Features

In January and February we introduced a lot of updates to Datalore: we integrated the UI for publishing notebooks, released the first version of Datalore’s documentation, updated the landing page, and introduced improvements for working with files from Python code.

Last year presented an unexpected challenge for the world, one we all had to rise to. In 2020, we managed to launch Datalore Professional and deliver lots of great new features for our users. Here we’ve assembled a description of some of the most notable ones. Datalore Professional In November we launched Datalore Professional. It was designed for solving more complex tasks with larger datasets t

Though this is our final blog post of 2020, we have a bunch of new Datalore updates we’d like to share, including the results of two major studies we recently conducted.

Greetings from the Datalore team! This November we released a major update: the Professional Plan is now available for Datalore users 🚀 Read on to learn more about the future of Datalore Pro.

We have some really exciting news for you – we’ve introduced a new Datalore plan, called Datalore Professional. This new plan comes with increased processing power and added storage for even faster calculation of bigger datasets.

This September has been quite productive for our Datalore team. We’ve performed a lot of user interviews and implemented some long-awaited features to improve the user experience. And now we are happy to share the new updates with you!

We hope your summer has been amazing. For us at Datalore, the upcoming autumn season brings a new beginning, and we are happy to announce some fresh updates. Logo update Perhaps you’ve already noticed that the Datalore logo has changed. This update is symbolic of a fresh start for the team, and we hope you like it as well. A huge thanks to the JetBrains Design team for working hard on it. The pre

Datalore is an Online Data Science Notebook with smart coding assistance. Read about Datalore's features in this blogpost and get excited to try it out!

Enjoy documentation inside the Datalore Online Notebook, incorporate Ipywidgets into your projects, and learn about Markdown improvements.