Untangle your web scraping complexities and access web data with ease using Python scripts Key Features Hands-on recipes for advancing your web scraping skills to expert level One-stop solution guide to address complex and challenging web scraping tasks using Python Understand web page structures and collect data from a website with ease Book DescriptionPython Web Scraping Cookbook is a solution-focused book that will teach you techniques to develop high-performance Scrapers, and deal with cookies, hidden form fields, Ajax-based sites and proxies. You'll explore a number of real-world scenarios where every part of the development or product life cycle will be fully covered. You will not only develop the skills to design reliable, high-performing data flows, but also deploy your codebase to Amazon Web Services (AWS). If you are involved in software engineering, product development, or data mining or in building data-driven products, you will find this book useful as each recipe has a clear purpose and objective. Right from extracting data from websites to writing a sophisticated web crawler, the book's independent recipes will be extremely helpful while on the job. This book covers Python libraries, requests, and BeautifulSoup. You will learn about crawling, web spidering, working with AJAX websites, and paginated items. You will also understand to tackle problems such as 403 errors, working with proxy, scraping images, and LXML. By the end of this book, you will be able to scrape websites more efficiently and deploy and operate your scraper in the cloud. What you will learn Use a variety of tools to scrape any website and data, including Scrapy and Selenium Master expression languages, such as XPath and CSS, and regular expressions to extract web data Deal with scraping traps such as hidden form fields, throttling, pagination, and different status codes Build robust scraping pipelines with SQS and RabbitMQ Scrape assets like image media and learn what to do when Scraper fails to run Explore ETL techniques of building a customized crawler, parser, and convert structured and unstructured data from websites Deploy and run your scraper as a service in AWS Elastic Container Service Who this book is forThis book is ideal for Python programmers, web administrators, security professionals, and anyone who wants to perform web analytics. Familiarity with Python and basic understanding of web scraping will be useful to make the best of this book.

Get to grips with pandas-a versatile and high-performance Python library for data manipulation, analysis, and discovery About This Book * Get comfortable using pandas and Python as an effective data exploration and analysis tool * Explore pandas through a framework of data analysis, with an explanation of how pandas is well suited for the various stages in a data analysis process * A comprehensive guide to pandas with many of clear and practical examples to help you get up and using pandas Who This Book Is For This book is ideal for data scientists, data analysts, Python programmers who want to plunge into data analysis using pandas, and anyone with a curiosity about analyzing data. Some knowledge of statistics and programming will be helpful to get the most out of this book but not strictly required. Prior exposure to pandas is also not required. What You Will Learn * Understand how data analysts and scientists think about of the processes of gathering and understanding data * Learn how pandas can be used to support the end-to-end process of data analysis * Use pandas Series and DataFrame objects to represent single and multivariate data * Slicing and dicing data with pandas, as well as combining, grouping, and aggregating data from multiple sources * How to access data from external sources such as files, databases, and web services * Represent and manipulate time-series data and the many of the intricacies involved with this type of data * How to visualize statistical information * How to use pandas to solve several common data representation and analysis problems within finance In Detail You will learn how to use pandas to perform data analysis in Python. You will start with an overview of data analysis and iteratively progress from modeling data, to accessing data from remote sources, performing numeric and statistical analysis, through indexing and performing aggregate analysis, and finally to visualizing statistical data and applying pandas to finance. With the knowledge you gain from this book, you will quickly learn pandas and how it can empower you in the exciting world of data manipulation, analysis and science. Style and approach * Step-by-step instruction on using pandas within an end-to-end framework of performing data analysis * Practical demonstration of using Python and pandas using interactive and incremental examples

Create attractive web-based data visualizations using the amazing JavaScript library D3.js About This Book * Learn to use the facilities provided by D3.js to create data-driven visualizations * Explore the concepts of D3.js through examples that enable you to quickly create visualizations including charts, network diagrams, and maps * Get practical examples of visualizations using real-world data sets that show you how to use D3.js to visualize and interact with information to glean its underlying meaning Who This Book Is For Whether you are new to data and data visualization, a seasoned data scientist, or a computer graphics specialist, this book will provide you with the skills you need to create web-based and interactive data visualizations. This book assumes some knowledge of coding and in particular, experience coding in JavaScript. What You Will Learn * Install and use D3.js to create HTML elements within the document * Use development tools such as JSBIN and Chrome Developer Tools to create D3.js applications * Retrieve JSON data and use D3.js selections and data binding to create visual elements from data * Create and style graphical elements such as circles, ellipses, rectangles, lines, paths, and text using SVG * Turn your data into bar and scatter charts, and add margins, axes, labels, and legends * Use D3.js generators to perform the magic of creating complex visualizations from data * Add interactivity to your visualizations, including tool-tips, sorting, hover-to-highlight, and grouping and dragging of visuals In Detail This book will take you through all the concepts of D3.js starting with the most basic ones and progressively building on them in each chapter to expand your knowledge of D3.js. Starting with obtaining D3.js and creating simple data bindings to non-graphical HTML elements, you will then master the creation of graphical elements from data. You'll discover how to combine those elements into simple visualizations such as bar, line, and scatter charts, as well as more elaborate visualizations such as network diagrams, Sankey diagrams, maps, and choreopleths. Using practical examples provided, you will quickly get to grips with the features of D3.js and use this learning to create your own spectacular data visualizations with D3.js. Style and approach This book uses a practical, step-by-step approach that builds iteratively, starting with the basic concepts right through to mastery of the technology. Each concept is demonstrated using code examples that are interactively available online (and can also be run locally), and each chapter builds upon the concepts covered in the previous chapter,with succinct explanations of what the code does and how it fits into the bigger picture.

About This Book A single source for learning how to use the features of pandas for financial and quantitative analysis. Explains many of the financial concepts including market risk, options valuation, futures calculation, and algorithmic trading strategies. Step-by-step demonstration with interactive and incremental examples to apply pandas to finance Who This Book Is ForIf you are interested in quantitative finance, financial modeling, and trading, or simply want to learn how Python and pandas can be applied to finance, then this book is ideal for you. Some knowledge of Python and pandas is assumed. Interest in financial concepts is helpful, but no prior knowledge is expected.

About This Book Employ the use of pandas for data analysis closely to focus more on analysis and less on programming Get programmers comfortable in performing data exploration and analysis on Python using pandas Step-by-step demonstration of using Python and pandas with interactive and incremental examples to facilitate learning Who This Book Is ForIf you are a Python programmer who wants to get started with performing data analysis using pandas and Python, this is the book for you. Some experience with statistical analysis would be helpful but is not mandatory.