Mastering Text Patterns with REGEX Functions in Google Sheets

Working with text patterns using regular expressions (REGEX) in Google Sheets can greatly enhance your ability to manage and manipulate data. REGEX functions are designed to recognize text patterns, making them invaluable for searching, extracting, or replacing specific data within cells.

In this guide, we’ll walk you through the basics of the REGEX function in Google Sheets, covering their syntax and practical applications. Starting with foundational examples, we'll progress to more advanced use cases like data validation and cleaning.

By the end, you'll have the skills to streamline text-based tasks and troubleshoot common REGEX issues.

REGEX functions in Google Sheets allow users to work with text patterns to search, match, extract, or replace specific data.

These functions are popularly known as:

• REGEXMATCH
• REGEXEXTRACT
• REGEXREPLACE

These functions simplify data manipulation, making it easier to manage large datasets. Whether you're organizing marketing campaign names or cleaning data, REGEX functions are essential tools for improving accuracy and efficiency in text handling.

A regular expression is a sequence of characters that forms a search pattern. It can be used to check if a string contains the specified search pattern, replace parts of the string, or extract certain parts from the string.

A regular expression is typically defined by special symbols, known as ‘metacharacters,’ which represent a single character, a sequence of characters, or any character from a specified set.

Here are some metacharacters:

Regular expressions combine these metacharacters with letters, numbers, or symbols to create patterns

REGEX functions in Google Sheets allow you to work with complex text patterns for tasks like matching, extracting, or replacing data.

Let's get down to the syntax of these functions and how they work with real-world examples.

The REGEXMATCH function in Google Sheets checks if a cell's content matches a specified regular expression pattern. It returns TRUE if the pattern is found within the text and FALSE if no match is detected, making it useful for identifying specific patterns in data.

The syntax of the REGEXMATCH function in Google Sheets is:

Here's the REGEX formula breakdown:

• text: The text or cell reference you want to test against the regular expression.
• regular_expression: The regular expression pattern used to match the text. This pattern can include specific characters, numbers, or special regex symbols.

Let's say you are managing an email marketing campaign and want to check if a list of email addresses in column C contains a specific domain, such as "example.com."

You can use the following formula in D3 :

Here’s what that means:

• C3: Refers to the cell containing the email address to be tested.
• example.com: The regular expression pattern checks for the "example.com" domain in the email address.

If the email in cell C3 contains "example.com," the function will return TRUE; otherwise, it will return FALSE.

For a more complex scenario, let’s say you want to check if the email addresses in column C belong to either "example.com," "test.com," or "demo.com."

In this case, you can use the OR operator (|) in the regular expression:

This formula will return TRUE if any specified domains are found in the email addresses, helping you easily filter and validate email lists.

REGEXEXTRACT is a powerful function in Google Sheets that enables efficient text manipulation by extracting specific data based on a regular expression. It uses regex patterns to identify and pull out desired portions of text, making complex text processing tasks easy and highly effective within spreadsheets.

The syntax of the REGEXEXTRACT function in Google Sheets is:

Here's the breakdown:

• text: The input text or cell reference from which you want to extract specific data.
• regular_expression: The pattern used to match and extract a specific part of the text.

Suppose you have a list of email addresses in column C, and you want to extract only the domain names from these email addresses.

You can use the following formula:

Here’s what that means:

• C3: Refers to the cell containing the email address.
• @(.+)$: The regular expression pattern extracts everything after the "@" symbol, which represents the domain name.

This formula returns the domain part of the email, helping you organize and analyze domain-specific email data.

REGEXREPLACE is a useful text function in Google Sheets that enables automatic find-and-replace operations using regular expressions (regex). It allows you to match and manipulate text patterns efficiently, saving time by automating repetitive text replacements without the need for manual intervention.

The syntax of the REGEXREPLACE function in Google Sheets is:

Here's the breakdown:

• text: The input text or cell reference where you want to perform the replacement.
• regular_expression: The pattern used to identify the text you want to replace.
• replacement: The text that will replace the matched pattern in the original text.

Suppose you have a list of email addresses in column C, and you want to replace all occurrences of the domain "example.com" with "demo.com"

You can use the following formula:

Here’s what that means:

• C3: Refers to the cell containing the email address.
• example.com: The regular expression identifies all instances of "example.com" in the text.
• demo.com: This is the replacement text that will replace all occurrences of "example.com" with "demo.com"

This formula helps you automate domain updates for email addresses efficiently, saving you from manually editing each one.

