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Let’s say you’re using Google Sheets to manage sales figures. You need to analyze sales by region, so using the Google Sheets QUERY function to filter the data sounds like a plan.
But what if your data has duplicate entries? Well, unfortunately, QUERY can’t handle that alone, but the above formula can help.
However, combining QUERY with UNIQUE allows you to easily clean up duplicates and tidy up the table before analysis and reporting. In this article, we’ll explore how these functions team up to improve your data analysis in Google Sheets. Let’s get started!
Note: This article was originally published in January 2024 and has been updated in April 2025 to improve content quality, and ensure accuracy with the latest Google Sheets functionalities.
Using the UNIQUE and QUERY functions in Google Sheets offers several advantages that can improve your data analysis and management:
By incorporating the UNIQUE and QUERY functions into your Google Sheets toolkit, you can take your data analysis to the next level, ensuring that your insights are both accurate and actionable.
The QUERY function in Google Sheets is like a smart search tool that helps you find, filter, and organize data easily. It uses simple commands to filter rows, sort information, and even combine data from different tables in your spreadsheet.
Understanding the QUERY formula is important because it lets you sort, group, and select specific data using SQL-like operations. This makes it easier to analyze your information and set up a Google Sheet QUERY UNIQUE structure, especially when combined with the SORT function for better organization.
The syntax of the QUERY function in Google Sheets looks like this:
=QUERY(data, query, [headers])
Here's what each parameter means:
💡For more information on how to use the QUERY function effectively, check out our detailed article covering all the ins and outs of QUERY in Google Sheets.
Let’s say you have a sales report in Google Sheets that includes multiple entries for the same product sold on different dates. You want to analyze your sales data to see which products sell better without counting duplicates.
With the UNIQUE function, you can extract a list of product names, identify each distinct product sold, and analyze sales trends more accurately.
If your dataset is large, adding a helper column can make it easier to apply the UNIQUE function, especially when working with Google Sheets QUERY UNIQUE values in a column.
Here’s how to remove duplicates in Google Sheets with a UNIQUE formula and streamline your data management processes.
The syntax of the UNIQUE function in Google Sheets is as follows:
=UNIQUE(range)
Where “range” specifies the range of cells from which you want to extract distinct or unique values. It can include a single range or multiple ranges separated by commas. This function is particularly useful for extracting unique rows from a dataset, ensuring that each entry is distinct.
In data analysis, it is crucial to distinguish between ‘unique' and ‘distinct' values for accurate data manipulation, especially if you're using the UNIQUE Google Sheets function.
While both terms identify different elements in a dataset, they serve different purposes:
If we have a list of sales representatives and their sales figures, here is how to use the unique function. The UNIQUE function can be applied to retrieve the list of distinct sales reps and the list of unique sales reps.
Understanding these distinctions not only enhances your ability to manipulate large datasets properly, but also equips you with the knowledge to apply the right type of data extraction based on your analytical needs.
💡For more practical applications and to see these concepts in action through detailed examples, consider exploring further in our complete guide on using the UNIQUE function in Google Sheets. Here, you’ll find refined techniques such as filtering your dataset based on specific criteria and creating a dynamic drop-down menu, which can elevate your data analysis tasks.
Let’s explore how QUERY paired with UNIQUE can simplify your daily tasks. With QUERY UNIQUE Google Sheets techniques, you can return unique combinations of data, making your analysis more precise and effective.
We’ll examine 3 situations where this combination is useful:
These methods help you identify distinct records more efficiently and improve data management. Additionally, advanced queries can streamline data analysis by focusing on specific conditions and making complex tasks easier.
When isolating distinct values in a single column, we’re essentially organizing our data to identify individual entries without any repetition. This process is useful in various scenarios, such as analyzing sales figures by region.
This process helps in identifying and eliminating repeated values, ensuring data accuracy. By using QUERY and UNIQUE functions, we can quickly filter out duplicate regions and focus solely on the distinct ones.
