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Practical Web Scraping For Data Science


Practical Web Scraping For Data Science
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Practical Web Scraping For Data Science


Practical Web Scraping For Data Science
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Author : Seppe vanden Broucke
language : en
Publisher: Apress
Release Date : 2018-04-18

Practical Web Scraping For Data Science written by Seppe vanden Broucke and has been published by Apress this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-04-18 with Computers categories.


This book provides a complete and modern guide to web scraping, using Python as the programming language, without glossing over important details or best practices. Written with a data science audience in mind, the book explores both scraping and the larger context of web technologies in which it operates, to ensure full understanding. The authors recommend web scraping as a powerful tool for any data scientist’s arsenal, as many data science projects start by obtaining an appropriate data set. Starting with a brief overview on scraping and real-life use cases, the authors explore the core concepts of HTTP, HTML, and CSS to provide a solid foundation. Along with a quick Python primer, they cover Selenium for JavaScript-heavy sites, and web crawling in detail. The book finishes with a recap of best practices and a collection of examples that bring together everything you've learned and illustrate various data science use cases. What You'll Learn Leverage well-established best practices and commonly-used Python packages Handle today's web, including JavaScript, cookies, and common web scraping mitigation techniques Understand the managerial and legal concerns regarding web scraping Who This Book is For A data science oriented audience that is probably already familiar with Python or another programming language or analytical toolkit (R, SAS, SPSS, etc). Students or instructors in university courses may also benefit. Readers unfamiliar with Python will appreciate a quick Python primer in chapter 1 to catch up with the basics and provide pointers to other guides as well.



Web Scraping With Python


Web Scraping With Python
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Author : Ryan Mitchell
language : en
Publisher: "O'Reilly Media, Inc."
Release Date : 2015-06-15

Web Scraping With Python written by Ryan Mitchell and has been published by "O'Reilly Media, Inc." this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-06-15 with Computers categories.


Learn web scraping and crawling techniques to access unlimited data from any web source in any format. With this practical guide, you’ll learn how to use Python scripts and web APIs to gather and process data from thousands—or even millions—of web pages at once. Ideal for programmers, security professionals, and web administrators familiar with Python, this book not only teaches basic web scraping mechanics, but also delves into more advanced topics, such as analyzing raw data or using scrapers for frontend website testing. Code samples are available to help you understand the concepts in practice. Learn how to parse complicated HTML pages Traverse multiple pages and sites Get a general overview of APIs and how they work Learn several methods for storing the data you scrape Download, read, and extract data from documents Use tools and techniques to clean badly formatted data Read and write natural languages Crawl through forms and logins Understand how to scrape JavaScript Learn image processing and text recognition



Automated Data Collection With R


Automated Data Collection With R
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Author : Simon Munzert
language : en
Publisher: John Wiley & Sons
Release Date : 2014-12-18

Automated Data Collection With R written by Simon Munzert and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-12-18 with Computers categories.


A hands on guide to web scraping and text mining for both beginners and experienced users of R Introduces fundamental concepts of the main architecture of the web and databases and covers HTTP, HTML, XML, JSON, SQL. Provides basic techniques to query web documents and data sets (XPath and regular expressions). An extensive set of exercises are presented to guide the reader through each technique. Explores both supervised and unsupervised techniques as well as advanced techniques such as data scraping and text management. Case studies are featured throughout along with examples for each technique presented. R code and solutions to exercises featured in the book are provided on a supporting website.



Web Scraping For Data Science With Python


Web Scraping For Data Science With Python
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Author : Seppe vanden Broucke
language : en
Publisher: Createspace Independent Publishing Platform
Release Date : 2017-11-30

Web Scraping For Data Science With Python written by Seppe vanden Broucke and has been published by Createspace Independent Publishing Platform this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-11-30 with categories.


