> For the complete documentation index, see [llms.txt](https://docs.trymito.io/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.trymito.io/how-to/importing-data-to-mito/importing-from-other-sources.md).

# Importing from other sources

Import any pandas dataframe into Mito.

Because Mito works seamlessly with Pandas dataframes, with only a bit of custom code, you can get any data you want into a mitosheet.

### Importing from a database

Here, we provide some internal links for reading from common databases into Pandas dataframes:

* [MySQL](https://pynative.com/python-mysql-select-query-to-fetch-data/)
* [Oracle](https://blogs.oracle.com/connect/post/run-sql-data-queries-pandas)
* [Sqlite](https://www.sqlite.org/index.html)
* [PostgresSQL](https://naysan.ca/2020/05/31/postgresql-to-pandas/)
* etc. Simply google "Reading {database name} into pandas dataframe" to get a tutorial for your database!

After getting the data from your database into a dataframe, simply [import the dataframe](/how-to/importing-data-to-mito/importing-dataframes.md) into Mito.

### Importing from a webpage

Pandas provides an easy solution for getting data from a webpage into a pandas dataframe, which you can then pass to Mito. See a tutorial that uses the `pd.read_html` function [here.](https://pbpython.com/pandas-html-table.html)

After getting this webpage data into a dataframe, simply [import the dataframe](/how-to/importing-data-to-mito/importing-dataframes.md) into Mito.

### Other connections

If you have data from a different data source you're looking to read into Mito, the first step is to get it into a pandas dataframe. Simply google "Reading {data source} into pandas dataframe," and you will most likely find an easy three-step tutorial for doing just this.

Then, after getting the data from your data source into a dataframe, simply [import the dataframe](/how-to/importing-data-to-mito/importing-dataframes.md) into Mito to begin to work with it.

{% content-ref url="/pages/j3IxecQBTPTIPbvEu9i1" %}
[Importing Dataframes](/how-to/importing-data-to-mito/importing-dataframes.md)
{% endcontent-ref %}


---

# 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.trymito.io/how-to/importing-data-to-mito/importing-from-other-sources.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.