By exploring the practical applications of REGEX functions below, you will be able to clean up messy data or search for specific patterns in your spreadsheets.

The REGEXMATCH function helps identify cells that start or end with specific text by using metacharacters. The caret (^) checks for the beginning, while the dollar sign ($) identifies the end of a string.

This function works for both text and numeric patterns, making it useful for filtering various types of data, such as product codes or other string sequences.

Suppose you are managing a product inventory and want to identify order IDs in column B that start with "DEMO" or end with "789."

To check if a product code starts with "DEMO":

Use the following REGEXMATCH formula:

This formula will return TRUE for product codes that begin with "DEMO."

To check if a product code ends with "789":

Use this formula:

This formula will return TRUE for Order IDs that end with "789," helping you filter products based on their manufacturing year.

The REGEXMATCH function can identify cells containing numbers by using a regular expression. Since REGEXMATCH works only with text, you can first convert numeric cells to text format. After conversion, the function can locate specific numbers in a string.

Suppose you are managing a list of Order IDs in column C and need to identify which IDs contain numbers between 1 and 4.

Since the REGEXMATCH function only works with text, first convert the order IDs to text format by selecting the cells, and going to Format > Number > Plain text.

Once the order IDs are converted to plain text, apply the following REGEXMATCH formula in column E:

This formula will return TRUE if the order ID in E3 contains any digit between 1 and 4, helping you quickly locate relevant products that meet this condition.

The REGEXMATCH function is useful for checking whether a cell contains an exact match for a string or numeric value. By using the caret (^) to mark the start and the dollar sign ($) to mark the end of the string, you can ensure the function looks for an exact match, whether it's text or numbers.

Suppose you manage Order IDs and want to ensure that an Order ID in C3 exactly matches the text "DEMO789."

To check for an exact match of the order ID, use the following formula in E3:

This process helps you verify exact matches for order IDs in your dataset. The REGEXMATCH function ensures that only entries that match exactly with "DEMO789" are marked as TRUE, filtering out any entries with additional or different characters.

The REGEXMATCH function in Google Sheets allows you to match multiple values, either across an entire column or within a single cell. This can be useful for checking if specific values are present in a dataset, either in a single column or within a string in a cell.

The REGEXMATCH function allows you to search for multiple values in an entire column by using the OR operator ‘(|)’. This is useful when you want to check if any cell in a column contains specific keywords or phrases.

Let’s assume you're managing a list of addresses, and you want to determine whether the addresses in column B contain the words "Pine" or "Spruce." You can use the REGEXMATCH function to check this.

Enter the formula in E3:

This formula will return TRUE if the address contains either "Pine" or "Spruce."

The REGEXMATCH function can also check if multiple specific values appear within a single cell. This is particularly useful when you need to verify that the cell content starts with one value and ends with another.

In this example, you want to check whether the addresses in column B begin with "890" and end with "Blvd." This is useful if you're looking for specific addresses that fit a particular pattern.

Enter the formula in E10:

Here:

• ^: Indicates that the address should start with "890".
• $: Ensures it ends with "Blvd".
• [a-zA-Z0-9, ]+: Allows any letters, numbers, commas, and spaces in between.

This formula will return TRUE if the address meets both conditions.

The REGEXREPLACE function in Google Sheets allows you to find and replace text based on patterns, making it especially useful for cleaning or standardizing data. This function is valuable in simple and complex text replacement tasks across a dataset.

You might have a list of customer names in column B and want to replace the last name "Doe" with "Smith" for consistency. You can use the REGEXREPLACE function to perform this replacement.

Enter the formula in D3:

This formula replaces the last name "Doe" with "Smith"

Suppose you have a list of phrases in column B that include the word "fun(ny)," and you want to replace it with "fun." Here’s how you can do it using REGEXREPLACE.

Enter the following REGEXREPLACE formula in D10:

This formula finds and removes the "(ny)" part, leaving "fun" in its place.

Extra spaces can cause issues in data formatting and analysis when working with datasets. The REGEXREPLACE function can quickly remove these extra spaces, ensuring that the data remains consistent and easy to work with.

Suppose you manage a customer list where some names have extra spaces between the first and last names. This can affect sorting and filtering in your dataset. To fix this, you can use the REGEXREPLACE function to replace multiple spaces with a single space.

Enter the following REGEXREPLACE formula in D3:

This formula finds any sequence of one or more spaces (\s+) and replaces them with a single space.

