> For the complete documentation index, see [llms.txt](https://docs.sdv.dev/rdt/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.sdv.dev/rdt/transformers-glossary/deep-data-understanding/email/domainextractor.md).

# ＊ DomainExtractor

{% hint style="info" %}
**＊SDV Enterprise Feature.** This feature is available to our licensed users and is not currently in our public library. For more information, visit our page to [Explore SDV](https://docs.sdv.dev/sdv/explore/sdv-enterprise/compare-features).
{% endhint %}

The `DomainExtractor` extracts domains from emails so that they can be used later for data science. It keeps the original emails so that the same exact emails can be recovered during the reverse transform.

<figure><img src="https://2225246359-files.gitbook.io/~/files/v0/b/gitbook-x-prod.appspot.com/o/spaces%2FVGX92M819eIp0rMg5elc%2Fuploads%2FeyNBdRcFDJG9kAPR0xEs%2Frdt_transformers-glossary-deep-data-understanding-email-domain-extractor_June%2002%202025.png?alt=media&amp;token=70e0bffc-6812-4614-ad4a-0964e2b2af00" alt=""><figcaption></figcaption></figure>

```python
from rdt.transformers.email import DomainExtractor

transformer = DomainExtractor()
```

## Parameters

**`extracted_domain`**: Which parts of the overall email domain to extract during the transformation phase

<table data-header-hidden><thead><tr><th width="186"></th><th></th></tr></thead><tbody><tr><td>(default) <code>'full'</code></td><td>Extract the full domain, which is everything after the <strong>@</strong> sign. For example if the email is <code>'info@datacebo.com'</code>, the full domain is <code>'datacebo.com'</code>.</td></tr><tr><td><code>'top'</code></td><td>Extract only the top domain, which is everything after the <strong>.</strong> character. For example if the email is <code>'info@datacebo.com'</code>, the top domain is <code>'com'</code>.</td></tr></tbody></table>

### Examples

```python
from rdt.transformers.email import DomainExtractor

transformers = DomainExtractor(extracted_domain='top')
```


---

# 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 by asking a question.

Perform an HTTP GET request on the following URL with the `ask` and `goal` query parameters:

```
GET https://docs.sdv.dev/rdt/transformers-glossary/deep-data-understanding/email/domainextractor.md?ask=<question>&goal=<user_goal>
```

`ask` is the immediate question: it should be specific, self-contained, and written in natural language.
`goal` is what the user is ultimately trying to achieve, the reason they need the answer. Sharing it helps GitBook give you a better, more relevant answer. A goal is most helpful when it describes the outcome the user wants rather than restating the question. For example, with `ask=how do I create an API token`, a goal like `automate deployments from our CI pipeline` lets GitBook tailor the answer to that use case.

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.
