How Data Mining is Useful to Companies?

How Data Mining is Useful to Companies?

Every business, organization and government bodies are collecting large amount of data for research and development. Such huge database can make them to have the information on hand when required. But most important is that it takes much time to find important information from the data. "If you want to grow rapidly, you must take quick and accurate decisions to grab timely available opportunities."

By applying the process of data mining, you can easily extract and filter required information from data. It is a processing of refining data and extracting important information. This process is mainly divided into 3 sections; pre-processing, mining and validation. In pre-processing, large amount of relevant data are collected. The mining section includes data classification, clustering, error correction and linking information. The last but important is validate without which you can not make trust on information. In short, data mining is a process of converting data into authentic information.

Let's have look on how data mining is useful to companies.

Fast and Feasible Decisions: To search information from huge bundle of data require more time. It also irritates a person who is doing such. With annoyed mind one can not take accurate decisions that's for sure. By having help of data mining, one can easily get information and make fast decisions. It also helps to compare information with various factors so the decisions become more reliable. Data mining is helpful in every decision to make it quick and feasible.

Powerful Strategies: After data mining, information becomes precise and easy to understand. While making strategies, one can easily analyze information in various dimensions. This analysis helps to get real idea about the strategy implementation. Management bodies can implement powerful strategies effectively to expand business boundaries.

Competitive Advantage: Information is easily available and precise so that one can compare it with competitors' information. It is very much required that you must compare the data otherwise you will have to suffer in business. After doing competitive analysis, one can make corrective decisions to go ahead from competitors. This way company can gain competitive advantage.

Your business can get all the benefits of data mining at cutting rates through outsourcing.

Source : http://ezinearticles.com/?How-Data-Mining-is-Useful-to-Companies?&id=2835042

Data Scrapping

Data Scrapping

People who are involved in business activities might have came across a term Data Scrapping. It is a process in which data or information can be extracted from the Portable Document Format file. They are easy to use tools that can automatically arrange the data that are found in different format in the internet. These advanced tools can collect useful information's according to the need of the user. What the user needs to do is simply enter the key words or phrases and the tool will extract all the related information available from the Portable Document Format file. It is widely used to take information's from the no editable format.

The main advantage of Portable Document Format files are they protect the originality of the document when you convert the data from Word to PDF. The size of the file is reduced by compression algorithems when the file are heavier due to the graphics or the images in the content. A Portable Document Format is independent of any software or hardware for installation. It allows encryption of files which enhances the security of your contents.

Although the Portable Document Format files have many advantages,it too have many other challenges. For example, you want to access a data that you found on the internet and the author encrypted the file preventing you from printing the file, you can easily do the scrapping process. These functions are easily available on the internet and the user can choose according to their needs. Using these programs you can extract the data that u need.

Source : http://ezinearticles.com/?Data-Scrapping&id=4951020

Data Extraction - A Guideline to Use Scrapping Tools Effectively

Data Extraction - A Guideline to Use Scrapping Tools Effectively

So many people around the world do not have much knowledge about these scrapping tools. In their views, mining means extracting resources from the earth. In these internet technology days, the new mined resource is data. There are so many data mining software tools are available in the internet to extract specific data from the web. Every company in the world has been dealing with tons of data, managing and converting this data into a useful form is a real hectic work for them. If this right information is not available at the right time a company will lose valuable time to making strategic decisions on this accurate information.

This type of situation will break opportunities in the present competitive market. However, in these situations, the data extraction and data mining tools will help you to take the strategic decisions in right time to reach your goals in this competitive business. There are so many advantages with these tools that you can store customer information in a sequential manner, you can know the operations of your competitors, and also you can figure out your company performance. And it is a critical job to every company to have this information at fingertips when they need this information.

To survive in this competitive business world, this data extraction and data mining are critical in operations of the company. There is a powerful tool called Website scraper used in online digital mining. With this toll, you can filter the data in internet and retrieves the information for specific needs. This scrapping tool is used in various fields and types are numerous. Research, surveillance, and the harvesting of direct marketing leads is just a few ways the website scraper assists professionals in the workplace.

