Pivot Charts in Excel: Complete Guide to Create, Format & Analyze Data

Complete-Guide-Pivot-Chart-in-Excel
Complete Guide Pivot Chart in Excel

Creating Pivot Charts in Excel is a game-changer for anyone looking to summarize and visualize data effectively. Pivot Charts take the powerful data summarization of Pivot Tables and add a visual element, helping you spot trends and patterns at a glance.

In this comprehensive guide, we’ll explain what Pivot Charts are and why they’re useful, show you step-by-step how to create a Pivot Chart, provide examples with sample data, compare Pivot Charts vs Pivot Tables, and share basic formatting tips. By the end, you’ll be able to create dynamic charts that make data analysis in Excel easier and more insightful. Let’s dive in!

What is a Pivot Chart in Excel?

What-is-a-Pivot-Chart-in-Excel
What is a Pivot Chart in Excel

Excel Pivot Chart:

A Pivot Chart is basically a visual representation of a Pivot Table’s data. Think of it as a regular Excel chart that’s powered by a Pivot Table in the background. When you have a large dataset and you use a Pivot Table to summarize it (for example, summing up sales by region or counting entries by category), a Pivot Chart can instantly turn that summary into a graph or chart for easier analysis.

In short, Pivot Charts give you a complete visual picture of your summarized data. They allow you to analyze data using graphs – making it much easier to spot comparisons, patterns, and trends in your data. Pivot Charts in Excel

Pivot Charts are dynamic and interactive. This means if you filter or rearrange fields in the Pivot Table, the chart updates automatically, and vice versa. For example, if you have a Pivot Chart showing total sales by product category, you can click filter buttons on the chart to show only a specific category or year, and both the chart and the underlying Pivot Table will adjust. This interactivity makes Pivot Charts excellent for exploring data. They are especially useful in presentations or dashboards where you want to communicate insights from data visually – for instance, highlighting sales trends over months or comparing performance across regions.

Use Cases: Pivot Charts shine whenever you need to present summary data visually. Common use cases include:

  • Financial Analysis: Summarize expenses or revenue by category and month, then use a Pivot Chart (like a line or column chart) to see trends over time.
  • Sales & Marketing: Visualize sales data by region, product, or salesperson to quickly identify top performers or trends (e.g., a Pivot Chart can instantly show which region had the highest sales this quarter).
  • Large Data Summaries: Any time you have a large data table (thousands of rows) and you want to distill it into meaningful graphics. Pivot Charts handle large datasets well because they rely on Pivot Tables’ efficient summarization.

Pivot Charts are built on Pivot Tables, so you’ll typically create a Pivot Table (or let Excel create one automatically) and then get a chart from it. If you’re new to Pivot Tables, it might help to brush up on that first (see for an introduction to PivotTables). But don’t worry – you can still follow along with creating Pivot Charts even if you’re not a Pivot Table expert. Excel often handles a lot of the setup for you when inserting a Pivot Chart.

How to Create a Pivot Charts in Excel Step-by-Step Tutorial

create-a-pivot-table-in-excel
create a pivot table in excel

Creating a Pivot Chart in Excel is straightforward. We’ll go step-by-step through the process. For this tutorial, let’s assume we have a sample dataset of sales – for example, a list of transactions with columns: Product, Region, and Sales Amount. We want to create a Pivot Chart to see total sales by product and region. Follow these steps:

