> ## Documentation Index
> Fetch the complete documentation index at: https://docs.activeviam.com/llms.txt
> Use this file to discover all available pages before exploring further.

# Tables.infer_data_types()

<span id="atoti.tables.Tables.infer_data_types" />

> Tables.infer\_data\_types(<br />
>     *data*: [Table](https://arrow.apache.org/docs/python/generated/pyarrow.Table.html#pyarrow.Table) | [DataFrame](https://pandas.pydata.org/pandas-docs/version/3.0/reference/api/pandas.DataFrame.html#pandas.DataFrame) | [DataLoad](./atoti.data_load.DataLoad#atoti.data_load.DataLoad),<br />
>     /,<br />
> ) → [dict](https://docs.python.org/3/library/stdtypes.html#dict)\[[str](https://docs.python.org/3/library/stdtypes.html#str), DataType]

Infer data types from the passed *data*.

### Parameters

<h4 id="atoti.tables.Tables.infer_data_types.data">
  *data*
</h4>

The data from which data types should be inferred.

***

```pycon theme={"languages":{"custom":["/engine/python-sdk/0.9/languages/pycon.tmLanguage.json"]}}
>>> from datetime import date
>>> dataframe = pd.DataFrame(
...     {
...         "Id": [1, 2, 3],
...         "Name": ["Phone", "Watch", "Laptop"],
...         "Price": [849.99, 249.99, 1499.99],
...         "Date": [
...             date(2024, 11, 27),
...             date(2024, 11, 26),
...             date(2024, 11, 25),
...         ],
...     }
... )
>>> session.tables.infer_data_types(dataframe)
{'Id': 'long', 'Name': 'String', 'Price': 'double', 'Date': 'LocalDate'}
```

<Callout icon="link">
  **See also**:
  [`load()`](./atoti.Table.load#atoti.Table.load).
</Callout>