> For the complete documentation index, see [llms.txt](https://docs.quadratichq.com/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.quadratichq.com/formulas/let-and-lambda.md).

# LET & LAMBDA

## LET & LAMBDA

Quadratic supports Excel's modern formula-composition functions, letting you name intermediate values and define custom functions inline.

### LET

`LET(name1, value1, ..., calculation)` defines named values inside a formula, then uses them in a final calculation. It improves readability and avoids repeating expressions.

```
=LET(revenue, SUM(Sales[Amount]), cost, SUM(Costs[Amount]), revenue - cost)
```

### LAMBDA

`LAMBDA(param1, ..., calculation)` defines a reusable custom function inline. Combine it with array functions — `MAP`, `REDUCE`, `BYROW`, `BYCOL`, `SCAN`, and `MAKEARRAY` — to apply custom logic across ranges:

```
=MAP(A1:A10, LAMBDA(x, x * 1.08))
```

```
=REDUCE(0, B1:B20, LAMBDA(acc, v, acc + MAX(v, 0)))
```

### ISOMITTED

Inside a `LAMBDA`, `ISOMITTED(argument)` returns `TRUE` if an optional argument was not supplied — useful for default values.

### STOCKHISTORY

Quadratic also supports the Excel-compatible `STOCKHISTORY` function for retrieving historical stock prices directly in the sheet:

```
=STOCKHISTORY("AAPL", "2025-01-01", "2025-12-31")
```

For richer financial data — fundamentals, statements, news, technical indicators — see Financial data in Python.

For the full function reference, see Functions and operators.


---

# Agent Instructions
This documentation is published with GitBook. GitBook is the documentation platform designed so that both humans and AI agents can read, navigate, and reason over technical content effectively. Learn more at gitbook.com.

## Querying This Documentation
If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question.

Perform an HTTP GET request on the current page URL with the `ask` query parameter, and the optional `goal` query parameter:

```
GET https://docs.quadratichq.com/formulas/let-and-lambda.md?ask=<question>&goal=<endgoal>
```

`ask` is the immediate question: it should be specific, self-contained, and written in natural language.
`goal` is optional and describes the broader end goal you are ultimately trying to accomplish on behalf of the user. GitBook uses it to tailor the answer towards what is most useful for that goal.

The response will contain a direct answer to the question and relevant excerpts and sources from the documentation.

Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.