Split Text into Columns in Google Sheets: A Step-by-Step Guide

Learn how to use Split text to columns in Google Sheets to separate names, dates, emails, and other data into multiple columns using delimiters or fixed rules.

Google Sheets includes a built-in Split text to columns feature that lets you separate combined data into multiple columns quickly. It is useful when imported data arrives in one cell but needs to be organized into separate fields.

You can use this tool for things like first and last names, city and state values, comma-separated lists, email addresses, or any other text that contains a clear separator.

Split Text into Columns in Google Sheets: A Step-by-Step Guide

How Split Text to Columns Works

The feature looks for a delimiter, which is the character or spacing pattern that separates parts of the text. Once Google Sheets finds that delimiter, it splits the content across adjacent columns.

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Key Fact Split text to columns changes the layout of your data in place, so make sure there is enough empty space to the right of the selected cells before you apply it.

Use Split Text to Columns in Google Sheets

  1. Select the cell or range of cells that contains the text you want to split.
  2. Open the Data menu at the top of Google Sheets.
  3. Click Split text to columns.
  4. Choose the separator type from the small menu that appears below the selected data.
  5. Check the columns to make sure the text split correctly.

Choose the Right Separator

Google Sheets can automatically detect some common separators, but you can also choose one manually if the default result is not correct.

  • Comma, for CSV-style data such as "Smith, John"
  • Semicolon, for regions or files that use semicolons instead of commas
  • Period, for text separated by dots
  • Space, for names or phrases with single spaces between parts
  • Custom, for symbols like hyphens, slashes, pipes, or tabs
Quick Tip If automatic detection does not split the data correctly, try choosing a custom separator instead of relying on the default option.

Examples of When to Use It

  • Splitting full names into first and last name columns
  • Separating email usernames from domain names
  • Breaking product codes into meaningful parts
  • Organizing imported address data
  • Cleaning up copied data from websites or spreadsheets
Why It Matters Splitting text into columns makes data easier to sort, filter, and analyze. It also helps when you need each piece of information in its own field for formulas, pivot tables, or reports.

Using a Custom Separator

If your data uses a character that is not listed, choose Custom from the separator options and type the symbol you want Sheets to use. This is helpful for data such as account numbers with hyphens or file paths with slashes.

Note If a value contains more than one possible separator, Sheets may split it in an unexpected way. In that case, clean the data first or use a formula-based approach instead.

Things to Watch Out For

Warning Split text to columns can overwrite data already sitting in the columns to the right of your selection. Clear space first or move existing data before applying the split.
  • If the original text has inconsistent separators, some rows may not split evenly.
  • Leading or trailing spaces can create messy results after splitting.
  • Merged cells may interfere with the command.
  • Very complex text patterns may be better handled with formulas such as SPLIT or REGEXEXTRACT.

When to Use a Formula Instead

Use the menu option when you want a quick one-time split. Use formulas when you need the split to update automatically as the source data changes.

Best For Quick cleanup of imported data, especially when you only need to separate text once and do not want to build a formula.

Useful Alternatives in Google Sheets

  • SPLIT formula, for automatic splitting based on a delimiter
  • LEFT, RIGHT, and MID, for extracting fixed parts of text
  • REGEXEXTRACT, for pattern-based text extraction
  • Text to columns in combination with Find and replace, for cleaning inconsistent separators first

If you are working with large or messy datasets, combining cleanup tools with Split text to columns usually gives the most reliable result.

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