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by vigneshchennai74 dot icon Updated: Aug 24, 2023

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In photography, Bokeh means how the blurry parts of a picture look. It's derived from the Japanese word "boke," which means "blur" or "haze." 

Bokeh is an artistic technique used by photographers. That will create pleasing and engaging photographs. The background gets blurry, but the subject stays clear, making a soft and dreamy look. Bokeh makes images look interesting. It makes the subject stand out and separates the foreground from the background. 

Bokeh in photography can differ in its appearance. The photographer creates a smooth bokeh by blurring the areas not in the center. The Bokeh appears delicate and velvety, with no distracting details. Representation photography often features a central subject as the main focus. Bokeh can create unique patterns when capturing light sources or reflective surfaces. The camera's edges create gaps and add imagination and creativity to the picture. 

You can use Bokeh to enhance various types of photos. In representation photography, Bokeh makes the person stand out by blurring the background. It can create a feeling of closeness and feature the subject's feelings. To make your photos more impressive, use a wide aperture (low f-number), like f/1.8 or f/2.8, as a focal point. The field has a shallow depth due to a wide gap. It appears unevenly shaped. This partition intensifies the bokeh impact. Using longer focal lengths can also improve the quality of Bokeh. Bokeh helps in concentrating on subjects with texture or detail. 

Bokeh photography adds creativity by blurring the foreground and background with focus control. It transforms ordinary scenes into captivating visual narratives. Bokeh is a unique technique in photography. It can create emotions, highlight subjects, and make dreamy atmospheres. 

Preview of the output that you will get on running this code from your IDE

Bokeh is a Python library for creating interactive and visually appealing web-based data visualizations and dashboards.


  1. Download and install VS Code on your desktop.
  2. Open VS Code and create a new file in the editor.
  3. Copy the code snippet that you want to run, using the "Copy" button or by selecting the text and using the copy command (Ctrl+C on Windows/Linux or Cmd+C on Mac).,
  4. Paste the code into your file in VS Code, and save the file with a meaningful name and the appropriate file extension for Python use (.py).file extension.
  5. To run the code, open the file in VS Code and click the "Run" button in the top menu, or use the keyboard shortcut Ctrl+Alt+N (on Windows and Linux) or Cmd+Alt+N (on Mac). The output of your code will appear in the VS Code output console.
  6. Paste the Bokeh code into your file in VS Code.
  7. Delete lines from 10 to 16.
  8. Save the file with a meaningful name and the appropriate file extension for Python use (.py).
  9. Install Bokeh Library; Open your command prompt or terminal.
  10. Type the following command and press Enter: pip install bokeh
  11. Run the Code

I hope you have found this useful. I have added the version information in the following section.

I found this code snippet by searching " How to Make Event Plot using Python Bokeh Library?" in Kandi. you can try any use case.

Environment Tested

I tested this solution in the following versions. Be mindful of changes when working with other versions.

  1. The solution is created and tested using Vscode 1.77.2 version
  2. The solution is created in Python 3.7.15 version
  3. The solution is created in bokeh 3.2.1

Using this solution, the code leverages `pandas` and `bokeh` libraries to visually represent a task stream, showcasing tasks as colored rectangles along a timeline. This process also facilities an easy-to-use, hassle-free method to create a hands-on working version of code which would help us visually represent a task stream using bokeh in Python


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  2. For further learning resources, visit the Open Weaver Community learning page.


1. What are bokeh plots, and how do they differ from static plots? 

Bokeh plots are dynamic visuals made with the Bokeh library in Python. Unlike fixed static plots, bokeh plots engage users with zooming, panning, and more. They're great for exploring data. 


2. How are event callbacks used for interactive Bokeh? 

Event callbacks trigger actions when users interact with bokeh plots. Clicks, hovers, sliders – callbacks make plots respond, revealing insights and enhancing engagement. 


3. Is Jupyter best for creating interactive Bokeh plots? 

Jupyter is popular for interactive Bokeh plots. You can also use Bokeh in other Python environments. Choose based on your workflow and preferences. 


4. How do I import figures for a bokeh plot in Python? 

To create bokeh plots, start by importing figures from Bokeh. It's your canvas for adding data and making dynamic visuals.