How to Build and Customize Pivot Charts in Google Sheets
Pivot charts in Google Sheets unlock a new level of data visualization, turning complex numbers and patterns into instantly understandable visuals. Using pivot charts, you can quickly summarize key metrics, track performance trends, and showcase campaign results in a clear and actionable format.
In this guide, we’ll walk you through each step of creating, customizing, and refining pivot charts in Google Sheets. Whether you’re a data analyst, marketer, or instructor, you’ll find practical tips for choosing the right chart type, adding insightful customizations, and maintaining an updated view as your data evolves.
What Is a Pivot Chart in Google Sheets?
A pivot chart in Google Sheets is a visual representation of data summarized in a pivot table. Unlike regular charts, which display raw data, pivot charts showcase calculated results, such as totals and averages, that have been dynamically grouped or filtered in the pivot table.
This flexibility allows pivot charts to adapt quickly as data changes, making them valuable for real-time insights. By converting pivot table results into a chart, users gain a powerful tool for analyzing and presenting complex data effectively and interactively.
Understanding the Role of Pivot Charts in Google Sheets
Pivot charts help users transform complex data into clear visuals, making analysis more intuitive. They allow users to quickly identify trends, patterns, and outliers by showcasing summarized pivot table data. This makes pivot charts essential for tracking metrics, comparing segments, and presenting insights to stakeholders.
Their dynamic nature ensures that as underlying pivot data updates, the chart automatically reflects changes, providing an efficient way to effortlessly maintain accurate and up-to-date reports.
Differences Between Pivot Charts and Regular Charts
Pivot charts and regular charts in Google Sheets serve different purposes, each tailored to specific data visualization needs. While both help present data visually, pivot charts excel in summarizing complex data, whereas regular charts are ideal for displaying raw data directly.
Here’s a comparison to understand their unique roles:
💡 Looking to master data analysis in Google Sheets? Check out our detailed guide on how to automate pivot tables and charts to learn powerful techniques for transforming raw data into meaningful visuals. Discover tips, tricks, and practical steps to enhance your reporting and streamline analysis! Read more.
Step-by-Step Tutorial to Creating Pivot Charts in Google Sheets
Creating pivot charts in Google Sheets is a straightforward process that begins with organizing your data effectively.
But before we jump into the steps it's essential to prepare your data, let's look at some important planning steps:
- Remove duplicates and correct any data errors for accuracy.
- Sort data by relevant metrics (e.g., date, category) to reveal trends clearly.
- Filter out unnecessary data points that don’t add value to the chart’s story.
- Add calculated fields like percentages, variances, or running totals for enhanced insights.
Step 1: Select Data for Pivot Table
To create a pivot chart, we’ll first set up a pivot table, then convert it into a chart.Using the dataset below, which starts at cell B2, we’ll go through each step to visualize sales data by day:
- Open your Google Sheets file.
- Select the dataset range starting from B2 to D12 (including the headers "Month," "Campaign Name," and "Amount USD").
- With the data selected, go to the Insert menu.
- Choose Pivot table.
Step 2: Choose Location
This is how you can select where your pivot table appears in the sheet to organize your data effectively.
- After clicking on “Pivot table,” a pop-up box will appear, allowing you to place the pivot table in either a new or an existing sheet. We have put this example in the same sheet, starting at cell F2.
- Click Create to generate the pivot table in your selected location.
Step 3: Add Rows and Columns
This step helps you organize your data in the pivot table to view your sales by day. Using the Pivot table editor on the right side of your screen, you can add rows, columns, and values to structure the table.
Add Rows:
- In the Pivot table editor, click on Add under the Rows section.
- Select Campaign Names from the dropdown list. This will list each campaign name in the pivot table.
(Optional) Add Columns: If you want to add a second grouping layer, click Add under the Columns section. You could add Month here to display.
Step 4: Add Values
In the Values section of the Pivot table editor, click Add and choose Amount(USD) from the dropdown list. Google Sheets will automatically summarize this data, calculating the total campaign expense listed in your pivot table.
This summary allows you to quickly view and compare total campaign costs, making data analysis more straightforward.
Step 5: Insert Chart
Now, let's add a chart that represents the pivot table data visually
- To create a visual representation of the pivot table data, select your pivot table, go to the Insert menu, and choose Chart.
- In the Chart editor, select Column Chart under the Chart type dropdown to display each campaign and its sum amount.
- If you don’t like the chart, you can edit it by double-clicking on the chart to open the Chart editor.
- Go to the Setup menu, click on Chart type, and choose a preferred chart style. For this example, select the Pie chart option to visualize the data in a circular format.
