Jupyter, the interactive data notebook for visualization and analysis with languages like Python and R, is undergoing a quiet but major reworking into a new product, JupyterLab. Jupyter’s ...

Introduction to Python for Data Analysis¶. Recall that R is a statistical programming language—a language designed to do things like t-tests, regression, and so on.The core of R was developed during ...

Originally developed for data science applications written in Python, R, and Julia, Jupyter Notebook is useful in all kinds of ways for all kinds of projects: Data visualizations.

Notebooks will help boost data analyst productivity with integrated workflows, source control, advanced security, and much more, allowing them to conduct ad hoc analysis on disparate datasets - in ...

When doing data analysis, I prefer to use Jupyter notebooks as they provide a more convenient environment than the command line. You can inspect the data you are working with and write your ...

For data scientists, Python integration with Jupyter Notebooks now enables users to create and share documents that contain live code, equations, visualizations and explanatory text.

Jupyter Notebooks, even though tightly tied to data science darling programming language Python, can now be done with .NET languages C# or F#. The popular notebooks provide interactive environments -- ...