Get Started with Web Scraping using Python! Congratulations! By picking up this book, you've set the first steps into the exciting world of web scraping. For those who are not familiar with programming or the deeper workings of the web, web scraping often looks like a black art: the ability to write a program that sets off on its own to explore the Internet and collect data is seen as a magical and exciting ability to possess. In this book, we set out to provide a concise and modern guide to web scraping, using Python as our programming language, without glossing over important details or best practices. In addition, this book is written with a data science audience in mind. We're data scientists ourselves, and have very often found web scraping to be a powerful tool to have in your arsenal, as many data science projects start with the first step of obtaining an appropriate data set, so why not utilize the treasure trove of information the web provides. As such, we've strived to offer a guide that: Is concise and to the point, whilst also being thorough Is geared towards data scientists: we'll show you how web scraping fits into the data science workflow Takes a "code first" approach to get you up to speed quickly without too much boilerplate text Is modern by using well-established best practices and Python packages only Shows how to handle the web of today, including JavaScript, cookies, and common web scraping mitigation techniques Includes a thorough managerial and legal discussion regarding web scraping Provides lots of pointers for further reading and learning Includes many larger, fully worked out examples Chapter Overview Nine chapters are included in this book. In Chapter 1, we provide a brief overview on web scraping and real-life use cases and make sure your Python environment is set up correctly. In Chapter 2, you'll learn the basics regarding HTTP, the core piece of technology behind the web, and the requests Python library. In Chapter 3, we start working with HTML and CSS sites, using the Beautiful Soup library. Chapter 4 returns to HTTP, exploring it more detail. Chapter 5 introduces the Selenium library, which you'll use to scrape JavaScript-heavy websites. Chapter 6 explains web crawling in detail. In Chapter 7, an in-depth discussion regarding managerial and legal concerns is provided. Chapter 8 recaps best practices and provides pointers to other tools. Chapter 9 includes fourteen, fully worked out web scraping examples bringing everything you've learned together, and illustrates various interesting data science oriented use cases.



Getting Structured Data From The Internet


Getting Structured Data From The Internet
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Author : Jay M. Patel
language : en
Publisher: Apress
Release Date : 2020-12-13

Getting Structured Data From The Internet written by Jay M. Patel and has been published by Apress this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-12-13 with Computers categories.


Utilize web scraping at scale to quickly get unlimited amounts of free data available on the web into a structured format. This book teaches you to use Python scripts to crawl through websites at scale and scrape data from HTML and JavaScript-enabled pages and convert it into structured data formats such as CSV, Excel, JSON, or load it into a SQL database of your choice. This book goes beyond the basics of web scraping and covers advanced topics such as natural language processing (NLP) and text analytics to extract names of people, places, email addresses, contact details, etc., from a page at production scale using distributed big data techniques on an Amazon Web Services (AWS)-based cloud infrastructure. It book covers developing a robust data processing and ingestion pipeline on the Common Crawl corpus, containing petabytes of data publicly available and a web crawl data set available on AWS's registry of open data. Getting Structured Data from the Internet also includes a step-by-step tutorial on deploying your own crawlers using a production web scraping framework (such as Scrapy) and dealing with real-world issues (such as breaking Captcha, proxy IP rotation, and more). Code used in the book is provided to help you understand the concepts in practice and write your own web crawler to power your business ideas. What You Will Learn Understand web scraping, its applications/uses, and how to avoid web scraping by hitting publicly available rest API endpoints to directly get data Develop a web scraper and crawler from scratch using lxml and BeautifulSoup library, and learn about scraping from JavaScript-enabled pages using Selenium Use AWS-based cloud computing with EC2, S3, Athena, SQS, and SNS to analyze, extract, and store useful insights from crawled pages Use SQL language on PostgreSQL running on Amazon Relational Database Service (RDS) and SQLite using SQLalchemy Review sci-kit learn, Gensim, and spaCy to perform NLP tasks on scraped web pages such as name entity recognition, topic clustering (Kmeans, Agglomerative Clustering), topic modeling (LDA, NMF, LSI), topic classification (naive Bayes, Gradient Boosting Classifier) and text similarity (cosine distance-based nearest neighbors) Handle web archival file formats and explore Common Crawl open data on AWS Illustrate practical applications for web crawl data by building a similar website tool and a technology profiler similar to builtwith.com Write scripts to create a backlinks database on a web scale similar to Ahrefs.com, Moz.com, Majestic.com, etc., for search engine optimization (SEO), competitor research, and determining website domain authority and ranking Use web crawl data to build a news sentiment analysis system or alternative financial analysis covering stock market trading signals Write a production-ready crawler in Python using Scrapy framework and deal with practical workarounds for Captchas, IP rotation, and more Who This Book Is For Primary audience: data analysts and scientists with little to no exposure to real-world data processing challenges, secondary: experienced software developers doing web-heavy data processing who need a primer, tertiary: business owners and startup founders who need to know more about implementation to better direct their technical team



Applied Data Science In Tourism


Applied Data Science In Tourism
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Author : Roman Egger
language : en
Publisher: Springer Nature
Release Date : 2022-01-31

Applied Data Science In Tourism written by Roman Egger and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-01-31 with Business & Economics categories.


