Google Sheets is a powerful tool for handling and analysing data, and one of its most exciting features is the ability to create custom functions using LAMBDA. But did you know that you can make your custom LAMBDA functions even more powerful by combining them with advanced helper functions like SCAN, REDUCE, and MAKEARRAY? These functions help you perform complex operations more efficiently and with greater flexibility.
In this article, we’ll explore how these three advanced LAMBDA helper functions can help you manage and manipulate your data with ease. Whether you’re trying to process arrays, create running totals, or generate custom arrays, these functions will give you the tools you need to take your Google Sheets skills to the next level.
What Are SCAN, REDUCE, and MAKEARRAY?
SCAN, REDUCE, and MAKEARRAY are advanced functions in Google Sheets that allow you to perform complex array operations, which is particularly useful when working with large datasets. Here’s a quick rundown of each function:
- SCAN: SCAN applies a function cumulatively across an array, producing an array of intermediate results. It’s useful when you need to track running totals or perform cumulative calculations.
- REDUCE: REDUCE allows you to accumulate a result by applying a function across an array, ultimately returning a single value. It’s ideal for summarizing or consolidating data into one final result.
- MAKEARRAY: MAKEARRAY generates a custom array with a specified number of rows and columns, and each element can be calculated based on its row and column indices. It’s helpful when you need to create dynamic arrays based on specific conditions or patterns.
When combined with LAMBDA, these functions allow for more sophisticated and dynamic data manipulation, making your Google Sheets formulas even more powerful.
How to Use SCAN with LAMBDA for Running Totals
One of the most common uses of SCAN is to create running totals or cumulative calculations. For example, let’s say you have a dataset of monthly sales figures, and you want to calculate the cumulative sales for each month.
Example: Running Total of Sales
Imagine you have the following sales data:
| Month | Sales |
|---|---|
| January | 200 |
| February | 150 |
| March | 180 |
To calculate a running total of sales, use SCAN with a LAMBDA function:
=SCAN(0, B2:B4, LAMBDA(accum, current, accum + current))
Here’s how the formula works:
- 0: The initial value of the accumulator (starting at 0).
- B2:B4: The range of sales data.
- LAMBDA(accum, current, accum + current): The LAMBDA function adds the current value to the accumulator, creating a cumulative sum.
This will produce the following cumulative sales data:
| Month | Sales | Cumulative Sales |
|---|---|---|
| January | 200 | 200 |
| February | 150 | 350 |
| March | 180 | 530 |
How to Use REDUCE with LAMBDA for Consolidating Data
The REDUCE function is great for summarizing data. It processes an array and returns a single value by applying a function cumulatively. REDUCE is often used for tasks like summing, averaging, or finding a specific value across an entire array.
Example: Calculating Total Sales Using REDUCE
Let’s say you want to calculate the total sales from the same dataset. You can use REDUCE to sum up all the sales values:
=REDUCE(0, B2:B4, LAMBDA(accum, current, accum + current))
In this formula:
- 0: The initial value for the accumulator (starting at 0).
- B2:B4: The range of sales data.
- LAMBDA(accum, current, accum + current): The LAMBDA function adds each value in the array to the accumulator, resulting in the total sales.
This will return the total sales value of 530, which is the sum of all the sales for the months listed in the dataset.
How to Use MAKEARRAY with LAMBDA for Custom Array Generation
MAKEARRAY is useful for creating dynamic arrays with a specific number of rows and columns. It allows you to define the logic for generating the array elements based on the row and column indices.
Example: Generating a Multiplication Table
Let’s create a multiplication table using MAKEARRAY. The formula will generate a 5×5 multiplication table based on the row and column indices:
=MAKEARRAY(5, 5, LAMBDA(row, col, row * col))
This formula works as follows:
- 5, 5: The dimensions of the array (5 rows and 5 columns).
- LAMBDA(row, col, row * col): The LAMBDA function calculates the product of the current row and column indices.
This will generate the following multiplication table:
| 1 | 2 | 3 | 4 | 5 | |
|---|---|---|---|---|---|
| 1 | 1 | 2 | 3 | 4 | 5 |
| 2 | 2 | 4 | 6 | 8 | 10 |
| 3 | 3 | 6 | 9 | 12 | 15 |
| 4 | 4 | 8 | 12 | 16 | 20 |
| 5 | 5 | 10 | 15 | 20 | 25 |
Benefits of Using SCAN, REDUCE, and MAKEARRAY with LAMBDA
- Flexibility: These functions allow you to create custom operations on arrays, providing much more flexibility than traditional formulas.
- Efficiency: SCAN, REDUCE, and MAKEARRAY can automate repetitive tasks and calculations, saving time and reducing errors.
- Dynamic Data Processing: These functions can process large datasets dynamically, updating automatically as the data changes.
- Streamlined Formulas: By using LAMBDA, SCAN, REDUCE, and MAKEARRAY, you can break down complex tasks into smaller, reusable steps, making your formulas easier to maintain and debug.
Quick Reference Cheat Sheet for SCAN, REDUCE, and MAKEARRAY
- SCAN Syntax:
=SCAN(initial_value, range, LAMBDA(accum, current, formula)) - REDUCE Syntax:
=REDUCE(initial_value, range, LAMBDA(accum, current, formula)) - MAKEARRAY Syntax:
=MAKEARRAY(rows, cols, LAMBDA(row, col, formula)) - Example for SCAN:
=SCAN(0, B2:B6, LAMBDA(accum, current, accum + current)) - Example for REDUCE:
=REDUCE(0, B2:B6, LAMBDA(accum, current, accum + current)) - Example for MAKEARRAY:
=MAKEARRAY(5, 5, LAMBDA(row, col, row * col))
SCAN, REDUCE, and MAKEARRAY are powerful functions in Google Sheets that, when combined with LAMBDA, can help you perform complex array operations with ease. Whether you’re calculating running totals, creating custom arrays, or reducing large datasets into single values, these functions provide the flexibility and efficiency needed to manage data in dynamic and meaningful ways. Start experimenting with these functions today and elevate your Google Sheets skills to a new level of productivity!