Bokeh
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Explore more → **Bokeh**
What is Bokeh?
Bokeh is a Python interactive visualization library that targets modern web browsers for presentation. It provides elegant, concise construction of novel graphics, high-performance interactivity over very large datasets, and versatile output to a range of formats.
What other technologies are related to Bokeh?
Bokeh Competitor Technologies
Leaflet/Folium
No summary available
Provides interactive maps, similar to Bokeh's ability to create interactive web visualizations. Focuses more narrowly on map visualizations though.
Plotly
Offers similar interactive plotting capabilities in Python and other languages, providing an alternative to Bokeh for creating web-based visualizations.
plot.ly
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.
Matplotlib
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.
Seaborn
Built on top of Matplotlib, Seaborn offers a higher-level interface for statistical plotting. Similar to Matplotlib, can be considered a partial competitor.
ggplot
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
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
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.
Number of organizations that mention technology
558
Bokeh
28
Leaflet/Folium
3,496
Plotly
83
plot.ly
7,974
Matplotlib
3,831
Seaborn
979
ggplot
2,582
Dash
2,526
Streamlit
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Bokeh Complementary Technologies
Pandas
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
NumPy provides fundamental numerical computing capabilities. Bokeh uses NumPy arrays as the underlying data structure, making it complementary.
Jupyter
Jupyter Notebooks are often used as the environment for creating Bokeh visualizations, making it a complementary technology.
Number of organizations that mention technology
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Which job functions commonly mention Bokeh?
Data Scientist
0.2% of all Data Scientist jobs mention Bokeh
View 517
jobs on Sumble
Machine Learning
0.1% of all Machine Learning jobs mention Bokeh
View 63
jobs on Sumble
Data, Analytics & Machine Learning
854 Data, Analytics & Machine Learning jobs mention Bokeh
View 854
jobs on Sumble
Data Analyst
235 Data Analyst jobs mention Bokeh
View 235
jobs on Sumble
Software Engineer
336 Software Engineer jobs mention Bokeh
View 336
jobs on Sumble
Which organizations are mentioning Bokeh?
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