Python for Data Analysis: Data Wrangling with Pandas, NumPy, and IPython

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Python for Data Analysis is concerned with the nuts and bolts of manipulating, processing, cleaning, and crunching data in Python. It is also a practical, modern introduction to scientific computing in Python, tailored for data-intensive applications. This is a book about the parts of the Python language and libraries you’ll need to effectively solve a broad set of data analysis problems. This book is not an exposition on analytical methods using Python as the implementation language.

Written by Wes McKinney, the main author of the pandas library, this hands-on book is packed with practical cases studies. It’s ideal for analysts new to Python and for Python programmers new to scientific computing.Use the IPython interactive shell as your primary development environmentLearn basic and advanced NumPy (Numerical Python) featuresGet started with data analysis tools in the pandas libraryUse high-performance tools to load, clean, transform, merge, and reshape dataCreate scatter plots and static or interactive visualizations with matplotlibApply the pandas groupby facility to slice, dice, and summarize datasetsMeasure data by points in time, whether it’s specific instances, fixed periods, or intervalsLearn how to solve problems in web analytics, social sciences, finance, and economics, through detailed examples

HTTP Programming Recipes for C# Bots

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The Hypertext Transfer Protocol (HTTP) allows information to be exchanged between a web server and a web browser. C# allows you to program HTTP directly. HTTP programming allows you to create programs that access the web much like a human user would. These programs, which are called bots, can collect information or automate common web programming tasks. This book presents a collection of very reusable recipes for C# bot programming. This book covers many topics related to C# HTTP programming. Both secure and insecure HTTP communications are covered, as well as HTTP authentication. Learn to interact with HTTP forms and support both HTTP POST and HTTP GET requests. Collect data from a wide array of HTML constructs, such as tables, and lists. Learn about advanced topics that complicate the life of a bot, such as AJAX and Javascript. Also learn about the ethical use of bots, and when bots should not be used. This book also introduces the Heaton Research Spider. The Heaton Research Spider is an open source spider framework. Using the Heaton Research Spider you can create spiders that will crawl a web site, much like a real spider crawls the web. The Heaton Research Spider is available in both Java and Microsoft Dot Net form.

Raspberry Pi Assembly Language RASPBIAN Beginners: Hands On Guide

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Raspberry Pi Assembly Language RASPBIAN Beginners is your hands-on guide to learning to program ARM machine code on your Raspberry Pi. With nothing other than the Raspbian Operating System installed on your Raspberry Pi, this book shows you how to access all the tools that you'll need to create your own machine code programs using assembly language. (A version of this book is available specifically for RISC OS – search Amazon for 'Assembly Language Beginners'.)

Ideal for the novice, this book starts from first principles and leads you comfortably on your way to become an accomplished programmer. Providing lucid descriptions, award winning author Bruce Smith keeps things simple and includes plenty of program examples you can try for yourself. Ideas and concepts are introduced in the order required so you should never be left wondering.
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Introduction to High Performance Computing for Scientists and Engineers (Chapman & Hall/CRC Computational Science)

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Written by high performance computing (HPC) experts, Introduction to High Performance Computing for Scientists and Engineers provides a solid introduction to current mainstream computer architecture, dominant parallel programming models, and useful optimization strategies for scientific HPC. From working in a scientific computing center, the authors gained a unique perspective on the requirements and attitudes of users as well as manufacturers of parallel computers.

The text first introduces the architecture of modern cache-based microprocessors and discusses their inherent performance limitations, before describing general optimization strategies for serial code on cache-based architectures. It next covers shared- and distributed-memory parallel computer architectures and the most relevant network topologies. After discussing parallel computing on a theoretical level, the authors show how to avoid or ameliorate typical performance problems connected with OpenMP. They then present cache-coherent nonuniform memory access (ccNUMA) optimization techniques, examine distributed-memory parallel programming with message passing interface (MPI), and explain how to write efficient MPI code. The final chapter focuses on hybrid programming with MPI and OpenMP.
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Fast Data Processing with Spark

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In Detail

Spark is a framework for writing fast, distributed programs. Spark solves similar problems as Hadoop MapReduce does but with a fast in-memory approach and a clean functional style API. With its ability to integrate with Hadoop and inbuilt tools for interactive query analysis (Shark), large-scale graph processing and analysis (Bagel), and real-time analysis (Spark Streaming), it can be interactively used to quickly process and query big data sets.
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