> For the complete documentation index, see [llms.txt](https://docs.sdv.dev/sdv/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/sdv/integration/local/additional-file-formats.md).

# Additional File Formats

## Do you have data in other formats?

The SDV uses the [pandas library](https://pandas.pydata.org/) for data manipulation and synthesizing. If your data is in any other format, load it in as a [pandas.DataFrame](https://pandas.pydata.org/docs/reference/api/pandas.DataFrame.html) object to use in the SDV. For multi table data, make sure you format your data as a dictionary, mapping each table name to a different DataFrame object.

```python
data = {
    'table_name_1': <pandas.DataFrame>,
    'table_name_2': <pandas.DataFrame>,
    ...
}
```

Pandas offers many methods to load in different types of data. For example: [SQL table](https://pandas.pydata.org/docs/reference/api/pandas.read_sql_table.html#pandas.read_sql_table) or [JSON string](https://pandas.pydata.org/docs/reference/api/pandas.read_json.html#pandas.read_json).

```python
import pandas as pd

data_table_1 = pd.read_json('file://localhost/path/to/table_1.json')
data_table_2 = pd.read_json('file://localhost/path/to/table_2.json')
```

For more options, see the [pandas reference](https://pandas.pydata.org/docs/reference/io.html).


---

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