Using REGEXREPLACE to remove extra spaces ensures that your customer names are uniformly formatted, improving data consistency.

When working with data like phone numbers or IDs, it’s often necessary to clean up entries by removing any non-numeric characters. The REGEXREPLACE function allows you to strip out non-numeric characters, leaving only the numbers easily.

Suppose you're managing a contact list where phone numbers are stored in column B with dashes, parentheses, or spaces. To standardize the phone numbers, you want to remove all non-numeric characters, leaving only the digits.

Enter the formula in E3:

The regular expression \D matches any non-numeric character, and the formula replaces these characters with an empty string, leaving only the numbers.

When working with dates, you might need to extract just the month and year for reporting or analysis. The REGEXEXTRACT function allows you to pull out specific parts of a date, such as a month or year, based on the format used in the dataset.

Suppose you have a list of purchase dates in various formats in column C, and you want to extract only the month and year for reporting purposes. You can use the REGEXEXTRACT function to do this.

A simple formula to extract just the year:

The regular expression \d{2}/(\d{4}) looks for the two-digit month (\d{2}) followed by a four-digit year (\d{4}), extracting only the year in this case.

However, if you want to extract both the month and year and combine them into a single value, you need a more comprehensive approach.

To extract both the month and year from the date and combine them into one result, use this formula:

Enter the following REGEXEXTRACT formula in E10:

Here:

• The first part REGEXEXTRACT(C10, "(\d{2})") extracts the first two digits, which represent the month.
• The second part REGEXEXTRACT(C10, "\d{2}/\d{2}/(\d{4})") extracts the last four digits, which represent the year.
• "& '/' &": Combines the month and year with a / in between, giving a final output in the format "MM/YYYY."

Using REGEXEXTRACT with the combined formula allows you to extract both the month and year from transaction dates.

The REGEXEXTRACT function in Google Sheets allows you to efficiently pull out the domain name from a URL, leaving out the protocol and other parts of the address.

You are managing a list of customer website URLs in column B and want to extract only the domain names for reporting or further analysis. Using the REGEXEXTRACT function, you can easily extract the domain from each URL.

Enter the following REGEXEXTRACT formula in E3:

This formula looks for the domain name after "www." and extracts everything that follows until the next /, using the regular expression "www\.([^/]+)". It extracts everything after "www." up to the next period, capturing the primary domain name.

Advanced applications of REGEX functions in Google Sheets allow you to handle more complex text-processing tasks. These advanced techniques enhance your ability to manipulate data efficiently, saving time and improving accuracy in large datasets.

When handling customer data or public reports, removing or masking email addresses for privacy is often necessary. The REGEXREPLACE function in Google Sheets allows you to detect and replace email addresses, either entirely or partially.

Suppose you have a list of customer emails in column C and want to completely replace or mask the email addresses for privacy purposes.

To replace the entire email address with a placeholder like [email address removed], you can use the following formula:

Here:

• [\w.-]+: Matches the local part of the email (everything before @).
• @[\w.-]{2,}\.[a-z]{2,}: Matches the domain part of the email.
• "[email address removed]": Replaces the entire email address with this placeholder.

If you want only to mask the first part of the email and keep the domain, use this formula:

Here:

• [\w.-]+: Matches the local part of the email (the part before @).
• (@[\w.-]{2,}\.[a-z]{2,}): Matches the domain part of the email and captures it in parentheses.
• "xxxxxx$1": Replaces the first part with "xxxxxx" while keeping the domain unchanged using $1 (which refers to the content inside the first set of parentheses).

In some cases, you may need to replace text in a way that ignores case sensitivity. Google Sheets allows you to make case-insensitive replacements using the REGEXREPLACE function by adding the (?i) flag at the beginning of the regular expression.

Suppose you have a list of product codes in column C, and you want to replace any instance of "demo" with "XXX". You want the replacement to apply regardless of how "demo" appears, whether in uppercase, lowercase, or mixed case.

Enter the following REGEXREPLACE formula:

Here:

• C3: The cell containing the original product code.
• "(?i)demo": Adding (?i) at the start of the pattern makes the replacement case-insensitive, matching any variation of "demo" (such as "DEMO," "Demo," or "dEmO").
• "XXX" : The replacement text.

When working with datasets that contain multiple values that need to be replaced with the same result, the REGEXREPLACE function is highly efficient.

