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Interactive Data Visualization with Python - Present your data as an effective and compelling story, 2nd Edition (Paperback, 2nd Revised edition)
Loot Price: R1,199
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Interactive Data Visualization with Python - Present your data as an effective and compelling story, 2nd Edition (Paperback, 2nd Revised edition)
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Create your own clear and impactful interactive data visualizations
with the powerful data visualization libraries of Python Key
Features Study and use Python interactive libraries, such as Bokeh
and Plotly Explore different visualization principles and
understand when to use which one Create interactive data
visualizations with real-world data Book DescriptionWith so much
data being continuously generated, developers, who can present data
as impactful and interesting visualizations, are always in demand.
Interactive Data Visualization with Python sharpens your data
exploration skills, tells you everything there is to know about
interactive data visualization in Python. You'll begin by learning
how to draw various plots with Matplotlib and Seaborn, the
non-interactive data visualization libraries. You'll study
different types of visualizations, compare them, and find out how
to select a particular type of visualization to suit your
requirements. After you get a hang of the various non-interactive
visualization libraries, you'll learn the principles of intuitive
and persuasive data visualization, and use Bokeh and Plotly to
transform your visuals into strong stories. You'll also gain
insight into how interactive data and model visualization can
optimize the performance of a regression model. By the end of the
course, you'll have a new skill set that'll make you the go-to
person for transforming data visualizations into engaging and
interesting stories. What you will learn Explore and apply
different interactive data visualization techniques Manipulate
plotting parameters and styles to create appealing plots Customize
data visualization for different audiences Design data
visualizations using interactive libraries Use Matplotlib, Seaborn,
Altair and Bokeh for drawing appealing plots Customize data
visualization for different scenarios Who this book is forThis book
intends to provide a solid training ground for Python developers,
data analysts and data scientists to enable them to present
critical data insights in a way that best captures the user's
attention and imagination. It serves as a simple step-by-step guide
that demonstrates the different types and components of
visualization, the principles, and techniques of effective
interactivity, as well as common pitfalls to avoid when creating
interactive data visualizations. Students should have an
intermediate level of competency in writing Python code, as well as
some familiarity with using libraries such as pandas.
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