Data Visualization with Python: Your guide to understanding your data


Data Visualization with Python: Create an impact with meaningful data insights using interactive and engaging visuals
By 作者: Mario Döbler – Tim Größmann
ISBN-10 书号: 1789956463
ISBN-13 书号: 9781789956467
Release Finelybook 出版日期: 2019-02-28
pages 页数: (368 )

$34.99

Book Description to Finelybook sorting

Data Visualization with Python reviews the spectrum of data visualization and its importance. Designed for beginners, it’ll help you learn about statistics by computing mean, median, and variance for certain numbers.

In the first few chapters, you’ll be able to take a quick tour of key NumPy and Pandas techniques, which include indexing, slicing, iterating, filtering, and grouping. The book keeps pace with your learning needs, introducing you to various visualization libraries. As you work through chapters on Matplotlib and Seaborn, you’ll discover how to create visualizations in an easier way. After a lesson on these concepts, you can then brush up on advanced visualization techniques like geoplots and interactive plots.

You’ll learn how to make sense of geospatial data, create interactive visualizations that can be integrated into any webpage, and take any dataset to build beautiful visualizations. What’s more? You’ll study how to plot geospatial data on a map using Choropleth plot and understand the basics of Bokeh, extending plots by adding widgets and animating the display of information.

By the end of this book, you’ll be able to put your learning into practice with an engaging activity, where you can work with a new dataset to create an insightful capstone visualization.

Contents
1: THE IMPORTANCE OF DATA VISUALIZATION AND DATA EXPLORATION
2: ALL YOU NEED TO KNOW ABOUT PLOTS
3: A DEEP DIVE INTO MATPLOTLIB
4: SIMPLIFYING VISUALIZATIONS USING SEABORN
5: PLOTTING GEOSPATIAL DATA
6: MAKING THINGS INTERACTIVE WITH BOKEH
7: COMBINING WHAT WE HAVE LEARNED
What You Will Learn
Understand and use various plot types with Python
Explore and work with different plotting libraries
Learn to create effective visualizations
Improve your Python data wrangling skills
Hone your skill set by using tools like Matplotlib, Seaborn, and Bokeh
Reinforce your knowledge of various data formats and representations
Authors
Mario Döbler
Mario Döbler is a Ph.D. student with focus in deep learning at the University of Stuttgart. He previously interned at the Bosch Center for Artificial Intelligence in Silicon Valley in the field of deep learning, using state-of-the-art algorithms to develop cutting-edge products. In his master thesis, he dedicated himself to apply deep learning to medical data to drive medical applications.

Tim Großmann
Tim Größmann is a CS student with an interest in diverse topics, ranging from AI to IoT. He previously worked at the Bosch Center for Artificial Intelligence in Silicon Valley, in the field of big data engineering. He’s highly involved in different open source projects and actively speaks at meetups and conferences about his projects and experiences.

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