These are Datalore features that help you get the most out of the application. For more details, visit this 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).
- Data access
Attached data is a tool used to upload and manage files and folders for your notebooks. All data stays persistent and is stored in the cloud.
Bucket data sources can be mounted directly inside your notebooks.
Secrets is a feature that ensures security of your credentials.
Table viewer allows to view .csv and .tsv files from Attached data.
Table of contents ensures easy navigation through your notebooks.
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.
Visibility control cells allow to collapse other cells in interactive reports.
Computation tab helps you manage kernels, machines, and notebook runs from one place.
- Presentation and communication
Publishing allows you to create reports based on your notebooks and share them using links.
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.
In addition to what is listed above, Datalore Professional provides a number of other features. Here are just a few of them:
Powerful CPU and GPU machines
Unlimited Background computation feature
Unlimited number of users with edit access to shared notebooks
Unlimited notebooks running in parallel
Advanced customization options