By using the OR condition (|), you can replace several values simultaneously with just one formula. This is particularly helpful when making case-insensitive replacements.

If you have a list of product codes in Google Sheets where specific sequences (like "dEMO") need to be replaced based on exact case-sensitive matches, REGEXREPLACE can simplify this task.

This function allows you to search for specific patterns within text strings and replace them, without needing to nest multiple SUBSTITUTE functions.

Enter the following REGEXREPLACE formula:

Here:

• C3 is the cell containing the original product code.
• "dEMO" is the exact pattern we want to replace. Since we haven’t added (?i), the replacement will only apply to case-sensitive matches.
• "XXX" is the replacement text.

The REGEXEXTRACT function allows you to extract multiple parts of a string by using parentheses to define each section you want to extract. This is particularly useful when dealing with structured data like IDs, phone numbers, or codes that follow a specific pattern.

Suppose you have a list of international phone numbers in Column B, structured as follows:

Enter the formula:

Here:

• \+(\d+): extracts the country code (e.g., +1). The \+ matches the plus symbol, and (\d+) matches one or more digits.
• -(\d+): extracts the area code, with - matching the hyphen separator.
• -(\d+): extracts the local number part.

The REGEXEXTRACT function allows you to extract specific portions of a string while ignoring others using non-capturing groups. Non-capturing groups, denoted by (?:), allow certain parts of the string to be matched but not returned as part of the extracted data.

Suppose you have a list of phone numbers, and you want to extract only the second group of numbers after the country code (e.g., "987" from "+91-987-6543-210"). By using a non-capturing group, you can ignore the country code and capture just the segment you need.

Enter the formula:

Here:

• (?: ...): This is a non-capturing group, meaning it matches text but does not include it in the result.
• \+: Matches the literal + character at the start of the phone number (e.g., +91).
• \d+: Matches one or more digits following the + symbol, which is the country code (e.g., 91 in +91-987-6543-210).
• -: Matches the hyphen right after the country code.
• {1}: Specifies that the non-capturing group (?:\+\d+-) should be repeated once. This effectively skips the first segment (country code) and hyphen after it.
• (\d+): This is a capturing group, which means the digits matched here will be extracted.
• \d+ : matches one or more digits. Since this is the first group after the country code, it captures the first segment after the country code (e.g., 987 in +91-987-6543-210).

Integrating REGEX functions with other Google Sheets functions can significantly expand their power. Combining these functions allows you to automate complex data tasks, perform advanced filtering, and manipulate large datasets.

This approach allows you to check if any values from a list are mentioned in a range of text in Google Sheets. By combining ARRAYFORMULA, REGEXMATCH, and JOIN, you can match multiple values simultaneously across multiple rows, simplifying the process of identifying matches in large datasets.

Let’s say we have Order IDs and a list of descriptions about the order. You want to check if any description contains an Order ID from the list.

Use the following formula:

Here’s what the formula does:

• JOIN("|", C3:C7): Combines all values into a single pattern, separated by | (OR operator).
• REGEXMATCH(D3:D7, JOIN("|", C3:C7)): Checks each cell to see if it contains any value from C3:C7.
• ARRAYFORMULA: Allows REGEXMATCH to apply to all cells simultaneously, returning TRUE if there’s a match and FALSE if not.

The result will return TRUE if a order ID is mentioned in the description, otherwise, it will return FALSE. Drag the fill handle down to apply the formula to other cells.

💡While the combination of ARRAYFORMULA and REGEXMATCH, enhances the process of matching values across large datasets, the ARRAYFORMULA function can be utilized in many other ways to improve data handling in Google Sheets. Dive into our guide on mastering the ARRAYFORMULA function to simplify and automate large-scale data manipulations.

You can match multiple values in a cell using the REGEXMATCH and AND functions in Google Sheets. This method ensures all specified values are present in the text, regardless of extra characters or spaces.

Suppose you want to identify rows where the email field contains the domain "example.com" and the description includes the word "high-quality".

Enter the formula:

Here’s how the formula works:

• REGEXMATCH([Email Cell], "example\.com"): This part checks if the cell containing the email address includes the domain "example.com".
• \ : an escape character, ensuring the dot is matched literally, looking for the exact string "example.com".
• REGEXMATCH([Description Cell], "(?i)high-quality"): This part checks if the cell containing the description includes the word "high-quality".
• (?i): The flag makes the match case-insensitive, so it will capture variations like "High-Quality" or "HIGH-QUALITY".
• AND(...): Combines the two REGEXMATCH results. It returns TRUE only if both conditions are TRUE.