  1. Select your data and insert a PivotChart:
    • Make sure your data is organized in a table with clear headers. Click any cell in the data range (Excel will auto-detect the full range for the PivotChart). Now, go to the Insert tab on Excel’s Ribbon and click PivotChart (in some Excel versions this might be labeled as PivotChart or found under the PivotTable dropdown). Figure: In Excel, go to the Insert tab and click PivotChart to start creating a Pivot Chart. This action tells Excel that you want to create a Pivot Table and a linked Pivot Chart from your data.
  2. Choose the data and placement for the PivotChart:
    • After clicking PivotChart, Excel opens the Create PivotTable dialog box (don’t let the name confuse you – this is used for PivotCharts too). In this dialog, you’ll see your data range pre-filled if your table was selected. Ensure “Select a table or range” is chosen, and verify the correct range of cells is highlighted for your data. Next, choose where you want the PivotChart (and PivotTable) to go – either New Worksheet (Excel will add a new sheet for the PivotChart) or Existing Worksheet (choose a cell on the current sheet where the chart should appear). Typically, selecting New Worksheet is convenient to keep things tidy. Once your settings look correct, click OK. Figure: The Create PivotTable dialog appears. Select your data range and choose to place the PivotChart report on a new or existing worksheet, then click OK.
  3. Build the PivotChart by adding fields to the PivotTable:
    • After clicking OK, Excel will insert a new worksheet (if you chose that option) with an empty PivotTable and a blank chart area – this blank chart is the PivotChart, waiting for data. You’ll also see the PivotTable Fields pane (often called the PivotChart Fields pane in this context) on the right side of Excel. Now it’s time to drag and drop fields to create your Pivot summary.
    • In our example, to visualize total sales by product and region, we would drag Product field to the Axis (Categories) area, Region field to the Legend (Series) area, and Sales Amount (or whatever your value field is) to the Values area (Excel will default to summing the values). As you add these fields, you will notice the Pivot Table gets populated with data, and the Pivot Chart on the sheet starts displaying a chart.
    • Figure: After adding fields to your PivotTable (Product in Rows, Region in Columns, and Sales in Values), Excel generates a Pivot Table and a Pivot Chart. Here, the Pivot Chart shows a comparison of sales by product (x-axis) across different regions (legend series). You can further refine the PivotTable if needed – for example, maybe you want to filter to a specific year or category. You can drag fields into the Filters area for that, and use the filter dropdowns that appear. The chart will update automatically to match any PivotTable filtering or rearrangement.
  4. Analyze and refine the Pivot Chart:
    • Your Pivot Chart is now created and showing summarized data! Take a moment to interpret it. In our example, you might see a clustered column chart with each product’s sales split by region, making it immediately clear which product is performing best in each region. You can hover over the chart columns to see exact values (Excel will show the values in a tooltip).
    • At this stage, you might want to do a bit of clean-up or customization: for instance, you can rename the chart title (just click on the default title and type a more descriptive one, like “Sales by Product by Region”), or adjust the field settings (maybe sort the products by total sales, or remove a field if the chart is too busy). We’ll cover formatting in more detail later, but even without any styling, you now have a functional Pivot Chart that you can interact with.
    • Try clicking the filter buttons on the chart (the little drop-down arrows next to field names on the chart, such as “Region” or “Product”) – you can filter out certain items or drill down as needed, and the chart (and PivotTable) will update accordingly. This interactivity allows you to analyze your data from different angles quickly.

Note: If you’re using Excel for Mac or Excel Online, the process to get a Pivot Chart is slightly different. Those versions do not have a one-click “PivotChart” insertion like Excel for Windows. Instead, you’ll need to create a PivotTable first, then insert a regular chart based on that PivotTable. The chart will behave like a Pivot Chart (it will pivot when you change PivotTable fields), but the initial step requires making the PivotTable manually. So Mac and web users: first go to Insert > PivotTable, set up your PivotTable, then select the PivotTable and insert a chart (e.g., Insert > Chart > choose a type). The inserted chart will link to the PivotTable.

Now that we’ve created a Pivot Chart step by step, let’s look at a concrete example to solidify the concept.

Pivot Chart in Excel Example with Sample Data

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click on pivot chart (1)

To illustrate how Pivot Charts can be used, let’s walk through an example scenario with actual numbers. Suppose you have the following simple dataset of monthly expenses for a household:

MonthCategoryAmount ($)
JanuaryRent1200
JanuaryGroceries400
JanuaryUtilities150
JanuaryEntertainment200
FebruaryRent1200
FebruaryGroceries350
FebruaryUtilities130
FebruaryEntertainment180

(This is just a snippet; imagine it continues for all months of the year.)