Syntax:
=UNIQUE(QUERY(range, "SELECT column"))
Here’s what each parameter means:
Example:
If you have a sales dataset with seller names, regions, and sales figures, using this formula will give you a list where each combination of seller, region, and sales data appears only once. For instance, you can extract data based on conditions applied to 'column B', which influences the selection of rows in a defined range.
You can use the following formula to get this result from your sales data:
=UNIQUE(QUERY(B3:D10, "SELECT B, C, D"))
It’s a simple way to clean up your data and make sure you’re working with information without duplicate entries.
It means finding distinct combinations of values that span across more than 1 column in your dataset. Instead of just looking for distinct values in a single column, you’re now considering combinations of values across different columns. This is particularly useful when dealing with horizontal data.
Syntax:
=UNIQUE(QUERY(range, "SELECT column1, column2, ..."))
Here’s what each parameter means:
Example:
Our sales dataset has columns for sales representative names, regions, and sales figures. Extending the UNIQUE function across multiple columns allows us to find distinct combinations of names and regions, rather than just values in each column separately.
You can use the following formula to get this result from your sales data:
=UNIQUE(QUERY(B3:D10, "SELECT B, C"))
It’s a helpful way to identify distinct combinations across columns and avoid duplicated groupings in your dataset.
Securing only distinct rows in your dataset means making sure that there are no identical rows. Each row should be different from the others, with no duplicates. This helps maintain accurate data, especially when each row represents a specific sales transaction or customer information.
Syntax:
=UNIQUE(QUERY(data_range, "SELECT column1, column2 WHERE condition"))
Here’s what each parameter means:
Example:
Let’s say we need to extract distinct rows from the range B3:C10, where the value in column B is either John Smith or Jane Doe. The formula returns unique rows based on these specific criteria, ensuring no duplicate entries.
You can use the following formula to get this result from your sales data:
=UNIQUE(QUERY(B3:C10, "SELECT B, C WHERE B='John Smith' OR B='Jane Doe'"))
This ensures you're working with truly distinct records, especially when each row contains important transactional or customer data.
Combining QUERY and UNIQUE techniques in Google Sheets can improve your data analysis. By using the following techniques together, you will save time and improve accuracy.
Before you mix QUERY and UNIQUE functions, make sure you understand each one on its own and learn their syntax. Knowing them individually first helps you tackle more complex data tasks, and then you will be ready to combine them effectively.
To avoid mistakes, use TO_TEXT, TO_NUMBER, or TO_DATE to make sure all data is in the same format before you start managing and analyzing data from it. This helps prevent errors, such as mismatched formats or calculations. Keeping your data consistent means you can trust your analysis more and make better decisions based on the information you have. Additionally, certain elements, like column letters, must be case sensitive to avoid errors.
To make your spreadsheet run faster, filter your data with QUERY before using the UNIQUE Function. For example, you can first apply QUERY to select specific records based on conditions, and then use UNIQUE to return only the distinct results. Also, avoid complicated calculations or array formulas that you don’t need. These can slow down your spreadsheet and make it harder to work with.
Giving special names to specific groups of cells in Google Sheets is called Named Ranges. They will make formulas easier to understand, especially with functions like QUERY and UNIQUE. Instead of using confusing cell references (such as A1:B10), you can use names like Sales Data. This makes your formulas much clearer, especially when you’re dealing with lots of data.
For example, you can use a formula like =QUERY(Sales Data, "SELECT A, B WHERE B > 100") to keep things simple. This approach helps in achieving unique results for easier data handling.
Understanding common pitfalls and errors can help you avoid mistakes when using these functions.
Here are some common challenges you might face with QUERY and UNIQUE Functions:
A common problem you can face when using QUERY and UNIQUE is getting the syntax wrong. This can cause errors like #VALUE! or "Unable to parse query string," making your formula fail.
Always check your query carefully to make sure it follows the correct format and avoid these issues.
