The SCAN function in Google Sheets scans an array and applies a LAMBDA function to each value, moving row by row. The output is an array of intermediate values obtained at each step.

It’s hard to understand without seeing an example, so let’s do that.

The most straightforward SCAN formula is to create a running total calculation on a column of numbers.

The formula is:

Which produces this array output:

The lambda simply adds together the current running total and the new value, then returns the answer to the output array.

When all of the values from the input array have been considered, the output array is returned.

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The REDUCE function in Google Sheets turns an array input into a single value, by applying a custom LAMBDA function to each value of the input array.

It reduces an array down to a single value.

It’s best to understand through a simple example:

The formula in this example is:

The REDUCE function takes a starting value (0 in this example), an input array, and then a custom LAMBDA function.

The formula applies the custom LAMBDA function to each value in the array. In this case, it takes the current total value and adds the next value in the array to it to make a new total. This new total is passed on to the next iteration.

So this REDUCE formula calculates the cumulative total of the 5 numbers.

(And yes, this formula also gets you there:

This REDUCE was deliberately simple to show you how it works.)

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The MAP function in Google Sheets creates an array of data from an input range, where each value is “mapped” to a new value based on a custom LAMBDA function.

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The XLOOKUP function in Google Sheets is a new lookup function in Google Sheets that is more powerful and flexible than the older lookup functions like VLOOKUP or HLOOKUP.

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The LAMBDA function in Google Sheets creates a custom function with placeholder inputs, that can be reused.

The use case for the LAMBDA function is to work with other lambda helper functions, like MAP, REDUCE, SCAN, MAKEARRAY, BYROW, and BYCOL.

LAMBDA functions are also the underlying technology for Named Functions, which are hugely useful.

LAMBDA functions themselves are challenging to use and not very intuitive compared to regular functions.

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