Develop, collaborate, manage and share your data science work in R and Python--all with RStudio

Many Data Science teams today are bilingual, leveraging both R and Python in their work. While both languages have unique strengths, teams frequently struggle to use them together:

Data Scientists

Constantly need to switch contexts among multiple environments. Read More

Data Science Leaders

Wrestle with how to share results consistently and deliver value to the larger organization, while providing tools for collaboration between R and Python users on their team. Read More

DevOps engineers and IT Admins

Spend time and resources attempting to maintain, manage and scale separate environments for R and Python in a cost-effective way. Read More

To help Data Science teams solve these problems, and in line with our ongoing mission to support the open-source data science ecosystem, we’ve made the love story between R and Python a happier one:

RStudio IDE makes it easy to combine R and Python in a single data science project.

RStudio Server Pro launches and manages Jupyter Notebooks and JupyterLab environments.

RStudio Connect makes it easy to share Jupyter Notebooks, Python APIs via Flask, and interactive Python applications via Dash, Streamlit, or Bokeh with your stakeholders, alongside your work in R and your mixed R and Python projects.

To learn more, schedule a conversation with our team.