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)
Preface
7
7. Combining What We Have Learned

Tile Providers

geoplotlib supports the use of different tile providers. This means that any OpenStreetMap tile server can be used as a backdrop for our visualization. Some of the popular free tile providers include Stamen Watercolor, Stamen Toner, Stamen Toner Lite, and DarkMatter. Changing the tile provider can be done in two ways:

  • Make use of built-in tile providers:

    geoplotlib contains a few built-in tile providers with shortcuts. The following code shows you how to use it:

    geoplotlib.tiles_provider('darkmatter')
  • Provide a custom object to the tiles_provider method:

    By providing a custom object to geoplotlib's tiles_provider() method, you will not only get access to the url parameter from which the map tiles are being loaded but also see the attribution parameter displayed in the lower-right corner of the visualization. We are also able to set a distinct caching directory for the downloaded tiles. The following code demonstrates how to provide a custom object...