Image by Adam Evertsson from Pixabay

Datalore by Jetbrains

An Alternative To Google Colab and Jupyter Notebook

Jupyter Notebook

Anyone who works with data makes use of Jupyter notebooks. It is an open-source web application that joins code, output, visualizations, and text. It also organizes your work. Using a Jupyter notebook is a smart solution for individual projects.

Collaborative Notebooks

Anytime you have a project as a team, you need a collaborative tool for real-life collaboration, peer review, or feedback. Google Colab or Kaggle Kernels will help you a lot by making collaboration easier and giving you free or cheap GPU. In this article, I will introduce you to a new notebook called Datalore by JetBrains.

Datalore

Datalore is an online computational notebook that created to be a collaborative experience. It brings Pycharm’s IDE, Jupyter Notebook’s design and flexibility, and Google Colab’s collaboration power in one place. It has a great code completion tool that understands the code and helps you with the syntax.

Image by Author using Jupyter, Colab, PyCharm, and Datalore icons.

Getting Started With DataLore

Screenshot by Author from Datalore

You can register Datalore and start to use it in a few seconds with an email address.

Pre-installed Libraries

In Datalore, all of the common libraries are installed. It means you don’t need to install the standard libraries before you start a project.

Library Manager

If you are going to use a specific library that doesn’t come preinstalled with Datalore, you can quickly install a library using the below steps.

  1. Go to Tools → Library Manager → Explore
  2. Search the library you want to install.
  3. Click install.

Attaching Files

While working on a Datalore notebook, you can attach data files and do the data analysis on the notebook. Most of the commonly used datasets are also provided.

Sheets In Notebooks

Similar to Microsoft Excel, you can add more sheets and organize your data science projects. You can have one notebook and several sheets for data cleaning, exploratory data analysis, model training, and performance evaluation.

Editing Notebooks

You can edit notebooks by the buttons and by keyboard shortcuts. Running, inserting, deleting cells, changing the types of cells, moving cells up and down are shown in the below gif animation.

Gif

LaTeX Support In Markdown Cells

Live Computation!

You can separate the notebook into two by View → Split View and see the results of your code by switching from the IPthon kernel to the Datalore kernel which provides you real-time computation.

Code Completion

JetBrains’ code insights make a coder’s life easier in all the IDEs. Datalore brings PyCharm’s excellent code completion, quick fixes, and auto imports to the notebook environment.

More To Discover

If you are interested in Datalore, there are more to discover: Sharing notebooks publicly or privately, publishing notebooks, commenting on published static HTML pages, variable viewer, table of contents, dark theme, etc.

Conclusion

You can use Datalore for both individual and group projects and use its paid GPU machines for larger computations.

I demonstrated some of the cool properties that come with the Datalore collaboration environment. Hope you enjoy it.

Contact me

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Any suggestions and comments will be very appreciated!

Data Scientist, Data Educator, Blogger https://www.linkedin.com/in/seyma-tas/

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