Screen scrapping tool is another tool which useful to extract the data from the web. This is much helpful when you work on the internet to mine data to your local hard disks. It provides a graphical interface allowing you to designate Universal Resource Locator, data elements to be extracted, and scripting logic to traverse pages and work with mined data. You can use this tool as periodical intervals. By using this tool, you can download the database in internet to you spread sheets. The important one in scrapping tools is Data mining software, it will extract the large amount of information from the web, and it will compare that date into a useful format. This tool is used in various sectors of business, especially, for those who are creating leads, budget establishing seeing the competitors charges and analysis the trends in online. With this tool, the information is gathered and immediately uses for your business needs.

Another best scrapping tool is e mailing scrapping tool, this tool crawls the public email addresses from various web sites. You can easily from a large mailing list with this tool. You can use these mailing lists to promote your product through online and proposals sending an offer for related business and many more to do. With this toll, you can find the targeted customers towards your product or potential business parents. This will allows you to expand your business in the online market.

There are so many well established and esteemed organizations are providing these features free of cost as the trial offer to customers. If you want permanent services, you need to pay nominal fees. You can download these services from their valuable web sites also.

Source:http://ezinearticles.com/?Data-Extraction---A-Guideline-to-Use-Scrapping-Tools-Effectively&id=3600918

Scraping in PDF Files - Improving Accessibility

Scraping in PDF Files - Improving Accessibility

Scraping of data is one procedure where mechanically information is sorted out that is contained on the Net in HTML, PDF and various other documents. It is also about collecting relevant data and saving it in spreadsheets or databases for retrieval purposes. On a majority of sites, text content can be easily accessed in the source code however a good number of business houses are making use of Portable Document Format. This format had been launched by Adobe and documents in this format can be easily viewed on almost any operating system. Some people convert documents from word to PDF when they need sending files over the Net and many convert PDF to word so that they could edit their documents. The best benefit that one gets for making use of it is that documents look a replica of the original and there is no form of disturbance in viewing them as they appear organized and same on almost all operating systems. The downside of the format is that text in such files is converted into a picture or image and then copying and pasting it is not possible any more.

Scraping in this format is a procedure where data is scraped that is available in such files. Most diverse of the tools is needed in order to carry out scraping in a document that is created in this format. You'd find two main forms of PDF files where one is built from a text file and the other firm is where it is built from some image. There is software brought by Adobe itself which can capably do scraping in text based files. For files that are image-based, there is a need to make use of special application for the task.

OCR program is one primary tool to be used for such a matter. Optical Recognition Program is capable in scanning documents for small picture that can be segregated into letters. The pictures are compared with actual letters and given they match well; the letters get copied into one file. These programs are able to do scraping in an apt way in image-based files pretty much aptly however it cannot be said that they are perfect. Once the procedure is done you could search through data so as to find those areas and parts which you had been looking for. More often than not it is difficult to find a utility that can obtain exact data that is needed without proper customization. But if thoroughly checked, you cou

Source: http://ezinearticles.com/?Scraping-in-PDF-Files---Improving-Accessibility&id=6108439

Data Discovery vs. Data Extraction

Data Discovery vs. Data Extraction

Looking at screen-scraping at a simplified level, there are two primary stages involved: data discovery and data extraction. Data discovery deals with navigating a web site to arrive at the pages containing the data you want, and data extraction deals with actually pulling that data off of those pages. Generally when people think of screen-scraping they focus on the data extraction portion of the process, but my experience has been that data discovery is often the more difficult of the two.

The data discovery step in screen-scraping might be as simple as requesting a single URL. For example, you might just need to go to the home page of a site and extract out the latest news headlines. On the other side of the spectrum, data discovery may involve logging in to a web site, traversing a series of pages in order to get needed cookies, submitting a POST request on a search form, traversing through search results pages, and finally following all of the "details" links within the search results pages to get to the data you're actually after. In cases of the former a simple Perl script would often work just fine. For anything much more complex than that, though, a commercial screen-scraping tool can be an incredible time-saver. Especially for sites that require logging in, writing code to handle screen-scraping can be a nightmare when it comes to dealing with cookies and such.

In the data extraction phase you've already arrived at the page containing the data you're interested in, and you now need to pull it out of the HTML. Traditionally this has typically involved creating a series of regular expressions that match the pieces of the page you want (e.g., URL's and link titles). Regular expressions can be a bit complex to deal with, so most screen-scraping applications will hide these details from you, even though they may use regular expressions behind the scenes.

