Example Notebooks
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. | |
| All sample notebooks on this page can be run directly in your browser via the Binder 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. |
Map SDK Samples
A number of sample notebooks that show how to work with Studio maps using the Map SDK:
| Notebook | Preview |
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| ### Introduction Create Studio map, add a dataset, and set the map view. |
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| ### Local Maps Use local Studio maps to visualize Dataframes, GeoJSON, and CSV. |
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| ### Layers Add and control map layers. |
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| ### Filters Control filters and listen to filter change events. |
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| ### Timeline Control map filters and listen to filter change events. |
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| ### Event Handling Interactivity, click and hover events. |
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 Synchronize Studio map filters with plotly charts. |
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| ### TensorFlow Prediction Visual prediction analysis using TensorFlow. |
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| ### PyTorch Prediction Bike share trip duration prediction using PyTorch. |
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| ### Kuwala Correlation Correlating against Kuwala data feeds. |
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 Site Selection / New Venue Location. |