✅ Solution: Make sure your syntax for combining QUERY and UNIQUE Functions is correct.
Example:
=QUERY(UNIQUE(range), "select * where Col1 is not null", 1)
This formula has a syntax error. In the QUERY function, "select" should be lowercase, and "Col1" should be enclosed in single quotes.
The correct syntax would be:
=QUERY(UNIQUE(range), "select * where 'Col1' is not null", 1)
A common problem happens when the data you’re querying mixes different types, like text and numbers. This can mess up the results or cause errors in the QUERY function.
✅ Solution: To fix this, ensure consistent data formatting across columns. You can use functions like TO_TEXT, TO_DATE, or TO_NUMBER to convert data types before applying the QUERY function.
Example:
=QUERY(TO_TEXT(UNIQUE(range)), "select * where 'Col1' is not null", 1)
The issue with the formula is the incorrect syntax in the WHERE clause. Instead of using single quotes around 'Col1', it should use backticks (`) or no quotes at all to refer to column labels.
The correct syntax would be:
=QUERY(TO_TEXT(UNIQUE(range)), "select * where Col1 is not null", 1)
Using single quotes (‘Col1’) can cause an error because Google Sheets interprets it as a string literal instead of a column reference.
💡If you’re trying to find specific data in a big dataset or match data from different tables, you might need VLOOKUP functions. To learn more about using VLOOKUP and XLOOKUP, check out our detailed guide on these functions.
Using QUERY and UNIQUE functions with large datasets can seriously slow down your Google Sheets.
✅ Solution: Increase performance by filtering your data with QUERY before using UNIQUE. For example, you can first use QUERY to filter and return a few rows of unique data, even when your dataset contains multiple entries like Team A or Position Guard. Additionally, we recommend limiting the use of array formulas (ARRAYFORMULA) and avoiding overly complicated calculations. Handling empty cells efficiently can also improve performance when working with large datasets.
If you’re handling data professionally and regularly dealing with dynamic information, we suggest using tools that can query data directly from spreadsheets and automate tasks on a schedule.
Managing large datasets can be challenging, especially when dealing with duplicate values. The QUERY function in Google Sheets helps by allowing you to remove duplicates and extract unique values. By combining QUERY with the UNIQUE function, you can easily clean your data and return only the distinct rows.
For example, you can use:
=UNIQUE(QUERY(range, "SELECT "))
This formula keeps your dataset free from duplicate entries, making your analysis more reliable and focused on meaningful insights.
When working with large datasets, it’s often necessary to query multiple columns to extract specific data. The QUERY function in Google Sheets lets you do this by specifying multiple column letters in the SELECT statement.
For example, to return only unique combinations from columns A and B, you can use:
=UNIQUE(QUERY(range, "SELECT A, B"))
This formula removes duplicate combinations across columns, helping you maintain a clean dataset for more accurate and meaningful data analysis.
While the QUERY and UNIQUE functions are powerful tools for managing and analyzing large datasets, Pivot Tables offer another simple option.
With a Pivot Table, you can quickly summarize, group, and find unique values without writing complex formulas.
For example, by creating a Pivot Table (Insert → Pivot Table), you can easily extract distinct entries and perform calculations like SUM, AVERAGE, or COUNT.
This makes Pivot Tables a helpful choice for users who prefer a more visual, drag-and-drop approach to managing unique data in Google Sheets.
If you want to improve your Google Sheets skills, learn more about mastering more advanced functions like ARRAY, XLOOKUP, and Pivot Table:
With the OWOX Reports Extension for Google Sheets, you can enhance your data analysis with OWOX Reports, all at a faster pace. By surpassing the 50K row limit, you can analyze larger datasets more thoroughly.
This extension lets you integrate data from BigQuery to Google Sheets. Also, you can use dynamic filters and aggregators which allow you to tailor the data view according to specific criteria, and easily share up-to-date reports with your team.
