| id | integration-with-data-libraries |
|---|---|
| title | Integrate with data libraries |
| description | Load Apify dataset items into Pandas DataFrames for analysis. |
import Tabs from '@theme/Tabs'; import TabItem from '@theme/TabItem'; import CodeBlock from '@theme/CodeBlock';
import PandasAsyncExample from '!!raw-loader!./code/04_pandas_async.py'; import PandasSyncExample from '!!raw-loader!./code/04_pandas_sync.py';
The Apify client for Python seamlessly integrates with data analysis libraries like Pandas. This allows you to load dataset items directly into a Pandas DataFrame for efficient manipulation and analysis. Pandas provides robust data structures and tools for handling large datasets, making it a powerful addition to your Apify workflows.
The following example shows how to retrieve items from the most recent dataset of an Actor run and load them into a Pandas DataFrame for further analysis:
{PandasAsyncExample} {PandasSyncExample}