As an addendum, I should probably mention a third phase that is often ignored, and that is, what do you do with the data once you've extracted it? Common examples include writing the data to a CSV or XML file, or saving it to a database. In the case of a live web site you might even scrape the information and display it in the user's web browser in real-time. When shopping around for a screen-scraping tool you should make sure that it gives you the flexibility you need to work with the data once it's been extracted.

Source: http://ezinearticles.com/?Data-Discovery-vs.-Data-Extraction&id=165396

An Easy Way For Data Extraction

An Easy Way For Data Extraction

There are so many data scraping tools are available in internet. With these tools you can you download large amount of data without any stress. From the past decade, the internet revolution has made the entire world as an information center. You can obtain any type of information from the internet. However, if you want any particular information on one task, you need search more websites. If you are interested in download all the information from the websites, you need to copy the information and pate in your documents. It seems a little bit hectic work for everyone. With these scraping tools, you can save your time, money and it reduces manual work.

The Web data extraction tool will extract the data from the HTML pages of the different websites and compares the data. Every day, there are so many websites are hosting in internet. It is not possible to see all the websites in a single day. With these data mining tool, you are able to view all the web pages in internet. If you are using a wide range of applications, these scraping tools are very much useful to you.

The data extraction software tool is used to compare the structured data in internet. There are so many search engines in internet will help you to find a website on a particular issue. The data in different sites is appears in different styles. This scraping expert will help you to compare the date in different site and structures the data for records.

And the web crawler software tool is used to index the web pages in the internet; it will move the data from internet to your hard disk. With this work, you can browse the internet much faster when connected. And the important use of this tool is if you are trying to download the data from internet in off peak hours. It will take a lot of time to download. However, with this tool you can download any data from internet at fast rate.There is another tool for business person is called email extractor. With this toll, you can easily target the customers email addresses. You can send advertisement for your product to the targeted customers at any time. This the best tool to find the database of the customers.

However, there are some more scraping tolls are available in internet. And also some of esteemed websites are providing the information about these tools. You download these tools by paying a nominal amount.

Source: http://ezinearticles.com/?An-Easy-Way-For-Data-Extraction&id=3517104

Tapping The Mining Services Goldmine

Tapping The Mining Services Goldmine

In Australia, resources booms tend to come and go. In a recent speech, Reserve Bank Deputy Governor Ric Battellino identified five major booms over the last two hundred years - from the gold rush of the 1850s, to our current minerals and energy boom.

Many have argued that the current boom is different from anything we've experienced before, with the modernisation of the Chinese and Indian economies likely to keep demand high for decades. That's led some analysts to talk of a resources supercycle. And yet a supercycle is still a cycle.

By definition, cycles are uneven, with commodity prices ebbing and flowing in response to demand, economic conditions and market sentiment. And the share prices of resources companies tend to move with them.

Which raises the question: what's the best way for investors to tap into the potential of the mining boom, without the heart-stopping volatility that mining stocks sometimes deliver?
Invest in the store that sells the spade

Legend has it that the people who really profited from Australia's gold rush weren't the miners who flocked to the fields, but the store-owners who sold them their spades and pans. You can put the same principle to work today by investing in mining services and engineering companies.

Here are five reasons to consider giving mining services companies a place in your portfolio:

1. Growing demand

In November, the Australian Bureau of Agricultural and Resource Economics reported that mining and energy companies plan to invest a record $132.9bn in new projects, a 58% increase from the previous year. That includes 72 projects at an advanced stage of development, such as the $43bn Gorgon LNG project and the $20bn Olympic dam expansion. The mining services sector is poised to benefit from all of them.

The sector also stands to benefit from Australia's worsening skills shortage, with more companies looking to contractors to provide essential services in remote locations.

2. Less volatility

Resource stocks tend to fluctuate with commodity prices, which are subject to international economic forces and market sentiment beyond the control of any individual company. As a result, they are among the most volatile companies on the Australian sharemarket. But mining services stocks, while still exposed to the commodities cycle, tend to be more stable.

