Mastering CHOOSECOLS and SPLIT in Google Sheets

Working with large or messy datasets in Google Sheets can slow you down—but it doesn’t have to. The CHOOSECOLS and SPLIT functions are powerful tools that make extracting and reshaping data fast and effortless. Whether you're splitting text from a single cell or selecting just the columns you need, these functions help you clean up your spreadsheets with precision. Let’s dive into the basics of these functions and explore some use cases.

🔍 What is CHOOSECOLS in Google Sheets?

CHOOSECOLS is a Google Sheets function that allows you to extract specific columns from a larger array or dataset by simply specifying their positions. It’s incredibly useful when you’re working with imported data, dashboards, or reports that require only certain fields.

Syntax:

=CHOOSECOLS(array, col_num1, [col_num2, …])

• array: The full data range (e.g., A2:D100)

• col_num1, col_num2, …: One or more column index numbers to extract (1-based)

Example:

You have a table with columns: Name, Age, City, Email. To pull just Name and Email:

=CHOOSECOLS(A2:D100, 1, 4)

This gives you a clean, focused table with only the columns you need.

🧰 Use Cases for CHOOSECOLS

• Custom Dashboards: Create summary tables with only relevant fields.

• Data Cleaning: Strip unnecessary columns from raw imported data.

• Exporting Clean Reports: Automatically extract and format the exact columns to share or export.

• Form Results Parsing: Select specific columns from a form submission dataset.

💻 Equivalent Functions in SQL and Python

If you’re familiar with SQL or Python, CHOOSECOLS is conceptually similar to selecting columns from a table or a DataFrame.

Standard SQL Example:

SELECT name, email FROM users

Python (pandas) Example:

import pandas as pd
df = pd.read_csv("users.csv")
subset = df[['name', 'email']]

Just like CHOOSECOLS, this returns only the desired fields from a larger dataset. These methods retrieve or isolate just the specific columns you want, similar to what CHOOSECOLS does in Sheets. Great if you're moving between tools and need a similar logic structure.

🔄 Using CHOOSECOLS Across Tabs and Sheets

One of the most practical features of CHOOSECOLS is its ability to work with data from other tabs or even other Google Sheets files. This is especially helpful when your data is organized across multiple sources and you want to create a central dashboard or reporting sheet.

📁 From a Different Tab (Worksheet)

To pull columns from another tab in the same spreadsheet, simply reference the tab name before your range.

Example:

You have a tab named Form_Responses and you want columns 1 and 4:

=CHOOSECOLS(Form_Responses!A2:D100, 1, 4)

This returns only the 1st and 4th columns from that specific tab. Make sure the tab name has no typos—if it contains spaces, enclose it in single quotes:

=CHOOSECOLS('Form Responses'!A2:D100, 1, 4)

🌐 From a Different Google Sheet (External File)

To use CHOOSECOLS with another sheet entirely, combine it with the IMPORTRANGE function.

Step-by-step:

1. First, get the URL of the source Google Sheet.

2. Use IMPORTRANGE to pull data.

3. Wrap CHOOSECOLS around it to extract specific columns.

Example:

=CHOOSECOLS(IMPORTRANGE("https://docs.google.com/spreadsheets/d/abc123xyz456", "Sheet1!A2:D"), 1, 3)

This imports data from columns A to D in another Google Sheet, then selects just columns 1 and 3 from the result.

⚠️ You may need to authorize the first connection between your sheet and the external file by clicking “Allow Access” when prompted.

🧰 Use Cases for Cross-Tab and Cross-Sheet CHOOSECOLS

• Centralized Dashboards: Pull specific fields from different department tabs.

• Aggregated Reports: Combine data from multiple contributors without duplicating entire sheets.

• External Data Sources: Use cleaned external data (like from forms or automation tools) and extract just what you need.

This makes CHOOSECOLS a key tool for modular, dynamic spreadsheet workflows—especially when paired with IMPORTRANGE.

✂️ What is SPLIT in Google Sheets?

TEXTSPLIT breaks a single string of text into multiple cells, using a specified delimiter (like a comma, pipe, space, or even a line break). It’s perfect for parsing CSV-style text or converting compact strings into structured data.

Syntax:

=SPLIT(text, col_delimiter, [row_delimiter])

• text: The string to split

• col_delimiter: Character that separates columns (e.g., ",", "|", etc.)

• row_delimiter: (Optional) Character to split rows (e.g., CHAR(10) for line breaks)

Example:

Cell A1 contains:
John Doe|28|New York|john@email.com

To split it into individual values across columns:

=SPLIT(A1, "|")

🧰 Use Cases for SPLIT

• Importing CSV Text: Convert pasted CSV or TSV strings into usable table formats.

• Parsing API Responses: Break apart structured strings returned by integrations.

• Cleaning Delimited Data: Split names, addresses, or product info stored in a single cell.

• Multi-line Splits: Separate multiple values into rows using CHAR(10) (line break delimiter).

💻 Equivalent Functions in SQL and Python

Standard SQL Example:

SELECT SUBSTRING(data FROM 1 FOR POSITION(',' IN data) - 1) AS first_item
FROM contacts;

Python (pandas) Example:

df['data'].str.split(',', expand=True)

This splits each row's string into separate columns—just like TEXTSPLIT.

🔗 Combining TEXTSPLIT and CHOOSECOLS

These two functions become especially powerful when used together. TEXTSPLIT breaks up a string into a structured array, and CHOOSECOLS lets you extract only the pieces you need. This combination is perfect for handling imported data, form responses, or third-party integrations where data comes in as a flat text string or a comma-separated format.

Example:

Cell A1 contains:
John Doe,28,New York,john@email.com

You want just the name and email:

=CHOOSECOLS(SPLIT(A1, ","), 1, 4)

First, TEXTSPLIT splits the string into Name, Age, City, and Email. Then CHOOSECOLS pulls only the first and fourth elements.

🧰 When to Combine These Functions

• Flattened Data Imports: When you paste or receive flattened data in a single column and only want certain parts.

• Quick Formatted Displays: For dashboards where raw text needs to be formatted into selected data points.

• Custom Outputs: When you need to dynamically clean and format structured text for reporting or sharing.

Python (pandas) Equivalent:

split_df = df['data'].str.split(',', expand=True)
subset = split_df[[0, 3]] # Select name and email

This mirrors the same logic and flow as the Sheets formula.

🧠 Pro Tips

• Use CHAR(10) for row-level splitting when working with multi-line text:
  =TEXTSPLIT(A1, ",", CHAR(10))

• Combine with ARRAYFORMULA for bulk processing across columns or rows.

• Use CHOOSECOLS on the output of IMPORTRANGE to trim data from external sheets.

• Make dropdown-controlled views by dynamically passing column indices into CHOOSECOLS.

🏁 Final Thoughts

If you work with Google Sheets regularly—especially for cleaning or extracting data—CHOOSECOLS and SPLIT are must-know tools. They simplify tasks that used to require complex formulas and allow for cleaner, more maintainable spreadsheets.

Combining these functions can drastically improve your spreadsheet workflow, whether you're building dashboards, cleaning up imports, or parsing strings. And if you're familiar with SQL or Python, you'll feel right at home using them.