How to View Pivot Table in Google Sheets
Staring at a massive grid of data in Google Sheets can be pretty intimidating. Transforming all those rows and columns into something that actually makes sense is the real challenge. Pivot tables are the perfect tool for turning that cluttered data into a clear, interactive summary. This article will walk you through exactly how to create, view, and modify pivot tables to quickly find the answers you need.
What Exactly Is a Pivot Table, Anyway?
Think of a pivot table as an interactive summary report you can build in seconds. Instead of writing complex formulas to aggregate your data, a pivot table lets you drag and drop different parts of your dataset to group and summarize it in different ways.
Imagine your raw data is a detailed log of every single sale your company made this year. It includes the date, sales rep, region, product, and sale amount. That's useful, but it’s hard to see the big picture. A pivot table can instantly transform that log to show you things like:
Total sales amount for each sales rep.
Which products are selling best in each region.
The average sale size per month.
The magic is in the name: you can quickly "pivot" the data - swapping rows and columns - to look at it from different angles without changing your original spreadsheet. This makes it incredibly easy to explore your numbers and uncover trends you might have otherwise missed.
Step 1: Get Your Data Ready
Before you build your pivot table, you need to make sure your data is structured properly. A pivot table's biggest weakness is messy, disorganized source data. Following a few simple rules now will save you from major headaches later.
Your data should be arranged in a “tidy” format, which means:
Every column needs a header. Make sure the first row of your dataset contains a unique, descriptive name for each column (e.g., "Date," "Region," "Sale Amount").
No empty rows or columns. Your data should be a single, continuous block. Avoid blank rows or columns in the middle of your dataset, as these can stop the pivot table from detecting all your data.
One record per row. Each row should represent a single, unique item. For sales data, each row would be one individual transaction. For survey data, each row would be one person's full response.
Keep data types consistent. Don't mix text and numbers in a column you want to do math with. Make sure your "Sale Amount" column contains only numbers and your "Date" column is properly formatted as dates.
Example Sales Data:
Here’s a simple dataset that's perfectly formatted for a pivot table. Notice how it follows all the rules above.
Step 2: Create and View Your First Pivot Table
With your data correctly formatted, creating the pivot table takes just a few clicks. We’ll use our sample sales data to find the total sales amount for each sales representative.
1. Select Your Data
Click any single cell within your data range. As long as there are no blank rows or columns, Google Sheets is smart enough to detect the entire dataset automatically. Alternatively, you can click and drag to select the full range of cells, including the headers.
2. Insert the Pivot Table
With your data selected, go to the Google Sheets menu and choose Insert > Pivot table.
A small dialog box will appear. It asks where you’d like to create the pivot table. The default option, New sheet, is almost always the best choice. This keeps your summary report separate from your raw data, which is much cleaner. Click Create.
3. Meet the Pivot Table Editor
Google Sheets will now open a new sheet with an empty pivot table on the left and a Pivot table editor sidebar on the right. This editor is your command center for designing the view.
Here are the four key containers in the editor:
Rows: Fields added here will appear as row labels down the left side of your table. This is what you want to group your data by. (e.g., list of Sales Reps)
Columns: Fields added here create columns across the top of your table, breaking down your data further. (e.g., list of Regions)
Values: This is where you put the numbers you want to calculate. Typically, you'll want to add fields with numerical data here. (e.g., Sale Amount)
Filters: You can add fields here to filter the entire pivot table based on specific criteria. (e.g., only show data for a certain Product)
4. Build Your View
Now, let’s build our report. Our goal is to see total sales by sales rep.
In the Pivot table editor, find the "Sales Rep" field and drag it into the Rows container. Instantly, you'll see a unique, alphabetized list of every sales rep appear as rows in your pivot table.
Next, find the "Sale Amount" field and drag it into the Values' container.
That's it! Your pivot table comes to life, showing the sum of sales for each person. Google Sheets automatically "summarizes by" SUM for any field containing numbers. You've just turned 15 rows of raw sales data into a tidy 4-row summary report that's easy to view and understand.
Customizing Your Pivot Table View
The real power of a pivot table comes from how quickly you can change its view to answer new questions. Let's explore how to customize it.
Change Calculation Types
What if you wanted to know the average sale amount for each rep instead of the total? In the editor's Values container, click on the dropdown menu under "Sale Amount" (it currently says "SUM"). You can choose a different calculation like AVERAGE, COUNT (to see how many sales they made), MAX, or MIN. The data in your table will update immediately.
"Pivoting" Your Data to Get New Views
Let’s ask a new question: "How did each rep perform in each region?"
In the editor, drag the Region field into the Columns container. Now your pivot table instantly reorganizes itself into a grid, with sales reps as rows and regions as columns. This cross-tabulated view makes it clear who your top performers are in the "North" region versus the "South."
This is the core concept of a pivot table. By simply dragging fields between the different containers, you can reshape your report to answer dozens of different questions.
Adding Multiple Layers
You can also stack multiple fields in the same container for a more detailed, grouped view. For example, what if you wanted to see the breakdown of products sold by each sales rep?
Drag the Product field into the Rows container, right below "Sales Repr." Your pivot table now creates a hierarchical view. You can see each sales rep, and under their name, a sub-list of the products they sold along with the matching sales totals. You can even click the small triangle next to each rep's name to collapse or expand the product details.
Filtering Data for a Focused View
If you have a lot of data, you'll often want to focus your view on a specific subset. Let's say you only want to see the performance of "Laptops." The Filters container is designed for this.
Drag the Product field into the Filters container.
A new filter box will appear below. Click the status dropdown (which currently says "Showing all items").
A checklist of all products will appear. Uncheck "(Select all)" and then check only the box for "Laptop."
Click OK.
Your entire pivot table will now adjust to only show data related to Laptop sales. You can filter by one item or multiple, giving you precise control over the data you’re viewing.
Keeping Your Pivot Table Fresh With Slicers
Filters are great, but toggling them on and off in the editor can be clunky. If you plan to share this report with team members who may not be comfortable in the editor, you can add a Slicer.
A slicer is basically a set of user-friendly buttons that sits on top of your spreadsheet, allowing anyone to filter the pivot table view without touching the editor. To add one:
Click inside your pivot table.
Go to Data > Add a slicer.
A slicer menu appears on the right. In the "Column" dropdown, select the field you want to filter with (e.g., "Region").
Close the menu.
You now have a floating slicer box on your sheet. Clicking on it and selecting "North" or "South" will filter your pivot table in real-time. It’s a much more intuitive way for others to interact with your report and find the view they need.
Final Thoughts
Once you get the hang of it, viewing and using pivot tables in Google Sheets becomes second nature. They're a fantastic tool for taking overwhelming datasets and turning them into concise reports that guide decision-making. The key is to experiment - drag fields around, try different calculations, and see what valuable insights you can find.
While an individual pivot table is great for organizing data in one sheet, the challenge multiplies when that data is scattered across different apps like Google Analytics, Shopify, your CRM, and Facebook Ads. We built Graphed to solve exactly this problem. Instead of exporting CSVs and wrestling spreadsheets, we connect straight to all your tools, bringing your sales and marketing data into one place. From there, you can create real-time dashboards and reports instantly, just by asking for what you want in plain English, and get a unified view of your business performance in seconds, not hours.