The Data Visualization Workshop: A self-paced, practical approach to transforming your complex data into compelling, captivating graphics

The Data Visualization Workshop: A self-paced, practical approach to transforming your complex data into compelling, captivating graphicsReviews
Author: Mario Döbler
Pub Date: 2020
ISBN: 978-1800568846
Pages: 536
Language: English
Format: PDF/EPUB
Size: 349 Mb

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Explore a modern approach to visualizing data with Python and transform large real-world datasets into expressive visual graphics using this beginner-friendly workshop
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.
What you will learn

  • Understand the importance of data visualization in data science
  • Implement NumPy and pandas operations on real-life datasets
  • Create captivating data visualizations using plotting libraries
  • Use advanced techniques to plot geospatial data on a map
  • Integrate interactive visualizations to a webpage
  • Visualize stock prices with Bokeh and analyze Airbnb data with Matplotlib