Datalore 2024.2 Help

Overview of Datalore features

These features help you get the most out of the application. For more details, visit the Datalore Features overview page.

Coding productivity
  • Coding assistance provides auto-completion, quick-fixes, and quick reference.

  • Ready-to-use environment allows you to start quickly with pre-installed Python packages. You can choose between pip and Conda package managers.

  • Automatic plotting helps you quickly generate visualizations for your DataFrames.

  • Terminal can be used to execute .py scripts and run sudo commands.

  • Statistics tab provides detailed metrics on your dataframes.

  • Variable viewer grants quick access to all variables and their values used in your notebook.

  • Scheduling allows you to run your notebooks at selected intervals (hourly, daily, weekly, or monthly). You can set up multiple or parameterized schedules for one notebook.

  • Supported languages: Python, R, Scala, Kotlin

Data access
Editor
  • Table of contents ensures easy navigation through your notebooks.

  • Command palette and shortcuts provide quick access to all editor operations.

  • View menu allows you to configure the appearance of your editor and notebook cells.

  • Reactive mode enables live computation. When you change code in one cell, the kernel automatically recalculates all the dependent cells without you manually running them.

  • Interactive controls help you quickly customize the output without manually changing the code.

  • Chart cells are specifically used to build multilayered charts based on datasets of any size. The feature also facilitates collaborative work.

  • Background computation keeps the computation running after the tab is closed with a cut-off timer option.

  • Computation tab helps you manage kernels, machines, and notebook runs from one place.

  • Interactive table output ensures interaction with table outputs (sorting, resizing, column renaming, scrolling, etc).

  • Metric cells allow you to track numerical values and compare them to others.

  • Export to database cells are used to append dataframes to tables attached to your notebooks.

  • Ask AI feature supports code generation and modification via commands in natural language.

  • Comments allow you and your teammates collaborate more productively on your projects by commenting individual notebook cells.

Collaboration
  • Sharing allows your team to edit notebooks in real time.

  • Report builder provides interface for preparing and publishing static and interactive reports.

  • Workspaces are used to organize your notebooks into collections with datasets that are shareable across teams and notebooks.

  • History is a tool for recording and tracking changes in your notebooks with the option of reverting to previous states.

  • Comments is an efficient tool to improve your team communication on notebooks and reports.

Presentation and communication
  • Markdown cells support LaTex to help you better describe your code.

  • Embedding code cells is a quick way to demonstrate your Datalore work on social networks and other platforms.

  • Exporting notebooks is supported for a number of file extensions: PDF, PY, HTML, IPYNB.

Professional features

In addition to what is listed above, Datalore Professional provides a number of other features. Here are just a few of them:

  • Database integration is an interface that allows you to set up database connections to your notebooks and use retrieved data via the SQL cell type.

  • Powerful CPU and GPU machines

  • Unlimited Background computation feature

  • Unlimited number of users with edit access to shared notebooks

  • Unlimited notebooks running in parallel

  • Machine CPU and GPU prepaid options

Datalore Enterprise

  • On-premises hosting

  • Advanced customization options

  • Teamwork-oriented solutions

  • Interactive reports

Datalore Enterprise official page

Last modified: 17 May 2024