Book Image

The Data Visualization Workshop

By : Mario Döbler, Tim Großmann
Book Image

The Data Visualization Workshop

By: Mario Döbler, Tim Großmann

Overview of this book

Do you want to transform data into captivating images? Do you want to make it easy for your audience to process and understand the patterns, trends, and relationships hidden within your data? The Data Visualization Workshop will guide you through the world of data visualization and help you to unlock simple secrets for transforming data into meaningful visuals with the help of exciting exercises and activities. Starting with an introduction to data visualization, this book shows you how to first prepare raw data for visualization using NumPy and pandas operations. As you progress, you’ll use plotting techniques, such as comparison and distribution, to identify relationships and similarities between datasets. You’ll then work through practical exercises to simplify the process of creating visualizations using Python plotting libraries such as Matplotlib and Seaborn. If you’ve ever wondered how popular companies like Uber and Airbnb use geoplotlib for geographical visualizations, this book has got you covered, helping you analyze and understand the process effectively. Finally, you’ll use the Bokeh library to create dynamic visualizations that can be integrated into any web page. By the end of this workshop, you’ll have learned how to present engaging mission-critical insights by creating impactful visualizations with real-world data.
Table of Contents (9 chapters)
7. Combining What We Have Learned


geoplotlib is an open-source Python library for geospatial data visualizations. It has a wide range of geographical visualizations and supports hardware acceleration. It also provides performance rendering for large datasets with millions of data points. As discussed in earlier chapters, Matplotlib provides various ways to visualize geographical data.

However, Matplotlib is not designed for this task because its interfaces are complicated and inconvenient to use. Matplotlib also restricts how geographical data can be displayed. The Basemap and Cartopy libraries allow you to plot on a world map, but these packages do not support drawing on map tiles. Map tiles are underlying rectangular, square, or hexagonal tile slabs that are used to create a seamless map of the world, with lightweight, individually requested tiles that are currently in view.

geoplotlib, on the other hand, was designed precisely for this purpose; it not only provides map tiles but also allows for...