<p>Some popular Python data visualization tools and techniques today include Data Visualization in Jupyter Notebook with Bloomberg's bqplot library, Programming Graph and Network Data Visualizations, Data Visualizations with Bokeh (a Python library), and building interactive web visualizations using Dash.</p> <p>You will start by programming stunning interactive Data Visualizations using bqplot, an open source Python library developed by Bloomberg. Then you will learn how to programmatically create interactive network graphs and visualizations. You will then programmatically visualize data with the interactive Python visualization library, Bokeh.</p> <p>Finally, you will build interactive web visualizations of data using Python: you will choose a number of inputs your users can control, then use any Python graphing library to create plots based on those inputs.</p> <p>All the code and supporting files for this course are available on GitHub at <a style="color: #fa8d11;" href="https://github.com/PacktPublishing/Data-visualization-projects-in-python." target="blank">https://github.com/PacktPublishing/Data-visualization-projects-in-python</a>.</p> <h1>Style and Approach</h1> <p>This friendly course takes you through data visualization in Python using bqplot, NetworkX, Bokeh, and Dash. It is packed with step-by-step instructions and working examples. This comprehensive course is divided into clear bite-size chunks so you can learn at your own pace and focus on the areas of most interest to you.</p>