Using a Pivot Chart, we can answer questions like “Which expense category is the highest each month?” or “How do my expenses compare month to month?”. Here’s how we’d do it:

  • Create a PivotTable from this data, and add Category to Rows, Month to Columns, and Amount to Values (summed). This PivotTable would show a matrix of total amounts per category per month.
  • Now insert a PivotChart from this PivotTable. Perhaps choose a Column Chart for a clear comparison. The Pivot Chart will display clustered columns by month for each category.
  • The resulting Pivot Chart might show, for example, that Rent is consistently the largest bar every month (as rent is a fixed high expense), while Entertainment might be a smaller bar that varies. You could quickly spot that groceries spiked in December (if the bar for Groceries in December is taller) and so on.

This visual makes it easy to see spending patterns: rent is steady, utilities perhaps go up in winter, entertainment might spike in holiday seasons, etc., all in one chart. Without the Pivot Chart, you’d have to read numbers from the PivotTable or original data, which is harder to digest quickly. This example shows how a Pivot Chart helps analyze and communicate data at a glance.

The beauty of Pivot Charts is that you can easily adjust them on the fly. If you wanted to see the yearly total per category instead of monthly, you could remove the Month field and just have Category vs Amount – the chart might instantly turn into a single-column per category (or you could change it to a Pie Chart to show the proportion of each category in total spending). With a few clicks, you’ve transformed the analysis perspective, which is incredibly powerful for decision-making.

(Internal Note: The Pivot Chart examples above demonstrate how versatile these charts can be with different data. Whether it’s sales data or expense data, the creation process is the same – only the fields you use will differ.)

Pivot Table vs Pivot Chart – What’s the Difference?: Pivot Charts in Excel

It’s common to hear both “Pivot Table” and “Pivot Chart” and wonder how they differ. In fact, they are closely related – one feeds the other – but they serve different purposes in Excel:

  • Pivot Table: This is a tool in Excel that summarizes data in a table (grid) format. With a Pivot Table, you take a large dataset and group it by categories to get totals, counts, averages, etc. Pivot Tables are fantastic for analyzing numerical data in detail, allowing you to drill down into specifics, sort and filter, and rearrange the table (pivot it) to answer different questions. The output is textual/numerical (rows and columns of numbers). For example, a Pivot Table might tell you total sales for each product in each region in a grid of numbers.
  • Pivot Chart: This is essentially the chart visualization of a Pivot Table’s output. It cannot exist without an underlying Pivot Table (Excel actually ties the two together – when you create a Pivot Chart, a Pivot Table is either created automatically or used as the source). The Pivot Chart takes the summary from the Pivot Table and displays it as a graph (columns, bars, line, pie, etc.). This makes it much easier to see comparisons and trends – your eyes can compare bar lengths or line slopes instead of scanning numbers. For example, a Pivot Chart of the sales data might show a bar chart comparing product sales across regions, making it immediately obvious which product is highest in each region, something that might take a bit of scanning in a raw Pivot Table.

In essence, Pivot Tables are about data, and Pivot Charts are about visuals. They work together: the Pivot Table does the heavy lifting of crunching numbers, and the Pivot Chart displays those numbers in a picture. Any changes you make to one will reflect in the other. If you update or refresh the Pivot Table (say new data added), the Pivot Chart updates too. If you filter a Pivot Chart, the Pivot Table behind it is also filtered to match. Microsoft’s documentation puts it nicely: Pivot Charts complement PivotTables by adding visualizations, allowing you to easily see patterns and trends from the summary data.