We need the "Grand Total" in the pivot table, but not in the pivot chart. Instead of disabling it in the pivot table editor, we’ll adjust the chart range to exclude it.
To do this:
- Double-click on the pivot chart to open the editor.
- Navigate to the Setup tab and modify the range.
- Based on the example, set the range to G12.
Now, the total isn't visible in the chart anymore.
Selecting the Right Chart Type for Your Pivot Data
Google Sheets offers various chart types, each suited to different data insights. Selecting the right chart type allows you to highlight key patterns, comparisons, and trends that best communicate your data’s story.
Here’s how to select the best chart type based on your pivot data:
- Bar charts: Ideal for comparing values across categories or illustrating parts of a whole.
- Column charts: Useful for comparing data points over time or displaying variations across categories.
- Line charts: Best for showing trends and changes over continuous time periods.
- Pie charts: Effective for displaying proportions or percentages within a small number of categories.
- Scatter charts: Helpful for exploring relationships between two variables, spotting outliers, or identifying clusters.
When choosing a chart type, you also need to consider-
- Data Type: Consider whether your data is numerical, categorical, or time-based.
- Data Story: Think about what you want to convey, such as comparisons, trends, or proportions.
- Detail Level: Choose a chart that provides the necessary depth to clearly communicate your message.
You can create visuals that effectively enhance your data insights by aligning your chart type with these factors.
💡 Want to transform your data into compelling visuals? Check out OWOX’s guide on using bar graphs in Google Sheets! This article walks you through selecting, customizing, and optimizing bar charts to convey essential insights effectively.
Ways to Customize Your Pivot Charts in Google Sheets
Customizing pivot charts in Google Sheets transforms raw data into clear, impactful visuals. With options to modify colors, adjust chart types, add labels, and apply filters, Google Sheets allows you to enhance chart readability and effectiveness, making your insights more accessible and data-driven decisions easier.
Choosing the Right Chart Type
Choosing the right chart type is essential for conveying insights effectively. Each chart type highlights different aspects of your data: bar charts compare categories, line charts show trends, and pie charts display proportions.
Experimenting with various options helps identify the chart that aligns with your data’s story, ensuring clarity and impact.
Modifying Chart Style
Modifying chart style enhances the visual appeal and coherence of your pivot chart. By adjusting colors, fonts, and borders, you can align the chart with your report's theme, making it more engaging and professional.
Google Sheets offers these customization tools, enabling you to create a polished and cohesive presentation of data insights.
Adding and Editing Chart & Axis Titles
Adding and editing chart and axis titles improves understanding by highlighting the chart’s focus. A clear, descriptive title provides context and directs the viewer’s attention to the main takeaway.
Customize titles to reflect the data's purpose, ensuring each chart element is as informative and intuitive as possible.
Customizing Data Series
Customizing data series enhances your chart’s clarity by visually distinguishing data points. By adjusting colors, line thickness, or style, you can make each series stand out, making comparisons easier for viewers.
Tailoring these elements ensures your chart communicates data distinctions effectively, aiding interpretation and insight discovery.
Adjusting the Legend
Adjusting the legend is critical to making your pivot chart easy to understand. You ensure viewers can quickly identify data series by positioning it where it’s most visible - whether at the top, bottom, or side. An effective legend placement enhances readability and supports smooth data interpretation.
Managing Gridlines & Ticks
Managing gridlines and ticks helps keep your pivot chart clean and focused. Reducing unnecessary gridlines or adjusting tick marks prevents visual clutter, allowing the key data to stand out. Streamlined charts improve readability and guide viewers to focus on the most important information.
Creating a Pivot Chart from a Duplicate Pivot Table in Google Sheets
Creating a pivot chart from a duplicate pivot table in Google Sheets offers flexibility, allowing you to experiment. If your dataset can grow, this approach will be helpful.
Step 1: Duplicate the Pivot Table
To create a pivot chart from a duplicate pivot table, right-click on your existing pivot table and select "Copy."
Now, paste this to a different tab and create a copy. This option allows you to experiment with data visualization settings without impacting the original data and pivot table.
Step 2: Remove Grand Totals
This step may or may not be required based on your existing pivot table setting. In our case, since we had turned it off for creating the chart, the duplicate pivot table also doesn't have it on.
Step 3: Create the Pivot Chart
Now, select the range of the duplicate pivot table to prepare it for charting. Highlight all the cells in this duplicate table. Proceed to create the pivot chart. With the duplicate pivot table range selected, go to Insert > Chart. Google Sheets will generate a chart based on your selected data.
Creating Dynamic Pivot Chart
For a Dynamic Pivot chart, the creation is different; there is one additional step that we need to follow. This is useful when your dataset has a chance of growing.
