At any time when I conduct coding workshops or tutorials, Google Colaboratory Notebooks — or Colab, because it is more commonly known — stays my go-to resource. It removes the trouble of environment setup for each presenters and attendees, moreover offering free access to powerful computing resources like GPUs and TPUs. With its easily shareable links, Colab makes your entire learning process more efficient and effective. To benefit from what Colab has to supply, I consistently regulate its latest releases and updates.

While I typically share these updates through LinkedIn occasionally, the extensive list of recent and enhanced features deserves a more comprehensive article like this one. My previous compilation of Colab’s significant features was in 2022, indicating it’s time for an updated overview.

Let’s delve into a number of the standout features of Colab which were invaluable in my work. I hope you discover them equally helpful.

Now, when users paste data into an empty code cell, Colab routinely generates code to create a pd.DataFrame. This enhancement eliminates the additional steps traditionally involved on this process, making it a seamless user experience.

And that’s not all — if there’s already text in a code cell, Colab thoughtfully adds the CSV literal for you.

Data visualization in Colab is now more accessible with its recent feature → the automated generation of plots from Pandas DataFrames. If you execute a code cell that concludes with a DataFrame reference, an auto-plotting button materializes on the…