> For the complete documentation index, see [llms.txt](https://docs.feathery.io/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.feathery.io/platform/document-intelligence/supported-document-types/spreadsheet-and-csv-extractions.md).

# Spreadsheet and CSV Extractions

### Getting Started

Create a Spreadsheet and CSV Extraction by going to the AI tab of your account and clicking **Create Extraction**.

1. Give your extraction a name
2. Select **Spreadsheets & CSVs** as the format

### Query Types

Use AI-driven natural language to query your documents for information.

<details>

<summary>Cell</summary>

Specify the exact cell to read data from.

**Configuration Fields:**

* **Cell** (Required) - The specific cell reference (e.g., A1, B2)
* **Sheet** (Optional) - The name of the sheet to extract from
* **Save To** (Optional) - The field the extracted value will be saved to

**Advanced Settings:**

* **Save File Name** - When enabled, saves the name of the source file where the value was extracted from

</details>

<details>

<summary>Column</summary>

Describe the column header to read data from. Will return all values in the corresponding column.

**Configuration Fields:**

* **Column** (Required) - The name or description of the column header
* **Save To** (Optional) - The field the extracted value will be saved to

**Advanced Settings:**

* **Save File Name** - When enabled, saves the name of the source file where the values were extracted from

</details>

### Managing Queries

* Use the **Add Query** button to create additional extraction queries
* Each query can be expanded or collapsed using the arrow controls
* Use the trash icon to delete unwanted queries
* Queries can be reordered using the drag handles


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# 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.feathery.io/platform/document-intelligence/supported-document-types/spreadsheet-and-csv-extractions.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.