Interactive Data Filtering in Bokeh: Building Dynamic Visualizations with Python
Learn how to use Python and Bokeh to interactively filter and visualize time series data. This tutorial covers loading real-world datasets with pandas, creating basic plots, and building interactive filters to explore trends in airline passenger data. You will gain hands-on experience with sliders, checkboxes, and custom JavaScript callbacks to make your visualizations dynamic and insightful.
By following along, you will understand how to connect widgets to your plots, filter by year or value, and build a complete dashboard for data exploration. The lesson also includes troubleshooting tips and best practices for keeping your data and visualization code organized. Perfect for beginners looking to enhance their data analysis skills with interactive tools.
00:00 Introduction and overview
00:20 What is Bokeh
00:50 Setting up the environment
01:30 Loading and preparing the dataset
02:22 Plotting the time series
03:01 Adding interactivity with sliders
03:44 Creating a year filter
04:44 Building a range slider for year selection
05:52 Recap and progress check
06:15 Counting filtered months
06:31 Filtering by passenger value
07:01 Custom threshold filtering
07:43 Building a complete dashboard
08:24 Best practices for data and visualization
08:58 Troubleshooting widget updates
09:27 Exporting interactive plots
09:51 Challenge: busiest quarter filter
10:11 Final recap and next steps
10:34 Conclusion and further learning
#Python #DataVisualization #Bokeh
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