Workspace | Creating a workspace

Creating a workspace

There are three ways to create a workspace: create a blank Python or R workspace, create a workspace from one of DataCamp's curated templates, or create a workspace from a (public) GitHub repository.

Creating a blank Python or R workspace

  1. From the workspace dashboard, select New Python Workspace or New R Workspace. A new workspace opens up with a blank notebook.
    • Python workspaces will open up in DataCamp's editor (with the option to switch the editor to JupyterLab), with a blank Jupyter notebook.
    • R workspaces will open up in RStudio, with a blank R Markdown notebook.
  2. You decide what you do next: you can upload a dataset, connect to an external data source, build a data visualization. If you're not sure how to start, you can consider starting from a dataset or a template, as explained in the next sections.

Creating a workspace from a dataset

DataCamp provides a rich and growing collection of intriguing datasets to analyze; the workspace you create through this way will contain all the necessary data pre-configured and a brief description, so you can dive in immediately.
To create a workspace from a DataCamp dataset
  • From the Workspace dashboard, select Datasets in the sidebar.
  • Select a dataset you're interested in. A dialog box displays. It provides an preview of the selected dataset including a data dictionary and a link to the dataset source, possible choice of language (Python or R), and an overview of Publications that other Workspace users created with this dataset.
  • Select Use Dataset. A new workspace opens up with the data and a basic notebook pre-configured so you can start your analysis.

Creating a workspace from a template

In addition to datasets, DataCamp also provides a wide range of templates that contain pre-written code to solve common data science tasks, going from simple things like merging two data frames, all the way up to larger problems such as training a decision tree classifier for making predictions.
To create a workspace from a DataCamp template:
  1. From the Workspace dashboard, select Templates in the sidebar.
  2. Select a template you're interested in. A dialog box displays. It provides an preview of the selected template, possible choice of language (Python or R), and an overview of Publications that other Workspace users created with this template.
  3. Select Use Template. A new workspace opens up with the data and all of the template's content loaded so you can continue working on it: you can hook up your own dataset, you can tweak the template's content, you can add more steps to the analysis; anything goes!
 
Creating a workspace from a (public) GitHub repository
Lots of interesting analyses live in GitHub repositories. DataCamp Workspace allows you to easily create a new DataCamp Workspace from any public GitHub repository.
  1. From the dashboard, select From GitHub Repository.
  2. Enter the URL or repository name and select the technology (Python or R) that you want to associate with the files.
  3. A new workspace opens up that includes all the files in the specified repository.

Personal and group workspaces

By default, all workspaces you create will live under your personal account. You can see this by checking the account selector in the workspace sidebar:
 
Workspaces that live in your personal account:
  • Are private by default, but can be shared as described in Sharing a workspace.
  • Can connect your personal integrations.
If you are a member of one or more DataCamp groups, you can also create workspaces inside this group. To do so, click the account selector dropdown and select a group. Workspaces you now create through one of the ways outlined above:
  • Can easily be shared with other group members (rather than having to share with every group member individually)
  • Can connect to your group's integrations.