TY  - BOOK
AU  - Raman,Kirthi
TI  - Mastering Python data visualization: generate effective results in a variety of visually appealing charts using the plotting packages in Python 
T2  - Community experience distilled
SN  - 1783988339
AV  - QA76.9.I52 R36 2015
U1  - 001.4/226028566 23
PY  - 2015///
CY  - Birmingham, UK
PB  - Packt Publishing
KW  - Information visualization
KW  - Visual analytics
KW  - Python (Computer program language)
KW  - Visualisation de l'information
KW  - Analyse visuelle
KW  - Python (Langage de programmation)
KW  - REFERENCE
KW  - Questions & Answers
KW  - bisacsh
KW  - fast
KW  - Electronic books
N1  - Includes index
N2  - Generate effective results in a variety of visually appealing charts using the plotting packages in Python 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 diverse 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 existing knowledge about Python to build analytical results and produce some amazing visual display, 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-driven narratives and author-driven narratives and the principles of perception Understand why Python is an effective tool to be used for numerical computation much like MATLAB, and explore some interesting data structures that come with it Explore with various visualization choices how Python can be very useful in computation in the field of finance and statistics Get to know why Python is the second choice after Java, and is used frequently in the field of machine learning 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 Hive to produce results efficiently in a distributed environment In Detail Python has a handful of open source libraries for numerical computations involving optimization, linear algebra, integration, interpolation, and other special functions using array objects, machine learning, data mining, and plotting. Pandas have a productive environment for data analysis. These libraries have a specific purpose and play an important role in the research into diverse domains including economics, finance, biological sciences, social science, health care, and many more. The variety of tools and approaches available within Python community is stunning, and can bolster and enhance visual story experiences. This book offers practical guidance to help you on the journey to effective data visualization. Commencing with a chapter on the data framework
UR  - https://search.ebscohost.com/login.aspx?direct=true&scope=site&db=nlebk&AN=1087761
ER  -