Here are a few key points comparing Pivot Tables and Pivot Charts:

  • Data vs Visualization: A Pivot Table shows numbers in rows and columns, whereas a Pivot Chart shows graphics (bars, lines, slices) based on those numbers. Pivot Charts make the data from Pivot Tables easier to digest visually for many people.
  • Interactivity: Both are interactive. You can pivot (rearrange fields), filter, and drill down in both. However, filtering might feel more intuitive in a Pivot Chart through clicking chart elements or slicers, while in a Pivot Table you often use drop-down menus. Either way, the changes sync between them.
  • Use Cases: Pivot Tables are ideal when you need precise numbers and perhaps to copy those summaries elsewhere or do further calculations. Pivot Charts are ideal when presenting the data or quickly demonstrating a trend or comparison in a meeting/report.
  • Limitations: A Pivot Table can handle any fields and values you throw at it, but a Pivot Chart is limited to chart-friendly data. For instance, Pivot Charts typically support most chart types (column, bar, line, pie, area, etc.) but not all (Excel doesn’t allow certain types like scatter or map charts directly from Pivot data). Also, some formatting that you might add to a standard chart (like intricate customizations, trendlines, or data point formatting) may not always stick if the PivotChart is refreshed because it redraws based on PivotTable data. In practice, this just means Pivot Charts are best for summary views, not for highly customized one-off charts.
  • Dependency: You can use a Pivot Table alone without any chart. You cannot truly use a Pivot Chart alone without a Pivot Table – even if Excel hides the Pivot Table, it’s there as the engine. So think of the Pivot Chart as an extension of the Pivot Table.

Bottom line: Use Pivot Tables for analyzing the data details and use Pivot Charts for presenting the data visually. They are complementary. It’s not really an “either/or” choice – in fact, you often use them together. For example, you might build a Pivot Table to ensure your calculations are right and then create a Pivot Chart from it to include in a report. If you’re new to Pivot Tables, again, consider Pivot Table Basics to get familiar, since a Pivot Chart’s effectiveness depends on a well-structured Pivot Table behind the scenes.

(Fun fact: When you create a PivotChart in Excel, if you don’t already have a PivotTable, Excel actually builds a PivotTable in the background to feed the chart. You can usually see this PivotTable on the sheet with the chart (it might be an empty-looking outline if you placed the PivotChart on a new sheet). So a PivotChart is essentially a PivotTable + a chart combined.)

Basic Pivot Chart Formatting Tips: Pivot Charts in Excel

Once your Pivot Chart is created and displaying the data you want, the next step is often to format the chart to make it clear and attractive. Excel provides many tools to customize the look and feel of your Pivot Charts. Here are some basic formatting tips and best practices, especially useful for making your chart easy to read and professional-looking:

