Constructed-in Jupyter notebooks in Azure Cosmos DB at the moment are accessible

Earlier this yr, we introduced a preview of built-in Jupyter notebooks for Azure Cosmos DB. These notebooks, working inside Azure Cosmos DB, at the moment are accessible.

Overview of built-in Jupyter notebooks in Azure Cosmos DB.

Cosmic notebooks can be found for all knowledge fashions and APIs together with Cassandra, MongoDB, SQL (Core), Gremlin, and Spark to reinforce the developer expertise in Azure Cosmos DB. These notebooks are immediately built-in into the Azure Portal and your Cosmos accounts, making them handy and simple to make use of. Builders, knowledge scientists, engineers and analysts can use the acquainted Jupyter notebooks expertise to:

  • Interactively run queries
  • Discover and analyze knowledge
  • Visualize knowledge
  • Construct, prepare, and run machine studying and AI fashions

On this weblog publish, we’ll discover how notebooks make it simple so that you can work with and visualize your Azure Cosmos DB knowledge.

Simply question your knowledge

With notebooks, we’ve included built-in instructions to make it simple to question your knowledge for ad-hoc or exploratory evaluation. From the Portal, you should utilize the %%sql magic command to run a SQL question towards any container in your account, no configuration wanted. The outcomes are returned instantly within the pocket book.

SQL query using built-in Azure Cosmos DB notebook magic command.

Improved developer productiveness

We’ve additionally bundled in model four of our Azure Cosmos DB Python SDK for SQL API, which has our newest efficiency and usefulness enhancements. The SDK can be utilized immediately from notebooks with out having to put in any packages. You may carry out any SDK operation together with creating new databases, containers, importing knowledge, and extra.

Create new database and container with built-in Python SDK in notebook.

Visualize your knowledge

Azure Cosmos DB notebooks comes with a built-in set of packages, together with Pandas, a preferred Python knowledge evaluation library, Matplotlib, a Python plotting library, and extra. You may customise your setting by putting in any package deal you want.

Install custom package using pip install.

For instance, to construct interactive visualizations, we are able to set up bokeh and use it to construct an interactive chart of our knowledge.

Histogram of data stored in Azure Cosmos DB, showing users who viewed, added, and purchased an item.

Customers with geospatial knowledge in Azure Cosmos DB also can use the built-in GeoPandas library, together with their visualization library of option to extra simply visualize their knowledge.

Choropleth world map of data stored in Azure Cosmos DB, showing revenue by country.

Getting began

  1. Observe our documentation to create a brand new Cosmos account with notebooks enabled or allow notebooks on an current account. Create account with notebooks or enable notebooks on existing account in Azure portal.
  2. Begin with one of many notebooks included within the pattern gallery in Azure Cosmos Explorer or Knowledge Explorer.Azure Cosmos DB notebooks sample gallery.
  3. Share your favourite notebooks with the neighborhood by sending them to the Azure Cosmos DB notebooks GitHub repo.
  4. Tag your notebooks with #CosmosDB, #CosmicNotebooks, #PoweredByCosmos on social media. We’ll characteristic the perfect and hottest Cosmic notebooks globally!

Keep up-to-date on the newest Azure #CosmosDB information and options by following us on Twitter or LinkedIn. We’d love to listen to your suggestions and see your finest notebooks constructed with Azure Cosmos DB!

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