Bokeh
Bokeh makes it simple to create common plots, but also can handle custom or specialized use-cases. Plots, dashboards, and apps can be published in web pages or Jupyter notebooks. Python has an incredible ecosystem of powerful analytics tools: NumPy, Scipy, Pandas, Dask, Scikit-Learn, OpenCV, and more. With a wide array of widgets, plot tools, and UI events that can trigger real Python callbacks, the Bokeh server is the bridge that lets you connect these tools to rich, interactive visualizations in the browser. Microscopium is a project maintained by researchers at Monash University. It allows researchers to discover new gene or drug functions by exploring large image datasets with Bokeh’s interactive tools. Panel is a tool for polished data presentation that utilizes the Bokeh server. It is created and supported by Anaconda. Panel makes it simple to create custom interactive web apps and dashboards by connecting user-defined widgets to plots, images, tables, or text.
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Polars
Knowing of data wrangling habits, Polars exposes a complete Python API, including the full set of features to manipulate DataFrames using an expression language that will empower you to create readable and performant code. Polars is written in Rust, uncompromising in its choices to provide a feature-complete DataFrame API to the Rust ecosystem. Use it as a DataFrame library or as a query engine backend for your data models.
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Positron
Positron is a next-generation, free, open source available integrated development environment for data science, built to support both Python and R in one unified workflow. It enables data professionals to move from exploration to production by offering interactive consoles, notebook support, variables and plot panes, and built-in previews of apps alongside code, all without needing extensive configuration. The IDE includes AI-assisted tools like the Positron Assistant and Databot agent to help write or refine code, perform exploratory analysis, and accelerate development. It offers features like a dedicated Data Explorer for viewing dataframes, a connections pane for databases, a variables pane, a plot pane, and seamless switch between R and Python with full support for notebooks, scripts, and visual dashboards. With version control, extensions support, and deep integration with other tools in the Posit Software ecosystem.
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JetBrains DataSpell
Switch between command and editor modes with a single keystroke. Navigate over cells with arrow keys. Use all of the standard Jupyter shortcuts. Enjoy fully interactive outputs – right under the cell. When editing code cells, enjoy smart code completion, on-the-fly error checking and quick-fixes, easy navigation, and much more. Work with local Jupyter notebooks or connect easily to remote Jupyter, JupyterHub, or JupyterLab servers right from the IDE. Run Python scripts or arbitrary expressions interactively in a Python Console. See the outputs and the state of variables in real-time. Split Python scripts into code cells with the #%% separator and run them individually as you would in a Jupyter notebook. Browse DataFrames and visualizations right in place via interactive controls. All popular Python scientific libraries are supported, including Plotly, Bokeh, Altair, ipywidgets, and others.
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