This method ensures that both criteria are met, making it useful for filtering or categorizing data based on the presence of multiple terms.

You can combine the FILTER function with REGEXMATCH in Google Sheets to filter data based on specific patterns. This approach allows you to extract rows that match specific criteria, making it ideal for filtering names, keywords, or phrases from a dataset.

Suppose you want to filter rows where Customer Name (Column A) includes specific names, such as "John Doe" or "Jane Doe," and display both Customer Name and Email Address columns.

In a new column, enter the following formula:

Here:

• REGEXMATCH(B2:B12, "John Doe|Jane Doe"): This part checks each cell in the Customer Name range (B3:B7) for the presence of "John Doe" or "Jane Doe".
• |: acts as "OR," so this pattern returns TRUE for cells in Customer Name that contain either name.
• FILTER(B3:C8, REGEXMATCH(B3:B8, "John Doe|Jane Doe")): FILTER includes rows from Customer Name and Email Address (Columns B and C) for entries where Customer Name in Column B matches "John Doe" or "Jane Doe"

By combining FILTER and REGEXMATCH, you can easily filter your data based on specific names or patterns.

💡While combining FILTER and REGEXMATCH helps efficiently narrow down data based on specific patterns, the FILTER function alone offers endless possibilities for dynamic data extraction. To unlock its full potential, check out our in-depth guide on mastering the FILTER function in Google Sheets.

In Google Sheets, when replacing text using the REGEXREPLACE function, the result may sometimes get truncated, especially when replacing shorter text with longer text. To avoid truncation, you can combine REGEXREPLACE with the MID function to maintain the entire string.

Imagine you’re managing a product catalog where each product code varies in case (upper, lower, or mixed). For quality control, you need to standardize part of this code. Specifically, you want to replace "CASE" with "ABCDE" while keeping the code’s length intact for downstream systems that require a fixed format.

Enter the following formula:

Here:

• MID(C3, 1, 10): Extracts the first 10 characters of the Product Code, preserving a specific length.
• (?i): makes the search case-insensitive, so it will match "case," "CASE," "Case," etc.
• "ABCDE": replaces any version of "case" with "ABCDE" while maintaining the length.

The ARRAYFORMULA function allows you to apply a formula to an entire range of data at once, making it highly efficient when working with large datasets. By combining ARRAYFORMULA with REGEXREPLACE, you can dynamically apply text replacements across multiple rows in a single step.

You’re managing a product catalog with product codes that vary in case. For quality control, you need to standardize these codes by replacing any version of "CASE" (upper, lower, or mixed) with "XXX" across the entire column in one step, ensuring consistency without manual edits.

Enter the following formula:

Here:

• ARRAYFORMULA(...): Applies the formula to each cell in the range, transforming every product code in one step.
• C3:C7: The range for the Product Code column, starting from the second row.
• (?i): Makes the replacement case-insensitive, so it captures any version of "CASE" (like "CaSe", "CASE", "cAse").
• "XXX": Replaces each instance of "CASE" with "XXX".

When you need to replace multiple different values within your dataset, you can use nested REGEXREPLACE functions in combination with ARRAYFORMULA. Each REGEXREPLACE function in the nest handles a different replacement condition, allowing you to apply multiple replacements at once.

Suppose you have a list of Product Codes in varying cases, and for quality control, you need to standardize specific parts of each code. Specifically, you want to replace any instance of "CASE" with "XXX" and "DEMO" with "YYY" across all product codes.

Using ARRAYFORMULA with nested REGEXREPLACE, you can make these changes in one step for the entire column.

Enter the following formula:

Here:

• REGEXREPLACE: REGEXREPLACE(C3:C7, "(?i)case", "XXX"): Replaces any instance of "CASE" (regardless of case) with "XXX".
• REGEXREPLACE: REGEXREPLACE(..., "(?i)demo", "YYY"): After replacing "CASE", this step replaces any instance of "DEMO" (regardless of case) with "YYY".
• ARRAYFORMULA(...): Applies these nested replacements across the entire Product Code range in one step.

When working with REGEX functions in Google Sheets, errors can occur due to incorrect patterns, syntax mistakes, or mismatched references. Understanding common issues and how to troubleshoot them is crucial for ensuring accurate results and smooth performance

⚠️ Error: The #VALUE! error in REGEXEXTRACT happens when the specified regular expression doesn’t match any part of the text.

