This page showcases a set of sample Jupyter notebooks that illustrate how to use Studio APIs.

These notebooks are designed to be copied, forked and reused, and are being made available as follows:

| Service | Description |
| --- | --- |
|  | All sample notebooks are provided in open source form under the MIT license on [GitHub](https://github.com/foursquare/fsq-studio-sdk-examples/tree/master/python-notebooks). |
|  | All sample notebooks on this page can be run directly in your browser via the [Binder](https://mybinder.org/v2/gh/foursquare/fsq-studio-sdk-examples/master?urlpath=lab/tree/python-notebooks/) service. _(Note: It can take take a minute for the Jupyter environment on Binder to start a notebook, however once a notebook is loaded you can fully interact with it in the browser.)_ |
|  | All sample notebooks on this page (except Plotly Cross-filtering) can be run directly in your browser via [Google Colab](https://colab.research.google.com/assets/colab-badge.svg). |

# Map SDK Samples
A number of sample notebooks that show how to work with Studio maps using the Map SDK:

| **Notebook** | **Preview** |
| --- | --- |
| ### Introduction<br> Create Studio map, add a dataset, and set the map view. <br> |  |
| ### Local Maps<br> Use local Studio maps to visualize Dataframes, GeoJSON, and CSV. <br> |  |
| ### Layers<br> Add and control map layers. <br> |  |
| ### Filters<br> Control filters and listen to filter change events. <br> |  |
| ### Timeline<br> Control map filters and listen to filter change events. <br> |  |
| ### Event Handling<br> Interactivity, click and hover events. <br> |  |

### Integration Notebooks
The sample notebooks in this section illustrate how to integrate the Map SDK with other notebook packages and workflows.

| **Notebook** | **Preview** |
| --- | --- |
| ### Plotly Cross-filtering<br> Synchronize Studio map filters with [`plotly`](https://plotly.com/python/) charts. <br> |  |
| ### TensorFlow Prediction<br> Visual prediction analysis using TensorFlow. <br> |  |
| ### PyTorch Prediction<br> Bike share trip duration prediction using PyTorch. <br> |  |
| ### Kuwala Correlation<br>Correlating against [Kuwala](https://kuwala.io/) data feeds. <br> |  |

# Use Case-focused Notebooks
The sample notebooks in this section illustrate how to use the Map SDK for analytics targeting specific use cases.

| **Notebook** | **Preview** |
| --- | --- |
| ### Suitability Analysis<br> Site Selection / New Venue Location. <br> |  |