Jupyter Notebook is an open-source, web-based interactive computing environment that lets users create documents combining live executable code, rich text explanations, mathematical equations, and data visualizations in a single shareable format. Originally developed as part of the IPython project, Jupyter now supports over 40 programming languages through interchangeable kernels, with Python, R, and Julia being the most popular.
The notebook interface organizes content into cells: code cells that execute and display output inline, and markdown cells for documentation and narrative text. This cell-based setup makes Jupyter a natural fit for exploratory data analysis, where analysts iteratively run queries, inspect results, and refine their approach. Rich output rendering supports charts (via Matplotlib, Plotly, or Seaborn), interactive widgets, DataFrames, images, and even embedded HTML, so your analysis and its documentation live in the same place.
Jupyter is the default tool for most data science, machine learning research, and technical education workflows. JupyterLab, the next-generation interface, adds a full IDE-like experience with file browsing, terminals, and multiple synchronized views. Cloud-hosted versions like Google Colab, Amazon SageMaker Studio, and Kaggle Notebooks offer free GPU access and collaboration features. For production workflows, tools like Papermill parameterize and execute notebooks programmatically, while nbconvert turns them into reports, slides, or static HTML for sharing with non-technical stakeholders.