Announcing Datalore Enterprise – The Smart and Secure Jupyter Environment for Data Science Teams

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.

Greetings from the Datalore team! Jupyter notebooks can get messy. Perhaps you have tried different things in one notebook, or maybe you have chunks of outdated code and variable declarations all over the place. This isn’t necessarily a sign that something is wrong. Rather, the tool was designed to allow you to work this way. For the last 3 years, our Datalore team has been experimenting wit

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.

Jupyter notebooks are arguably the most widely used tool in data science. However, when it comes to collaboration, resource management, and security...

Here’s how we used the hundreds of thousands of publicly accessible repos on GitHub to learn more about the current state of data science.