  • Add Chart Elements like Titles, Labels, Legend:
    • One of the first things you’ll want to do is ensure your chart has a descriptive title and properly labeled axes (if applicable).
    • Excel Pivot Charts, by default, might not include axis titles or a detailed legend title. Click on the “+” (Chart Elements) button that appears next to the chart, or use the Add Chart Element menu on the Chart Design (or PivotChart Analyze) tab, to add things like Axis Titles, Data Labels, Gridlines, and Legends.
    • For example, adding data labels can directly show values on each bar/column, which may help readers see the numbers without referring to the table. However, use data labels judiciously – if there are too many bars, labels can clutter the chart.
  • Use Chart Styles and Colors:
    • Excel has pre-set Chart Styles (usually found on the Ribbon under Chart Design when the chart is selected) that can instantly give your Pivot Chart a polished look.
    • Feel free to click through these styles to find one that suits your presentation. You can also change the color palette by choosing a different Colorful or Monochromatic option, matching perhaps your company’s theme colors.
    • The Chart Styles and color options allow you to adjust the chart’s look in one click. For instance, you might choose a style that makes the chart 3D or one that places data labels nicely. Just remember that clarity is more important than fanciness – pick a style that makes the data easy to read. A simple design with contrasting colors for different series often works best.
  • Formatting Axes and Numbers:
    • If your Pivot Chart has a value axis (like the Y-axis on a column chart), make sure the number format is appropriate. If you’re dealing with currency, format the axis labels as currency; if large numbers, maybe use a shorthand (e.g., display in thousands “K”).
    • To do this, click the axis, right-click and choose Format Axis, and set the format (or, easier, format the field in the PivotTable itself by applying number formatting to the Values field – the chart will inherit that).
    • A well-formatted axis prevents confusion (for example, knowing that numbers are in dollars, or that they represent percentages). Also consider the scale of the axis – Excel auto-chooses it, but you can adjust the bounds if it makes the chart tell a clearer story.
  • Adjust Layout for Clarity:
    • Sometimes the default layout can be improved. Maybe the legend would be better at the bottom than on the side, or the categories on the axis need to be rotated because they’re long text.
    • All these can be adjusted. On the Chart Design tab, you’ll find Quick Layout options that rearrange titles, legends, and labels in preset ways. This can be a fast way to try out a different look. You can also click any specific element (like the legend or an axis) and drag it or format it.
    • For category labels that are long, right-click the axis -> Format Axis -> you can angle the text or wrap it. Small tweaks like this can make a big difference in readability.
  • Pivot Chart Analyze Tools:
    • When you click on a Pivot Chart, an extra tab on the Ribbon called PivotChart Analyze (or Analyze in some versions) appears. Here you have some pivot-specific options. For example, you can click Field Buttons to hide those filter buttons on the chart if you don’t want them visible in a final report. (They’re useful for interactivity, but if you’re printing the chart or sending to someone, you might hide field buttons to declutter the chart area.)
    • You can also insert Slicers from this tab, which are visual filters – for instance, a slicer for Region would create clickable buttons for each region, which can be a user-friendly way to let a viewer filter the chart. Slicers look nice on dashboards and make filtering very obvious. In PivotChart Analyze, you’ll also see options to Refresh (which updates the chart if data changed) and to Move Chart (perhaps you want to move the chart to its own sheet or to a dashboard sheet).
  • Use the Format Tab for Fine Tuning:
    • Next to the PivotChart Analyze/Design tabs, you should also see a Format tab (this is the regular chart formatting tools). This is where you can change shapes, text styles, and other detailed formatting. For example, you can click on a data series (e.g., the bars for “North Region”) and then use Format to change its color or outline manually if you don’t like the default. You can add Shape Effects or WordArt Styles for titles if that suits your report’s style – but usually simpler is better. The Format tab also lets you precisely adjust size and alignment if needed. These tools are the same as for standard charts, so if you know how to format a regular chart, it all works on Pivot Charts too.
  • Keep it Simple and Consistent:
    • A key rule for any chart is to avoid unnecessary clutter. With Pivot Charts, it can be tempting to add all the things – data labels, every field button, an extensive legend, brightly colored backgrounds, etc. But remember, the goal is to communicate insights, not distract. Make sure your colors are consistent (e.g., if you have multiple Pivot Charts in a report, use the same color scheme for all). Use gridlines sparingly or only as needed for reference. Each element on the chart should serve a purpose. For example, if the chart bars already have data labels showing exact values, you might decide to remove or lighten the value axis, since the labels do the job. If you have many categories and the chart is crowded, consider breaking it into multiple charts by a logical grouping rather than one overstuffed chart.
  • Common Mistakes to Avoid:
    • Be mindful of a few pitfalls. One common mistake is overloading the chart with too much information – for instance, too many categories or series can make it indecipherable. If your Pivot Chart looks overwhelmingly busy, try filtering out some data or grouping items (you can group in the PivotTable or use a slicer to focus on a subset). Another mistake is using inconsistent or loud colors that confuse the viewer.
    • Stick to a palette that is colorblind-friendly and professional (Excel’s defaults are usually OK, but ensure enough contrast between series). Also, remember to refresh your PivotTable/PivotChart if your source data has changed – a Pivot Chart does not auto-update in real-time unless you refresh the data or have an Excel Table as source and refresh the PivotTable.
    • If you see something odd (like data missing or outdated), you might have forgotten to hit the refresh button on the PivotChart Analyze tab. Finally, choose the right chart type for your data story: for comparing parts of a whole, a pie might work (though avoid too many slices); for trends over time, a line chart is clearer than a bar; for ranking or comparisons, bar/column charts are very effective. Excel allows you to change Pivot Chart types easily, so feel free to experiment – just right-click the chart and choose Change Chart Type.

