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Effective Data Visualization下载
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2019-12-03 12:30:24
Effective Data Visualization 2017 page 426 Stephanie D.H. Evergreen
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Effective Data Visualization下载
Effective Data Visualization 2017 page 426 Stephanie D.H. Evergreen 相关下载链接://download.csdn.net/download/happyfreeangel/10451770?utm_source=bbsseo
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Effect
ive
Data
Visualization
Effect
ive
Data
Visualization
2017 page 426 Stephanie D.H. Evergreen
Applied
Data
Visualization
with R and ggplot2
Develop informat
ive
and aesthetic
visualization
s that enable
effect
ive
data
analysis in less time Applied
Data
Visualization
with R and ggplot2 introduces you to the world of
data
visualization
by taking you through the basic features of ggplot2. To start with, you’ll learn how to set up the R environment, followed by getting insights into the grammar of graphics and geometric objects before you explore the plotting techniques. You’ll discover what layers, scales, coordinates, and themes are, and study how you can use them to transform your
data
into aesthetical graphs. Once you’ve grasped the basics, you’ll move on to studying simple plots such as histograms and advanced plots such as superimposing and density plots. You’ll also get to grips with plotting trends, correlations, and statistical summaries. By the end of this book, you’ll have created
data
visualization
s that will impress your clients.
Mastering Python
Data
Visualization
(PACKT,2015)
About This Book Explore various tools and their strengths while building meaningful representations that can make it easier to understand
data
Packed with computational methods and algorithms in d
ive
rse fields of science Written in an easy-to-follow categorical style, this book discusses some niche techniques that will make your code easier to work with and reuse Who This Book Is For If you are a Python developer who performs
data
visualization
and wants to develop your existing Python knowledge, then this book is for you. A basic knowledge level and understanding of Python libraries is assumed. What You Will Learn Gather, cleanse, access, and map
data
to a visual framework Recognize which
visualization
method is applicable and learn best practices for
data
visualization
Get acquainted with reader-dr
ive
n narrat
ive
s, author-dr
ive
n narrat
ive
s, and the principles of perception Understand why Python is an
effect
ive
tool for numerical computation much like MATLAB, and explore some interesting
data
structures that come with it Use various
visualization
techniques to explore how Python can be very useful for financial and statistical computations Compare Python with other
visualization
approaches using Julia and a JavaScript-based framework such as D3.js Discover how Python can be used in conjunction with NoSQL, such as H
ive
, to produce results efficiently in a distributed environment In Detail Python has a handful of open source libraries for numerical computations that involve optimization, linear algebra, integration, interpolation, and other special functions using array objects, machine learning,
data
mining, and plotting. This book offers practical guidance to help you on the journey to
effect
ive
data
visualization
. Commencing with a chapter on the
data
framework, the book covers the complete
visualization
process, using the most popular Python libraries with working examples. You will learn how to use NumPy, SciPy,
Data
Visualization
- A Practical Introduction [Kieran Healy](2018)
An accessible primer on how to create
effect
ive
graphics from
data
This book provides students and researchers a hands-on introduction to the principles and practice of
data
visualization
. It explains what makes some graphs succeed while others fail, how to make high-quality figures from
data
using powerful and reproducible methods, and how to think about
data
visualization
in an honest and
effect
ive
way.
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