Access to large data sets has led to a paradigm shift in the tourism research landscape. Big data is enabling a new form of knowledge gain, while at the same time shaking the epistemological foundations and requiring new methods and analysis approaches. It allows for interdisciplinary cooperation between computer sciences and social and economic sciences, and complements the traditional research approaches. This book provides a broad basis for the practical application of data science approaches such as machine learning, text mining, social network analysis, and many more, which are essential for interdisciplinary tourism research. Each method is presented in principle, viewed analytically, and its advantages and disadvantages are weighed up and typical fields of application are presented. The correct methodical application is presented with a "how-to" approach, together with code examples, allowing a wider reader base including researchers, practitioners, and students entering the field. The book is a very well-structured introduction to data science – not only in tourism – and its methodological foundations, accompanied by well-chosen practical cases. It underlines an important insight: data are only representations of reality, you need methodological skills and domain background to derive knowledge from them - Hannes Werthner, Vienna University of Technology Roman Egger has accomplished a difficult but necessary task: make clear how data science can practically support and foster travel and tourism research and applications. The book offers a well-taught collection of chapters giving a comprehensive and deep account of AI and data science for tourism - Francesco Ricci, Free University of Bozen-Bolzano This well-structured and easy-to-read book provides a comprehensive overview of data science in tourism. It contributes largely to the methodological repository beyond traditional methods. - Rob Law, University of Macau



Hands On Web Scraping With Python


Hands On Web Scraping With Python
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Author : Anish Chapagain
language : en
Publisher:
Release Date : 2019

Hands On Web Scraping With Python written by Anish Chapagain and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019 with categories.


Collect and scrape different complexities of data from the modern Web using the latest tools, best practices, and techniques Key Features Learn different scraping techniques using a range of Python libraries such as Scrapy and Beautiful Soup Build scrapers and crawlers to extract relevant information from the web Automate web scraping operations to bridge the accuracy gap and manage complex business needs Book Description Web scraping is an essential technique used in many organizations to gather valuable data from web pages. This book will enable you to delve into web scraping techniques and methodologies. The book will introduce you to the fundamental concepts of web scraping techniques and how they can be applied to multiple sets of web pages. You'll use powerful libraries from the Python ecosystem such as Scrapy, lxml, pyquery, and bs4 to carry out web scraping operations. You will then get up to speed with simple to intermediate scraping operations such as identifying information from web pages and using patterns or attributes to retrieve information. This book adopts a practical approach to web scraping concepts and tools, guiding you through a series of use cases and showing you how to use the best tools and techniques to efficiently scrape web pages. You'll even cover the use of other popular web scraping tools, such as Selenium, Regex, and web-based APIs. By the end of this book, you will have learned how to efficiently scrape the web using different techniques with Python and other popular tools. What you will learn Analyze data and Information from web pages Learn how to use browser-based developer tools from the scraping perspective Use XPath and CSS selectors to identify and explore markup elements Learn to handle and manage cookies Explore advanced concepts in handling HTML forms and processing logins Optimize web securities, data storage, and API use to scrape data Use Regex with Python to extract data Deal with complex web entities by using Selenium to find and extract data Who this book is for This book is for Python programmers, data analysts, web scraping newbies, and anyone who wants to learn how to perform web scraping from scratch. If you want to begin your journey in applying web scraping techniques to a range of web pages, then this book is what you need! A working knowledge of the Python programming language is expected. Downloading the example code for this ebook: You can download the example code files for this ebook ...



R Web Scraping Quick Start Guide


R Web Scraping Quick Start Guide
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Author : Olgun Aydin
language : en
Publisher: Packt Publishing Ltd
Release Date : 2018-10-31

R Web Scraping Quick Start Guide written by Olgun Aydin and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-10-31 with Computers categories.


