In this course, learners explore approaches to building and implementing visualizations for data science, as well as plotting and graphing using Python libraries such as Matplotlib, ggplot, bokeh, and Pygal. Key concepts covered here include the importance and relevance of data visualization from the business perspective; libraries that can be used in Python to implement data visualization and how to set up a data visualization environment using Python tools and libraries; and prominent data visualization libraries that can be used with Matplotlib. Then see how to create bar charts by using ggplot in Python; how to create charts, using the bokeh and Pygal libraries in Python; and criteria that should be considered when selecting an appropriate data visualization library. Learners observe how to create interactive graphs and image files; how to plot graphs using line and markers; and how to plot multiple lines in a single graph with different line styles and markers. Finally, see how to create a line chart with Pygal, create an HTML directive to render the line chart, and render the line chart.
Advanced Visualizations & Dashboards: Visualization Using Python