Introduction to Regex Regular Expressions, commonly referred to as Regex, are powerful tools for working with patterns in text. Whether you’re cleaning data, extracting specific information, or validating inputs, Regex enables you to search, match, and manipulate strings with unparalleled precision. By leveraging concise patterns, Regex allows users to perform what would otherwise be tedious tasks in a fraction of the time.
The Regex Extractor, one of the most popular tools previously offered by WorkbenchData, empowered users to harness the full potential of Regex for various data applications. In this guide, we’ll explore how Regex can be used across different platforms like Excel, Google Sheets, Python, and other coding languages, as well as how it integrates with ChatGPT for advanced prompt engineering.
Regex Formulae in Excel and Google Sheets While Excel and Google Sheets do not natively support full Regex capabilities, they provide workarounds and extensions to achieve similar outcomes.
Regex in Excel Excel supports limited Regex functionality through VBA (Visual Basic for Applications). By writing a custom function, you can add Regex capabilities to your workbooks:
Enable Developer Mode :Go to File > Options > Customize Ribbon and enable the Developer tab. Create a VBA Regex Function : Function RegExExtract(text As String, pattern As String) As String Dim RE As Object Set RE = CreateObject("VBScript.RegExp") RE.Pattern = pattern RE.Global = False If RE.Test(text) Then RegExExtract = RE.Execute(text)(0) Else RegExExtract = "" End If End Function Usage :Use the formula =RegExExtract(A1, "pattern")
to extract matches from text in cell A1
.Regex in Google Sheets Google Sheets natively supports Regex through built-in functions:
REGEXEXTRACT :Extracts the first match of a pattern from a string.Formula: =REGEXEXTRACT(A1, "\d+") (Extracts the first numeric value). REGEXMATCH :Returns TRUE
if a pattern is found in the string.Formula: =REGEXMATCH(A1, "^\w+") (Checks if the string starts with a word). REGEXREPLACE :Replaces text matching a pattern with specified text.Formula: =REGEXREPLACE(A1, "\s+", "-") (Replaces all spaces with hyphens). Regex in Python Python is one of the most Regex-friendly programming languages, with its re
module offering comprehensive Regex capabilities.
Common Regex Functions in Python Searching for Patterns :import re text = "Extract email: example@test.com" pattern = r"[a-zA-Z0-9._%+-]+@[a-zA-Z0-9.-]+\.[a-zA-Z]{2,}" match = re.search(pattern, text) if match: print(match.group()) # Outputs: example@test.com Finding All Matches :text = "Emails: first@test.com, second@sample.org" matches = re.findall(pattern, text) print(matches) # Outputs: ['first@test.com', 'second@sample.org'] Replacing Text :result = re.sub(r"\s", "-", "Convert spaces to hyphens") print(result) # Outputs: Convert-spaces-to-hyphensRegex Tips in Python Use raw strings (r"pattern") to avoid issues with escape sequences. Test your Regex patterns using online tools like regex101 before implementing them in code. VIDEO
Regex in Other Languages Regex is supported across many programming and scripting languages. Below are some examples:
JavaScript const text = "Phone: (123) 456-7890"; const pattern = /\(\d{3}\) \d{3}-\d{4}/; const match = text.match(pattern); if (match) { console.log(match[0]); // Outputs: (123) 456-7890 }
PHP $text = "Find IP: 192.168.0.1"; $pattern = '/\d{1,3}(\.\d{1,3}){3}/'; if (preg_match($pattern, $text, $matches)) { echo $matches[0]; // Outputs: 192.168.0.1 }
R text <- "Extract digits: 42, 78" pattern <- "\\d+" matches <- regmatches(text, gregexpr(pattern, text)) print(matches) # Outputs: [[1]] [1] "42" "78"
Prompt Template for Regex in ChatGPT and Its Uses ChatGPT can assist in generating, explaining, and refining Regex patterns, making it an invaluable tool for both beginners and advanced users.
Prompt Template "I need a Regex pattern for [describe task, e.g., extracting emails].
Requirements:
[Specify any constraints, e.g., "It must match only .com domains"]. [Additional notes, e.g., "It should handle multiple matches in a single text"]. Please provide:
The Regex pattern. An explanation of how it works. Example code snippets for Google Sheets, Python or JavaScript." Useful extra details to help it work the first time:
The target cell to extract the value from and the cell you'll be entering the formula. The potential hiccups: often the data are messy and so you'll see it not work because dates are not in a regular format, or in Python a value is not classified as a string or an integer (just tell the AI this in advance and it will apply the appropriate remedy). Example Use Case Prompt :"Write a Regex pattern to extract phone numbers in the format (123) 456-7890 and provide Python and JavaScript examples."
ChatGPT Output :
Regex Pattern :\(\d{3}\) \d{3}-\d{4}
Explanation :\(: Matches the opening parenthesis. \d{3}: Matches three digits. \): Matches the closing parenthesis. \d{3}: Matches another three digits. \-: Matches the hyphen. \d{4}: Matches the final four digits. Python Code :import re text = "Call me at (123) 456-7890 or (987) 654-3210." pattern = r"\(\d{3}\) \d{3}-\d{4}" matches = re.findall(pattern, text) print(matches) # Outputs: ['(123) 456-7890', '(987) 654-3210'] JavaScript Code : const text = "Call me at (123) 456-7890 or (987) 654-3210."; const pattern = /\(\d{3}\) \d{3}-\d{4}/g; const matches = text.match(pattern); console.log(matches); // Outputs: ['(123) 456-7890', '(987) 654-3210']Uses of Regex in ChatGPT Pattern Validation : Validate and troubleshoot existing Regex patterns.Customization : Generate Regex patterns for specific tasks or datasets.Education : Learn Regex step by step with clear examples and explanations.Regex is an essential tool for anyone working with data, text, or automation. By integrating it into platforms like Excel, Google Sheets, Python, and even ChatGPT, you can unlock powerful solutions to complex problems. Start experimenting with Regex today and discover its transformative potential!