Big data analytics drives innovation in scientific research, digital marketing, policy making, and much more. With the increasing amount of data from sensors, user activities, to APIs and databases, there is a need to visualize data effectively in order to communicate the insights to the target audience.
Matplotlib offers a simple but a powerful plotting library that helps to resolve the complexity in big data visualization, and turns overwhelming data into useful information. The library offers versatile plot types and robust customizations to transform data into persuasive and actionable figures. With the recent introduction of version 2, Matplotlib has further established its pivotal role in Python visualization.
Matplotlib 2.x By Example illustrates the methods and applications of various plot types through real-world examples. It begins by giving readers the basic know-how on how to create and customize plots with Matplotlib. It further covers how to plot different types of economic data in the form of 2D and 3D graphs, which give insights from a deluge of data from public repositories such as Quandl Finance and data.gov. By extending the power of Matplotlib using toolkits such as GeoPandas, Lifelines, Mplot3d, NumPy, Pandas, Plot.ly, Scikit-learn, SciPy, and Seaborn, you will learn how to visualize geographical data on maps, implement interactive charts, and craft professional scientific visualizations from complex datasets. By the end of this book, you will become well-versed with Matplotlib in your day-to-day work and be able to create advanced data visualizations.
