learning ipython for interactive computing and data visualization

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Learning Ipython For Interactive Computing And Data Visualization

Author : Cyrille Rossant
ISBN : 9781782169949
Genre : Computers
File Size : 60. 91 MB
Format : PDF, Kindle
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A practical hands-on guide which focuses on interactive programming, numerical computing, and data analysis with IPython.This book is for Python developers who use Python as a scripting language or for software development, and are interested in learning IPython for increasing their productivity during interactive sessions in the console. Knowledge of Python is required, whereas no knowledge of IPython is necessary.

Learning Ipython For Interactive Computing And Data Visualization Second Edition

Author : Cyrille Rossant
ISBN : 1783986980
Genre : Computer graphics
File Size : 66. 13 MB
Format : PDF, Docs
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Get started with Python for data analysis and numerical computing in the Jupyter notebookAbout This Book- Learn the basics of Python in the Jupyter Notebook- Analyze and visualize data with pandas, NumPy, matplotlib, and seaborn- Perform highly-efficient numerical computations with Numba, Cython, and ipyparallelWho This Book Is ForThis book targets students, teachers, researchers, engineers, analysts, journalists, hobbyists, and all data enthusiasts who are interested in analyzing and visualizing real-world datasets. If you are new to programming and data analysis, this book is exactly for you. If you're already familiar with another language or analysis software, you will also appreciate this introduction to the Python data analysis platform. Finally, there are more technical topics for advanced readers. No prior experience is required; this book contains everything you need to know.What You Will Learn- Install Anaconda and code in Python in the Jupyter Notebook- Load and explore datasets interactively- Perform complex data manipulations effectively with pandas- Create engaging data visualizations with matplotlib and seaborn- Simulate mathematical models with NumPy- Visualize and process images interactively in the Jupyter Notebook with scikit-image- Accelerate your code with Numba, Cython, and IPython.parallel- Extend the Notebook interface with HTML, JavaScript, and D3In DetailPython is a user-friendly and powerful programming language. IPython offers a convenient interface to the language and its analysis libraries, while the Jupyter Notebook is a rich environment well-adapted to data science and visualization. Together, these open source tools are widely used by beginners and experts around the world, and in a huge variety of fields and endeavors.This book is a beginner-friendly guide to the Python data analysis platform. After an introduction to the Python language, IPython, and the Jupyter Notebook, you will learn how to analyze and visualize data on real-world examples, how to create graphical user interfaces for image processing in the Notebook, and how to perform fast numerical computations for scientific simulations with NumPy, Numba, Cython, and ipyparallel. By the end of this book, you will be able to perform in-depth analyses of all sorts of data.Style and approachThis is a hands-on beginner-friendly guide to analyze and visualize data on real-world examples with Python and the Jupyter Notebook.

Ipython Interactive Computing And Visualization Cookbook

Author : Cyrille Rossant
ISBN : 9781783284825
Genre : Computers
File Size : 58. 88 MB
Format : PDF, Docs
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Intended to anyone interested in numerical computing and data science: students, researchers, teachers, engineers, analysts, hobbyists... Basic knowledge of Python/NumPy is recommended. Some skills in mathematics will help you understand the theory behind the computational methods.

Python For Data Analysis

Author : Wes McKinney
ISBN : 9781449319793
Genre : Computers
File Size : 65. 31 MB
Format : PDF, ePub, Mobi
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Presents case studies and instructions on how to solve data analysis problems using Python.

Python Data Visualization Cookbook

Author : Igor Milovanović
ISBN : 9781782163374
Genre : Computers
File Size : 52. 29 MB
Format : PDF, ePub
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This book is written in a Cookbook style targeted towards an advanced audience. It covers the advanced topics of data visualization in Python.Python Data Visualization Cookbook is for developers that already know about Python programming in general. If you have heard about data visualization but you don't know where to start, then this book will guide you from the start and help you understand data, data formats, data visualization, and how to use Python to visualize data.You will need to know some general programming concepts, and any kind of programming experience will be helpful, but the code in this book is explained almost line by line. You don't need maths for this book, every concept that is introduced is thoroughly explained in plain English, and references are available for further interest in the topic.

Mastering Python Data Visualization

Author : Kirthi Raman
ISBN : 9781783988334
Genre : Computers
File Size : 75. 68 MB
Format : PDF, Mobi
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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, which explains the transformation of data into information and eventually knowledge, this book subsequently covers the complete visualization process using the most popular Python libraries with working examples. You will learn the usage of Numpy, Scipy, IPython, MatPlotLib, Pandas, Patsy, and Scikit-Learn with a focus on generating results that can be visualized in many different ways. Further chapters are aimed at not only showing advanced techniques such as interactive plotting; numerical, graphical linear, and non-linear regression; clustering and classification, but also in helping you understand the aesthetics and best practices of data visualization. The book concludes with interesting examples such as social networks, directed graph examples in real-life, data structures appropriate for these problems, and network analysis. By the end of this book, you will be able to effectively solve a broad set of data analysis problems. Style and approach The approach of this book is not step by step, but rather categorical. The categories are based on fields such as bioinformatics, statistical and machine learning, financial computation, and linear algebra. This approach is beneficial for the community in many different fields of work and also helps you learn how one approach can make sense across many fields

Mining The Social Web

Author : Matthew A. Russell
ISBN : 9781449368210
Genre : Computers
File Size : 78. 95 MB
Format : PDF, Kindle
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How can you tap into the wealth of social web data to discover who’s making connections with whom, what they’re talking about, and where they’re located? With this expanded and thoroughly revised edition, you’ll learn how to acquire, analyze, and summarize data from all corners of the social web, including Facebook, Twitter, LinkedIn, Google+, GitHub, email, websites, and blogs. Employ the Natural Language Toolkit, NetworkX, and other scientific computing tools to mine popular social web sites Apply advanced text-mining techniques, such as clustering and TF-IDF, to extract meaning from human language data Bootstrap interest graphs from GitHub by discovering affinities among people, programming languages, and coding projects Build interactive visualizations with D3.js, an extraordinarily flexible HTML5 and JavaScript toolkit Take advantage of more than two-dozen Twitter recipes, presented in O’Reilly’s popular "problem/solution/discussion" cookbook format The example code for this unique data science book is maintained in a public GitHub repository. It’s designed to be easily accessible through a turnkey virtual machine that facilitates interactive learning with an easy-to-use collection of IPython Notebooks.

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