Book Description
Data Visualization with Python reviews the spectrum of data visualization and its importance. Designed for beginners, itβll help you learn about statistics by computing mean, median, and variance for certain numbers.
In the first few chapters, youβll be able to take a quick tour of key NumPy and Pandas techniques, which include indexing, slicing, iterating, filtering, and grouping. The book keeps pace with your learning needs, introducing you to various visualization libraries. As you work through chapters on Matplotlib and Seaborn, youβll discover how to create visualizations in an easier way. After a lesson on these concepts, you can then brush up on advanced visualization techniques like geoplots and interactive plots.
You'll learn how to make sense of geospatial data, create interactive visualizations that can be integrated into any webpage, and take any dataset to build beautiful visualizations. Whatβs more? You'll study how to plot geospatial data on a map using Choropleth plot and understand the basics of Bokeh, extending plots by adding widgets and animating the display of information.
By the end of this book, youβll be able to put your learning into practice with an engaging activity, where you can work with a new dataset to create an insightful capstone visualization.