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DataCamp Workspace

Analyze data any time, anywhere

Share your data analysis in a cloud-based environment—no installation required.

Get Started For Free

Workspace supports R, Python and SQL and is available on Mac, Windows, and Linux.

What is DataCamp Workspace?

Workspace is a collaborative cloud-based notebook that allows you to analyze data, collaborate with your team and share insights. Workspace is designed to take you from learning data science to doing data science. And with built-in datasets, you can start analyzing data within minutes.

Get a step ahead with ready-to-use datasets 

Ready to put your skills into practice but don’t have a dataset to work on? Choose from our curated library of datasets to analyze in Workspace. Plus, with all the necessary data and packages included, you can save on setup time and share insights sooner.

Explore Our Datasets

Must have templates

Our templates give you access to pre-written code so you can build visualizations and reports faster than ever—saving you hours from writing repetitive code.

Explore Our Templates

Get moving faster with better collaboration

We created Workspace to help individuals and teams be more productive. We’ve made it easy to edit, comment, and share like you would in Google Docs. With our one-click publishing tool, any of your data projects can be shared while staying in control of who gets to see them. 

Share your vision with captivating data visualizations

Bar charts? Check. Multi-dimensional time series plots? Check. Whatever story you’re trying to tell with your data, Workspace has you covered. Our data science notebooks support all common Python and R data visualization libraries.

Analyze your own data

Want to connect your data? Seamlessly and securely access your data through native SQL integrations.

Explore Workspace Integrations

Create a shareable data science portfolio

There is no better way to display your data skills to the world as with actual examples. Use your public DataCamp profile as an up to date portfolio of your best workspace reports and analysis.

Trust matters to us

Keeping your data science notebooks secure is a top priority for us. DataCamp is ISO 27001:2017 certified and implements safeguards to secure all your data science work. 

Photo of Sanjay N

‘‘Through Workspace, I've been able to apply my learnings and take my skills to the next level.”

Sanjay N, Computer Science Student

Explore analyses published by others using Workspace

Divvy 2021 Bike Sharing

Explore a dataset to understand how casual riders and annual members use Divvy bikes different. 

Oscar Herrada HeadshotOscar Herrada

Forest Fires Analysis

This dataset consists of an analysis on forest fires in Turkey, yearly and total percentages. 

Hakan Ozler HeadshotHakan Ozler

Victorian Electricity Project

This project analyzes historical data on energy prices to inform future contract negotiations and storage venture profitability. 

Nikki S HeadshotNikki S

Heat Distribution in Petri Dish Heater

This is a visualization of the experimental and simulated values of the temperature in the centre of a homemade Petri dish heater.

Jorge Rodríguez Ramos HeadshotJorge Rodríguez Ramos

Water Quality

This project investigates whether we can predict if a household switches wells based on environmental variables (i.e. arsenic levels)

Richard Pallangyo HeadshotRichard Pallangyo

Data Visualization in Python

This publication covers different ways to visualize data in Python.

Ramnath Vaidyanathan HeadshotRamnath Vaidyanathan
See more
Photo of Richard Pallangyo

‘‘The ability to create a portfolio was the biggest advantage of using Workspace.”

Richard Pallangyo, Data Science Enthusiast

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FAQ

What are data science notebooks?

A data science notebook is a collection of text and code cells tools in a document-like layout that data scientists use to write and execute code and create visualization, but also to give color to their insights in plain language. This way, both the text and code live in one and the same document. Workspace uses the notebook as the default file format, and makes it easy to collaborate in and share notebooks.

What is an online IDE?

An online IDE allows you to write, run and share your data science code online. With an online IDE, there is no need to install any software on your local computer.

How does Workspace differ from other IDEs for Python?

Workspace is completely pre-configured, with recent versions of Python, R, SQL and the latest versions of a slew of commonly used packages pre-installed. Combined with Workspace's collection of ready-to-use datasets and templates, you can start your analysis in no time. In addition to that, Workspace has native SQL support built-in, allowing you to query databases without ever leaving your Workspace environment. Finally, Workspace has real-time collaboration, commenting and sharing built in, bringing a Google Docs-like collaboration experience to the world of data science.

Is DataCamp Workspace free?

The basic version of DataCamp Workspace is free for all learners. For individuals wanting more RAM and CPU and a more secure way to access databases, individuals can subscribe to the Workspace Premium plan. Groups can buy and assign Workspace Teams licenses to get all Workspace Premium benefits and easily collaborate with other group members. All members of Academic and DataCamp Donates groups get a Workspace Teams license for free.

Can you share Workspace notebooks with non DataCamp account holders?

Yes, you can share your Workspace through a unique dedicated URL.

Which programming languages does the Workspace IDE support?

Currently Workspace supports Python and R, both with native SQL integrations so you can query SQL databases without leaving your workspace.

Is Workspace compatible with Windows, Mac or Linux?

Yes, Workspace is compatible with Windows, Mac or Linux

How can I create a data science portfolio with Workspace?

Workspace is the perfect tool for you to create your data science portfolio. Once you’ve completed your notebook, you can publish it and have it features on your DataCamp profile page. You can share this profile page with others as a data science portfolio.

What are the most popular data connectors for data science projects?

There are various data sources that you can connect to from Workspace. These include GitHub, Dropbox, S3 Buckets, Redshift, PostgreSQL, MySQL, Snowflake, Google Cloud (coming soon) and Google Drive.

Photo of Rodriguez Ramos

‘‘How amazing is it that through Workspace, you can share your data insights with one simple click”

Rodriguez Ramos, Post Doctoral Researcher

Analyze data any time, anywhere

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