News

In the past few months, we’ve been working hard on improving the data exploration and collaboration workflows in Datalore. In this blog post, we’ll give you an overview of what’s new!

Check out the newest data exploration features and enjoy the upgraded interactive reporting experience in Datalore Enterprise 2022.1.

We talk and write a lot about sharing in Datalore as we truly believe in the collaborative nature of data workflows. Today we are happy to introduce a new feature for the result sharing workflow – publishing of Interactive reports.

What are the most common ways to query SQL databases from a Python notebook? They might include using Python SQL libraries such as PySQL or SQLAlchemy... We can now suggest a more effective method: combine native SQL cells and Python code in Datalore notebooks.

It’s already 2022, and we are here with the first newsletter of the year! Read on to learn what the Datalore team has been up to recently.

The focus of this release was to make it easy for data scientists to share their work and to facilitate fetching data from databases with SQL. Read on for the highlights of this release!

Greetings from the Datalore team! Exciting news for those of you who love more than just Python: Datalore now also supports R and Scala notebooks! Read on to learn more about the updates. R and Scala support Although Python is the most popular language in data science, R and Scala also do a great job for data science tasks and have a rich user community. That’s why we added support for S

Greetings from the Datalore team! Does the #Tesla stock price depend on Elon Musk’s mood? In this newsletter, we’ll share a new tutorial for sentiment analysis and talk about the new features that can improve your daily workflow in Datalore. Chart cells Could you imagine that working with visualizations in Python would be as easy as it is in spreadsheets? Last month we took a step further

We have been busy this month laying the foundations for future features. This work will enable us to take some big steps with Datalore over the coming year.

We believe that Jypyter notebooks could become a great presentation and reporting tool. Read on to learn how Datalore makes notebooks more friendly for non-tech people.

Read this blog post to learn about how we improved the plotting workflow, integrated Terminal and Pip package manager, and adjusted the features on the Community plan.

For the last month, we’ve been working on implementing a frequent user request to export notebooks into different types of files and to share code on other platforms. You might have also already noticed that the look of the editor has changed a bit. Read on to learn more about the recent updates in Datalore 👇🏻