Step 1: Create the Pivot Table with Extra Row Selection
In the usual process, we created the pivot table by selecting the exact range of the dataset. Here, we will choose a few additional rows while making the pivot table.
Step 2: Insert the Pivot and Edit as Necessary
Now, we will insert the pivot in the usual process by selecting the destination (new sheet or existing sheet with range specification). After that, we will add the rows and columns and remove the grand totals for better visualization.
Step 3: Add Dummy Headers
Before creating the pivot chart, adding temporary headers, also known as dummy headers, in the columns is essential.
These headers ensure the chart can pull data dynamically from columns, as Google Sheets charts cannot directly use data from columns without headers. However, it can pull from rows if the range is considered while creating the chart.
We have added March as one of the dummy headers. You can remove the dummy headers once the pivot chart has been created from the pivot table.
Step 4: Insert the Chart from Pivot by Selecting Additional Rows and Columns
We will now select the pivot table and the dummy header column and insert the chart.
Once the chart is created, we can remove the dummy headers.
We will update the source data to see if it reflects in the pivot table and pivot chart as intended.
If you look at the dataset on the left, we added a row called “March” with campaign data, and you can see that both the pivot and the chart have updated automatically.
Best Practices and Tips for Maintaining Pivot Charts
Maintaining pivot charts ensures your data visualizations stay accurate and relevant. Regularly updating data sources, checking chart formatting, and reviewing filter settings help keep charts aligned with the latest insights. By following best practices, you can ensure your pivot charts effectively communicate data trends and support decision-making over time.
Choose the Right Chart Type for Ongoing Analysis
Choosing the right chart type for ongoing analysis is critical to capturing and communicating data trends. Opt for chart types that best represent your data's nature, like line charts for trend tracking or bar charts for category comparisons. This approach ensures your chart stays effective as the dataset grows.
Keep Pivot Charts Dynamic
Keeping pivot charts dynamic is essential for reliable, up-to-date insights. Link your pivot charts to dynamic data ranges to ensure they automatically update as the underlying data changes. This setup eliminates manual adjustments, helping you maintain accuracy and streamline your data analysis.
Regularly Refresh Your Data
Regularly refreshing your data sources is essential for accurate pivot charts, especially when pulling from external sheets or databases. By updating frequently, you ensure that your charts reflect the latest data, providing the most relevant insights for analysis and decision-making.
Simplify Your Charts for Readability
Simplifying your charts enhances readability by emphasizing the most relevant data points. Remove any unnecessary series, gridlines, or excessive colors to prevent visual clutter. Keeping charts clean and straightforward makes it easier for viewers to focus on key insights and understand the data's core message.
Document Chart Customizations
Documenting chart customizations helps maintain consistency, especially in collaborative settings. By noting changes—such as color schemes, label adjustments, or specific chart types—you provide a reference for future updates. This practice ensures that all team members understand the customization choices and can keep reports uniform over time.
Elevate Your Analysis with Advanced Google Sheets Functions
Using advanced functions in Google Sheets makes it easier to work with large datasets, automate repetitive tasks, and uncover valuable insights. These functions streamline complex calculations, organize information, and enable deeper comparisons, helping you turn raw data into actionable analysis with minimal effort.
- UNIQUE: Filters out duplicates from a selected range, returning unique entries. Ideal for cleaning up data, this function makes it easy to focus on distinct items, helping you organize information for more accurate analysis.
- IMPORTRANGE: This enables you to pull data from other sheets, making it easy to consolidate information across multiple documents for streamlined analysis.
- MATCH: Finds the position of a specified value within a range, helping you quickly locate data for precise analysis.
- COUNTA: Counts all non-empty cells in a range, making it ideal for tracking filled entries, even if they contain text or numbers.
- MAX, MIN, MEDIAN: Identify critical values in your data: the highest, lowest, and middle values. These functions are essential for quickly understanding data range and distribution.
- AVERAGE: Calculates the mean of selected values, giving a quick view of the overall data trend and helping to summarize large datasets effectively.
Simplify Data Visualization with OWOX: Reports Extension for Google Sheets
OWOX: Reports, Charts & Pivots Extension offers powerful tools to transform raw data into actionable insights, with features like reports, charts, and pivot tables. These tools make complex data analysis accessible, helping teams visualize trends, measure KPIs, and make informed decisions.
With OWOX's pivot tables, users can dynamically filter and organize data, creating clear visual representations with charts for more straightforward interpretation.
Customizable reports add flexibility, allowing teams to focus on the most important metrics. Together, these features streamline the process of uncovering key insights across datasets.
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