Bokeh

Provides interactive maps, similar to Bokeh's ability to create interactive web visualizations. Focuses more narrowly on map visualizations though.

Offers similar interactive plotting capabilities in Python and other languages, providing an alternative to Bokeh for creating web-based visualizations.

An older name for Plotly. Offers similar interactive plotting capabilities in Python and other languages, providing an alternative to Bokeh for creating web-based visualizations.

A fundamental plotting library in Python. While it lacks Bokeh's interactivity, it's often used as a starting point, making it an indirect competitor, despite also potentially being used in conjunction with it for data preparation.

Built on top of Matplotlib, Seaborn offers a higher-level interface for statistical plotting. Similar to Matplotlib, can be considered a partial competitor.

ggplot is an implementation of the Grammar of Graphics in R, a popular alternative to Python. While distinct languages, both can address the same visualization needs.

Dash is a framework for building web applications using Python. While it can incorporate Bokeh plots, it is often used as an alternative for building interactive dashboards.

Streamlit is a framework for building interactive web applications for machine learning and data science. It provides an alternative way to display interactive visualizations, including those made with Bokeh. Can be used as an alternative to creating dashboards with Bokeh, though Bokeh can be used within Streamlit.

Pandas is used for data manipulation and analysis. Bokeh can readily visualize Pandas DataFrames, making it a valuable tool for exploring and presenting data processed with Pandas.

NumPy provides fundamental numerical computing capabilities. Bokeh uses NumPy arrays as the underlying data structure, making it complementary.

Jupyter Notebooks are often used as the environment for creating Bokeh visualizations, making it a complementary technology.