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Kirthi Raman, "Mastering Python Data Visualization"
English | ISBN: 1783988320 | 2015 | PDF | 305 pages | 12,1 MB
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.
本帖隐藏的内容
Mastering Python Data Visualization py2.pdf
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