✅ Solution: To resolve this, carefully review your pattern to ensure it correctly targets the desired substring. Adjust or simplify the expression if necessary for accurate matching.

⚠️ Error: The #ERROR! in REGEXEXTRACT formulas usually arises due to syntax errors or invalid cell references.

✅ Solution: Check that your regular expression is correctly formatted and ensure all referenced cell ranges are valid. Correcting these issues will help avoid formula errors and improve functionality.

⚠️ Error: When using REGEXREPLACE or REGEXMATCH, even a small mistake in your regular expression syntax can cause errors.

✅ Solution: Test your expressions with sample data to identify issues and ensure they perform as expected. Carefully check for missing escapes or incorrect character usage to avoid unexpected results.

⚠️ Error: An incorrect reference format in REGEXREPLACE occurs when the formula references an invalid cell range or incorrectly structured data.

✅ Solution: Ensure that the referenced cells contain valid text data and that the range is properly defined. Correcting the reference format helps avoid errors and ensures smooth function performance.

⚠️ Error: In REGEXREPLACE, special characters like ‘*, +, ?,’ and ‘.’ have specific meanings in regular expressions.

✅ Solution: To match them literally, use a backslash (\) to escape these characters. This ensures that the characters are treated as text rather than part of the pattern, preventing unexpected results.

⚠️ Error: REGEXMATCH is case-sensitive by default, leading to incorrect results when matching text with varying cases.

✅ Solution: To perform a case-insensitive match, use the ‘(?i)’ flag at the start of the regular expression, or apply the LOWER function to the text before matching.

⚠️ Error: When using REGEXREPLACE, unexpected results may occur due to unaccounted whitespace in the text.

✅ Solution: To handle spaces correctly, include \s in your regular expression to match any whitespace character. This ensures your pattern accurately replaces text, even if it includes spaces or tabs.

To get the most out of REGEX functions in Google Sheets, it's important to follow best practices. These guidelines help you create efficient, accurate expressions, avoid common mistakes, and streamline your data handling. With the right approach, REGEX can significantly simplify complex text-processing tasks.

When working with both REGEXMATCH and REGEXEXTRACT, begin by testing simple patterns to ensure accuracy. Gradually build up to more complex expressions. This approach helps you catch errors early and create reliable patterns that work as intended.

To improve performance when using REGEXMATCH with large datasets, focus on optimizing your formulas. Minimize unnecessary calculations by simplifying patterns and avoiding the use of volatile functions like NOW() or RAND() in your regular expressions. This approach helps reduce processing time and ensures smoother performance.

When working with REGEXREPLACE and REGEXEXTRACT, take advantage of online regex tools to refine your patterns. Websites offering regex testers or cheat sheets allow you to quickly validate, test, and adjust your regular expressions before applying them in Google Sheets, saving time and ensuring accuracy.

When using REGEXMATCH and REGEXEXTRACT, always test and debug your patterns carefully. Work with sample data to verify that your expressions are capturing the intended results. This helps ensure accuracy and prevents unexpected errors when applied to larger datasets.

Before incorporating regular expressions into complex formulas, test them first with the REGEXREPLACE function. This allows you to verify that your patterns work as intended, making it easier to troubleshoot and refine them without dealing with additional formula complexity.

Before making significant changes with REGEXREPLACE, always create backups or duplicate your data. This precaution helps you avoid accidental data loss or irreversible changes, allowing you to restore the original dataset if something goes wrong during the modification process. It's a key step to safeguard your work.

Google Sheets offers a range of powerful formulas designed to streamline your data analysis. These key functions enable you to handle, evaluate, and interpret complex datasets with accuracy and simplicity, making it easier to derive meaningful insights.

• INDEX Function: Returns the value of a cell in a given range based on row and column numbers.
• IMPORTRANGE: Imports a range of cells from a specified spreadsheet, enabling you to pull data from other Google Sheets.
• UNIQUE: Extracts unique values from a range, eliminating duplicates.
• SEARCH: Finds the position of a specified text string within another text string. It’s useful for locating specific data within cells.
• COUNTIF: Counts the number of cells in a range that meet a specific condition.
• MATCH Function: Searches for a specific value in a range and returns the relative position of that value.
• QUERY Function: Allows you to run SQL-like queries on your data within Google Sheets, offering powerful data manipulation and filtering options.

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