By applying these formatting tips, your Pivot Chart will not only be accurate in terms of data but also visually clear and appealing. A well-formatted Pivot Chart can make the difference between confusing your audience and impressing them with a compelling data story. Remember, simplicity and consistency are key for professional-looking charts – make your chart tell the story at a glance.

Conclusion: Pivot Chart in Excel

Pivot Charts in Excel are a powerful way to turn your data into insightful visuals. In this guide, we covered what Pivot Charts are and how they work hand-in-hand with Pivot Tables, walked through creating a Pivot Chart step by step, looked at real examples of how they can be used to analyze data, compared Pivot Charts to Pivot Tables, and discussed tips for formatting Pivot Charts for maximum clarity. By now, you should feel confident in creating Pivot Charts and customizing them to fit your needs.

In practice, the more you use Pivot Charts, the more ideas you’ll get on slicing and dicing your data. They invite you to explore – you might start with one view of your data and then quickly pivot (pun intended!) to another insight just by dragging a new field or applying a filter. This flexibility makes Pivot Charts one of the favorite tools for analysts and managers alike.

If you’re building out a full report or dashboard, remember to consider the cluster strategy: this Pivot Chart guide is like a pillar content piece. You can dive deeper into related topics (for example, mastering the underlying Pivot Tables in Pivot Table Basics, or learning advanced PivotTable techniques, or how to use slicers and timelines for interactive filtering). Each of those topics can strengthen your overall understanding of Excel’s data analysis capabilities.

Finally, as you create Pivot Charts, always circle back to the question: What insight am I trying to communicate? Let that guide which data you include and how you format the chart. With practice, your Pivot Charts will help you and your audience make sense of complex data quickly and effectively. Happy charting!

FAQ: Learn Pivot Charts in Excel

Q1. What is a Pivot Chart in Excel?

A Pivot Chart in Excel is a visual representation of a Pivot Table that helps you analyze and compare data using interactive charts.

Q2. How do I create a Pivot Chart in Excel?

Go to Insert > PivotChart, select your data range, choose placement (new or existing sheet), then drag fields into Rows, Columns, and Values.

Q3. Can I use Pivot Chart without a Pivot Table?

No. Pivot Charts always need a Pivot Table as their source, but Excel creates one automatically when you insert a Pivot Chart.

Q4. Why should I use Pivot Charts?

They make it easier to spot trends, patterns, and comparisons in your data than just reading numbers in a Pivot Table.

Q5. What’s the difference between a Pivot Table and Pivot Chart?

A Pivot Table summarizes data in rows and columns, while a Pivot Chart displays that summarized data visually as graphs.

Q6. Can I filter data directly in a Pivot Chart?

Yes. Pivot Charts have filter buttons that let you quickly drill down or hide/show data categories.

Q7. Which chart types are supported in Pivot Charts?

Most common types like column, bar, line, pie, and area are supported. Advanced types like scatter or map charts are not.

Q8. Can I format a Pivot Chart like a normal chart?

Yes, you can add chart elements, change colors, and adjust layout. But some custom formatting may reset after refreshing.

Q9. How do Pivot Charts handle large datasets?

They efficiently summarize and display large data when combined with Pivot Tables, making analysis scalable and interactive.

Q10. Can I connect multiple Pivot Charts to one dataset?

Yes. You can create multiple Pivot Tables from the same source data and link them with Slicers for synchronized filtering.

Jitendra Rao

Jitendra Rao, the founder of Excel Pro Tutorial, is a seasoned Microsoft Excel Trainer with over 11 years of hands-on experience. He shares his knowledge through engaging tutorials in Hindi on both YouTube and Instagram, making learning Excel accessible to a wide audience. With a strong background in not only Excel but also PowerPoint, Word, and data analytics tools like Power BI, SQL, and Python, Jitendra has become a versatile trainer. His mission is to empower individuals and professionals with the skills they need to succeed in today’s data-driven world.

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