Web Scraping techniques are getting more popular, since data is as valuable as oil in 21st century. Through this book get some key knowledge about using XPath, regEX; web scraping libraries for R like rvest and RSelenium technologies. Key FeaturesTechniques, tools and frameworks for web scraping with RScrape data effortlessly from a variety of websites Learn how to selectively choose the data to scrape, and build your datasetBook Description Web scraping is a technique to extract data from websites. It simulates the behavior of a website user to turn the website itself into a web service to retrieve or introduce new data. This book gives you all you need to get started with scraping web pages using R programming. You will learn about the rules of RegEx and Xpath, key components for scraping website data. We will show you web scraping techniques, methodologies, and frameworks. With this book's guidance, you will become comfortable with the tools to write and test RegEx and XPath rules. We will focus on examples of dynamic websites for scraping data and how to implement the techniques learned. You will learn how to collect URLs and then create XPath rules for your first web scraping script using rvest library. From the data you collect, you will be able to calculate the statistics and create R plots to visualize them. Finally, you will discover how to use Selenium drivers with R for more sophisticated scraping. You will create AWS instances and use R to connect a PostgreSQL database hosted on AWS. By the end of the book, you will be sufficiently confident to create end-to-end web scraping systems using R. What you will learnWrite and create regEX rulesWrite XPath rules to query your dataLearn how web scraping methods workUse rvest to crawl web pagesStore data retrieved from the webLearn the key uses of Rselenium to scrape dataWho this book is for This book is for R programmers who want to get started quickly with web scraping, as well as data analysts who want to learn scraping using R. Basic knowledge of R is all you need to get started with this book.



Web Scraping With Python


Web Scraping With Python
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Author : Richard Lawson
language : en
Publisher: Packt Publishing Ltd
Release Date : 2015-10-28

Web Scraping With Python written by Richard Lawson and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-10-28 with Computers categories.


Successfully scrape data from any website with the power of Python About This Book A hands-on guide to web scraping with real-life problems and solutions Techniques to download and extract data from complex websites Create a number of different web scrapers to extract information Who This Book Is For This book is aimed at developers who want to use web scraping for legitimate purposes. Prior programming experience with Python would be useful but not essential. Anyone with general knowledge of programming languages should be able to pick up the book and understand the principals involved. What You Will Learn Extract data from web pages with simple Python programming Build a threaded crawler to process web pages in parallel Follow links to crawl a website Download cache to reduce bandwidth Use multiple threads and processes to scrape faster Learn how to parse JavaScript-dependent websites Interact with forms and sessions Solve CAPTCHAs on protected web pages Discover how to track the state of a crawl In Detail The Internet contains the most useful set of data ever assembled, largely publicly accessible for free. However, this data is not easily reusable. It is embedded within the structure and style of websites and needs to be carefully extracted to be useful. Web scraping is becoming increasingly useful as a means to easily gather and make sense of the plethora of information available online. Using a simple language like Python, you can crawl the information out of complex websites using simple programming. This book is the ultimate guide to using Python to scrape data from websites. In the early chapters it covers how to extract data from static web pages and how to use caching to manage the load on servers. After the basics we'll get our hands dirty with building a more sophisticated crawler with threads and more advanced topics. Learn step-by-step how to use Ajax URLs, employ the Firebug extension for monitoring, and indirectly scrape data. Discover more scraping nitty-gritties such as using the browser renderer, managing cookies, how to submit forms to extract data from complex websites protected by CAPTCHA, and so on. The book wraps up with how to create high-level scrapers with Scrapy libraries and implement what has been learned to real websites. Style and approach This book is a hands-on guide with real-life examples and solutions starting simple and then progressively becoming more complex. Each chapter in this book introduces a problem and then provides one or more possible solutions.



Doing Data Science


Doing Data Science
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Author : Cathy O'Neil
language : en
Publisher: "O'Reilly Media, Inc."
Release Date : 2013-10-09

Doing Data Science written by Cathy O'Neil and has been published by "O'Reilly Media, Inc." this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-10-09 with Computers categories.


A guide to the usefulness of data science covers such topics as algorithms, logistic regression, financial modeling, data visualization, and data engineering.