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

Relation Plots

Relation plots are perfectly suited to showing relationships among variables. A scatter plot visualizes the correlation between two variables for one or multiple groups. Bubble plots can be used to show relationships between three variables. The additional third variable is represented by the dot size. Heatmaps are great for revealing patterns or correlations between two qualitative variables. A correlogram is a perfect visualization for showing the correlation among multiple variables.

Scatter Plot

Scatter plots show data points for two numerical variables, displaying a variable on both axes.


  • You can detect whether a correlation (relationship) exists between two variables.
  • They allow you to plot the relationship between multiple groups or categories using different colors.
  • A bubble plot, which is a variation of the scatter plot, is an excellent tool for visualizing the correlation of a third variable.


The following diagram...