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Data visualization with Python : create an impact with meaningful data insights using interactive and engaging visuals

Author: Mario Döbler; Tim Grössmann
Publisher: Birmingham, UK : Packt Publishing, [2019] ©2019
Edition/Format:   eBook : Document : English
Summary:
Understand, explore, and effectively present data using the powerful data visualization techniques of Python programming. Key Features Study key visualization tools and techniques with real-world data Explore industry-standard plotting libraries, including Matplotlib and Seaborn Breathe life into your visuals with exciting widgets and animations using Bokeh Book Description Data Visualization with Python reviews the  Read more...
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Genre/Form: Electronic books
Additional Physical Format: Print version:
Döbler, Mario.
Data visualization with Python.
[Birmingham, UK] : Packt Publishing, [2019]
(OCoLC)1102058918
Material Type: Document, Internet resource
Document Type: Internet Resource, Computer File
All Authors / Contributors: Mario Döbler; Tim Grössmann
ISBN: 1789951194 9781789951196
OCLC Number: 1098198103
Description: 1 online resource (1 volume) : illustrations
Contents: Table of ContentsThe Importance of Data Visualization and Data ExplorationAll You Need to Know about PlotsA Deep Dive into MatplotlibSimplifying Visualizations Using SeabornPlotting Geospatial DataMaking Things Interactive with BokehCombining What We Have Learned
Responsibility: Mario Döbler and Tim Grössmann.

Abstract:

With so much data being continuously generated, developers with a knowledge of data analytics and data visualization are always in demand. With Data Visualization with Python, you'll learn how to use  Read more...

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    schema:description "Understand, explore, and effectively present data using the powerful data visualization techniques of Python programming. Key Features Study key visualization tools and techniques with real-world data Explore industry-standard plotting libraries, including Matplotlib and Seaborn Breathe life into your visuals with exciting widgets and animations using Bokeh Book Description 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. 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 Who this book is for Data Visualization with Python is designed for developers and scientists, who want to get into data science or want to use data visualizations to enrich their personal and professional projects. You do not need any prior experience in data analytics and visualization, however, it'll help you to have some knowledge of Python and familiarity with high school level mathematics. Even though this is a beginner level course on data visualization, e..."@en ;
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