Hit the Ground Running With Pandas

DataSpell 2022.3.2 brings you fixes to ensure that Jupyter Notebooks are consistently reloaded from disk and that your typing doesn’t get stuck in reverse.

Get a fix for interpreter widget woes, an uninterrupted onboarding tour, simplified settings sync and code completion for column names in Python scripts.

DataSpell 2022.3 has been released! The most important new features include: - Remote development via SSH - Remote Jupyter debugging - Automatic tracking of important code changes - Enhanced DataFrame interactivity - In-line data about Jupyter variables

The second EAP build for DataSpell 2022.3 contains some exciting new features, including two highly requested additions: the ability to configure a remote interpreter using SSH and debugging for Jupyter notebooks running on remote machines. In addition, we’ve greatly expanded the options for working with DataFrames, including by making improvements to how you can display and export your data. Finally, we’ve added enhancements to help with coding, such as autocompletion for pandas column names when using Python scripts and Data Vision, which displays helpful in-line information about variables.

DataSpell 2022.2.3 implements an important fix – editing the search query no longer results in cell code deletion. There are also more improvements to the notebook editor in this build. Read on to learn more. You can download the new version from our website, update directly from the IDE, update via the free Toolbox App, or use snaps for Ubuntu. DOWNLOAD DATASPELL 2022.2.3 The Terminal now respects the Python environment In DataSpell you can set up a dedicated Python environment for any folder you attach to the workspace.  In earlier versions, when you opened the built-in

In the first EAP build for DataSpell 2022.3, you will find the ability to track and revert changes made to Jupyter notebooks, as well as a better in-editor experience for formatting multiline code blocks in Jupyter notebooks and searching within them. This first build also enriches support for web outputs by making it possible to use the Output widget.  Please give the new functionality a try and share your feedback! The Toolbox App is the easiest way to get the EAP builds and keep your stable and EAP versions up to date. You can also manually download the EAP builds from our we

DataSpell 2022.2.2 introduces enhancements for the Python interpreter selector, addresses a bug affecting the display of image outputs in the Python Console, and fixes the way metadata from externally created notebooks is handled.  You can download the new version from our website, update directly from the IDE, update via the free Toolbox App, or use snaps for Ubuntu. DOWNLOAD DATASPELL 2022.2.2 Python interpreter selector DataSpell has an Interpreter selector in the bottom right-hand corner of the IDE that helps you see and change the Python interpreter you are currently wo

Get up and running with version control using Git when working with Jupyter notebooks.

The first minor update to DataSpell 2022.2 brings the ability to copy-paste directories between your local machine and remote Jupyter servers, as well as better rendering for Markdown and HTML tables in the Jupyter editor. Let’s take a closer look! You can download the new version from our website, update directly from the IDE, update via the free Toolbox App, or use snaps for Ubuntu. Copy-paste directories between the local machine and the remote Jupyter server You can now copy-paste both files and directories from your local machine to remote Jupyter servers, and vice versa. To

DataSpell 2022.2 is here and ready to give your data science work an efficiency boost. Merging diverged notebooks is now straightforward with the visual merge tool, as DataSpell 2022.2 allows you to review them as two notebooks open side by side, highlighting the changes in the cells. Support for WSL allows you to create WSL-based projects as well as interpreters and to work in the Python console and the terminal directly in DataSpell. Code insight for your Python and Jupyter files is provided too.

Learn more about using Windows Subsystem for Linux with Jupyter Notebooks, including how to run Python code from Windows using Linux.