# Overview of Datalore features These features help you get the most out of the application. Some features may be subject to restrictions based on the selected plan. For more details, visit the [Datalore Plan overview](https://www.jetbrains.com.cn/en-us/datalore/buy/) page. Coding productivity : * [AI Assistant](ask-ai.html) feature supports code generation and modification via commands in natural language. : : * [Coding assistance](coding-assistance.html) provides auto-completion, quick-fixes, and quick reference. : : * [Ready-to-use environment](environment.html) allows you to start quickly with pre-installed Python packages. You can choose between pip and Conda package managers. : : * [Automatic plotting](automatic-plotting.html) helps you quickly generate visualizations for your DataFrames. : : * [Terminal](terminal.html) can be used to execute `.py` scripts and run sudo commands. : : * [Statistics tab](statistics-tab.html) provides detailed metrics on your DataFrames. : : * [Variable viewer](variable-viewer.html) grants quick access to all variables and their values used in your notebook. : : * [Scheduling](scheduling.html) 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 : * [Attached data](data.html) is a tool used to upload and manage files and folders for your notebooks. All data stays persistent and is stored in the cloud. : : * [Cloud storage connections](use-s3-buckets.html) (Amazon S3, GCS, SMB/CIFS folders) can be mounted directly inside your notebooks. : : * [Environment variables](environment-variables.html) is a feature that ensures security of your credentials. : : * [Table viewer](table-viewer.html) allows viewing `.csv` and `.tsv` files from Attached data. Git integration : * [Importing a Git repository](import-workspace-from-git-repository.html) allows you to create a workspace in Datalore based on a Git repository. : : * [Adding a Git repository to workspace resources](git-reps-in-workspace.html) enables you to use it as a Python library with a setup.py file in it across all notebooks of this workspace. : : * [Access Git repositories via Terminal](use-terminal-for-git-integration.html) to use their data in your notebooks. Editor : * [Table of contents](table-of-contents.html) ensures easy navigation through your notebooks. : : * [Command palette](feedback-and-reference-options.html#palette) and [shortcuts](feedback-and-reference-options.html#shortcuts) provide quick access to all editor operations. : : * [View](customize-the-editor.html) menu allows you to configure the appearance of your editor and notebook cells. : : * [Reactive mode](kernel-management.html) 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](interactive-control-cells.html) help you quickly customize the output without manually changing the code. : : * [Chart cells](chart-cells.html) are specifically used to build multilayered charts based on datasets of any size. The feature also facilitates collaborative work. : : * [Background computation](instance-types.html#long-computation) keeps the computation running after the tab is closed with a cut-off timer option. : : * [Use the Computation tool](computation-tab.html) helps you manage kernels, machines, and notebook runs from one place. : : * [Interactive table output](interactive-table-output.html) ensures interaction with table outputs (sorting, resizing, column renaming, scrolling, etc). : : * [Metric cells](metric-cells.html) allow you to track numerical values and compare them to others. : : * [Export to database](export-to-database.html) cells are used to append DataFrames to tables attached to your notebooks. Collaboration : * [Sharing](share-a-notebook.html) allows your team to edit notebooks in real time. : : * [Report builder](report-builder.html) provides interface for preparing and publishing static and interactive reports. : : * [Workspaces](datalore-workspaces.html) are used to organize your notebooks into collections with datasets that are shareable across teams and notebooks. : : * [History](history.html) is a tool for recording and tracking changes in your notebooks with the option of reverting to previous states. : : * [Comments](comments.html) is an efficient tool to improve your team communication on notebooks and reports. Presentation and communication : * [Markdown](markdown-cells.html) cells support LaTex to help you better describe your code. : : * [Embedding](static-reports.html) code cells is a quick way to demonstrate your Datalore work on social networks and other platforms. : : * [Exporting notebooks, workspaces, and reports](export.html) is supported for a number of file extensions: PDF, PY, HTML, IPYNB. ## Datalore On-Premises (previously called Datalore Enterprise) This solution offers full Datalore functionality and the special features listed below. * On-premises hosting * Advanced customization options * Teamwork-oriented solutions * [Interactive reports](interactive-reports.html) [Datalore On-Premises official page](https://www.jetbrains.com.cn/en-us/datalore/enterprise/)