Top 3 Python Alternative (Similar) to Bokeh Visualization Library
Bokeh Visualization Library alternatives - Best library similar to Bokeh Visualization Library. Find the top competitors of Bokeh Visualization Library.
Bokeh is an interactive visualization library for modern web browsers. Bokeh can help anyone who would like to quickly and easily make interactive plots, dashboards, and data applications.
- Flexible: Bokeh makes it simple to create common plots and handle custom or specialized use-cases.
- Interactive: Tools and widgets let you and your audience probe “what if” scenarios or drill down into the details of your data.
- Shareable: Plots, dashboards, and apps can be published in web pages or Jupyter notebooks.
- Productive: Work with PyData tools you are already familiar.
- Powerful: You can always add custom JavaScript to support advanced or specialized cases.
- Open Source: Everything, including the Bokeh server, is BSD licensed and available on GitHub.
Best Python Bokeh Visualization Library alternatives and competitors
Matplotlib is a comprehensive library for creating static, animated, and interactive visualizations in Python. Matplotlib produces high-quality charts in various formats and interactive environments across platforms. Matplotlib can be used in Python scripts, Python/IPython shells, web application servers, and graphical user interface toolkits.
- Create high-quality plots.
- Make interactive figures that can zoom, pan, and update.
- Customize visual style and layout.
- Export to many file formats.
- Embed in JupyterLab and Graphical User Interfaces.
- Use a rich array of third-party packages built on Matplotlib.
Seaborn is a library for making statistical graphics in Python. It is a Python data visualization library based on matplotlib and integrates closely with pandas data structures. Seaborn helps you explore and understand your data. Behind the scenes, seaborn uses matplotlib to draw its plots. Its plotting functions operate on data frames and arrays to produce informative plots.
