Data Visualization with Python

OverviewThis On Demand course 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 by Matplotlib. It 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. You will learn to visualize geographical data on maps and implement interactive charts. You'll become well versed with Matplotlib in your day-to-day work to perform advanced data visualization. It will help you prepare high quality figures for manuscripts and presentations, and you will learn to create intuitive infographics to effectively communicate information.Objectives

Upon completion of this event you will:

• Familiarize yourself with the latest features in Matplotlib 2.x
• Create data visualizations on 2D and 3D charts in the form of bar charts, bubble charts, heat maps, histograms, scatter plots, stacked area charts, swarm plots and many more
• Make clear and appealing figures for scientific publications
• Create interactive charts and animations
• Extend the functionalities of Matplotlib with third-party packages, such as Basemap, GeoPandas, Mplot3d, Pandas, Scikit-learn, and Seaborn
• Design intuitive infographics for effective storytelling

Content

Hello to the world of plotting

Figure layout and annotations

Visualizing online data

Extending to multidimensional space

Adding interactivity and animating plots

Practical guide to scientific plotting

FurtherinfoThis course will help anyone interested in data visualization to get insights from big data with Python and Matplotlib 2.x. With this course you will be able to extend your knowledge and learn how to use Python code to create 2D and 3D interactive vizualizations. A basic knowledge of Python is expected.