague labels. "Chart 1" tells nobody anything. Neither does a bar chart with no axis labels. Spend ten seconds on a descriptive title and make sure both axes are labeled.

Using 3D effects. Excel offers 3D bar charts. Don't use them. The perspective distortion makes it genuinely harder to compare bar lengths, which is the entire point of the chart. Stick to 2D.

Wrong chart type for the data. Bar charts compare categories. If you're showing change over time with a continuous scale, a line chart is usually better. If you're showing parts of a whole for a single category, consider a pie chart (though bar charts often work here too).

Not sorting by value. An unsorted bar chart forces your audience to visually scan every bar to find the largest or smallest. Sort descending unless there's a natural order to the categories (like months or age ranges).

Starting the value axis above zero. This is subtle but important. If your axis starts at 50,000 instead of zero, small differences between bars look huge. Bar charts encode data as length — if the axis doesn't start at zero, the lengths are misleading. (Line charts are different — truncating the axis is often fine there since you're tracking change, not comparing absolute sizes.)

Inconsistent colors with no meaning. If every bar is a different color but the colors don't represent anything, you're adding visual noise. Use one color for a single series. Use distinct colors only when they map to something meaningful, like different product lines or teams.

When Excel bar charts aren't enough

Excel works well for simple, one-off charts. But a few patterns signal you've outgrown it.

The chart is static. Every time the underlying data changes, you're rebuilding or at least manually updating. If your data refreshes weekly or daily, this gets old fast. You end up spending time on chart maintenance instead of analysis.

No live connection to your actual data. Your numbers probably live in a database, CRM, or SaaS tool — not a spreadsheet. Getting them into Excel means exporting CSVs, copying and pasting, or building fragile connector setups. Each manual step is a chance for errors and stale data.

Sharing means emailing files. You made a chart. Now you need five people to see it. So you email the file, or paste a screenshot into Slack. Three days later, someone makes a decision based on a version that's already outdated.

You can't combine data from multiple sources. Want to plot marketing spend from your ad platform against revenue from Stripe on the same chart? In Excel, that means manually pulling both datasets, aligning them, and hoping the formats match. It's doable once. Doing it every week is a different story.

Customization hits a ceiling. Excel's chart engine is capable, but it hasn't changed fundamentally in years. Interactive filtering, drill-downs, dynamic date ranges, conditional formatting based on thresholds — these either require VBA workarounds or aren't possible at all.

What the alternative looks like

At Fabi, we built our platform around a different model. You connect your data sources directly — Postgres, MySQL, Salesforce, Stripe, Google Sheets, whatever you're using — and ask for what you want in plain English.

"Show me a bar chart of revenue by region for the last 6 months."

You get an interactive chart that updates when your data does. You can share it with a link — not a screenshot, not an attachment, an actual live view. Your team can filter and explore without touching the underlying data. And if you want to go deeper — pivot to a different chart type, add a breakdown, compare to a different time period — you just ask.

The difference is most obvious when you're doing something you do regularly. A weekly pipeline review, a monthly revenue breakdown, a daily campaign performance check. In Excel, that's a recurring time cost. With a live connection to your data, the chart is always current. You open it and start discussing, not rebuilding.

It's not about replacing Excel for everything. If you need a quick chart for a one-time presentation, Excel is still perfectly fine. But if you're building charts regularly from data that changes, the manual workflow becomes the bottleneck.

If you're interested in how AI is changing data visualization more broadly, we wrote about AI data visualization tools and getting started with AI-powered visualization. And if you're hitting the limits of spreadsheet-based reporting, our guide on building dashboards from Google Sheets covers similar pain points. We also compared the broader Excel vs Python tradeoff for data analysis if you're evaluating your options.

The bottom line

Making a bar chart in Excel is simple: select your data, insert a chart, pick the type, and customize. For quick, one-off visualizations, it works.

But if you find yourself rebuilding the same charts every week, stitching together data from multiple sources, or emailing spreadsheets around so people can see the numbers — that's friction worth eliminating.

You can try Fabi free and build your first chart in a few minutes. Connect a data source, describe what you want, and see if it fits how your team actually works.