3. More predictable cash flow

One reason for the comparative volatility of commodity companies is that their cash flow can be very variable. In the development phase, they need to make significant capital expenditure, often leading to negative cash flows. And while they enjoy healthy revenues in the production phase, that revenue may diminish as a resource is exhausted, unless they make further investments in exploration and development.
In contrast, mining services companies require comparatively little capital investment, with more predictable cash flows over the long-term.

4. Higher dividends

Predictable cash flows and lower capital expenditures often allow services companies to pay out more of their earnings as dividends, making them more appealing for income-oriented investors.

5. No need to pick winners

Many miners are highly leveraged to demand for a single commodity, whether it's gold, coal, copper or iron ore. Some are reliant on a single mine or field. Whereas services companies generally have a more diversified customer base.

Source: http://ezinearticles.com/?Tapping-The-Mining-Services-Goldmine&id=5924837

What are the ethics of web scraping?

What are the ethics of web scraping?

Someone recently asked: "Is web scraping an ethical concept?" I believe that web scraping is absolutely an ethical concept. Web scraping (or screen scraping) is a mechanism to have a computer read a website. There is absolutely no technical difference between an automated computer viewing a website and a human-driven computer viewing a website. Furthermore, if done correctly, scraping can provide many benefits to all involved.

There are a bunch of great uses for web scraping. First, services like Instapaper, which allow saving content for reading on the go, use screen scraping to save a copy of the website to your phone. Second, services like Mint.com, an app which tells you where and how you are spending your money, uses screen scraping to access your bank's website (all with your permission). This is useful because banks do not provide many ways for programmers to access your financial data, even if you want them to. By getting access to your data, programmers can provide really interesting visualizations and insight into your spending habits, which can help you save money.

That said, web scraping can veer into unethical territory. This can take the form of reading websites much quicker than a human could, which can cause difficulty for the servers to handle it. This can cause degraded performance in the website. Malicious hackers use this tactic in what’s known as a "Denial of Service" attack.

Another aspect of unethical web scraping comes in what you do with that data. Some people will scrape the contents of a website and post it as their own, in effect stealing this content. This is a big no-no for the same reasons that taking someone else's book and putting your name on it is a bad idea. Intellectual property, copyright and trademark laws still apply on the internet and your legal recourse is much the same. People engaging in web scraping should make every effort to comply with the stated terms of service for a website. Even when in compliance with those terms, you should take special care in ensuring your activity doesn't affect other users of a website.

One of the downsides to screen scraping is it can be a brittle process. Minor changes to the backing website can often leave a scraper completely broken. Herein lies the mechanism for prevention: making changes to the structure of the code of your website can wreak havoc on a screen scraper's ability to extract information. Periodically making changes that are invisible to the user but affect the content of the code being returned is the most effective mechanism to thwart screen scrapers. That said, this is only a set-back. Authors of screen scrapers can always update them and, as there is no technical difference between a computer-backed browser and a human-backed browser, there's no way to 100% prevent access.

Going forward, I expect screen scraping to increase. One of the main reasons for screen scraping is that the underlying website doesn't have a way for programmers to get access to the data they want. As the number of programmers (and the need for programmers) increases over time, so too will the need for data sources. It is unreasonable to expect every company to dedicate the resources to build a programmer-friendly access point. Screen scraping puts the onus of data extraction on the programmer, not the company with the data, which can work out well for all involved.

Source: https://quickleft.com/blog/is-web-scraping-ethical/

How to do data scraping from PDF files using PHP?

How to do data scraping from PDF files using PHP?

Situations arise when you want to scrap data from PDF or want to search PDF files for matching text. Suppose you have website where users uploads PDF files and you want to give search functionality to user which searches all uploaded PDF file content for matching text and show all PDFs that contains matching search keywords.

Or you might have all London real estate properties details in PDF report file and you want to quickly grab scrape data from PDF reports then you might need PDF scraping library.

To integrate such functionality to web application is not similar to normal search functionality that we do with database search.

Here is the straight solution for this problem. This involves PDF Data Scraping to plain text and match search terms. I have written this post for the people who want to do PDF data scraping or want to make their PDF files to be Searchable.

We are going to use class named class.pdf2text.php which converts PDF text to into ASCII text, so the class is known for PDF extraction. This PHP class ignores anything in PDF that is not a text.

Let’s see very basic example (Taken from author’s file):

<?php

include "class.pdf2text.php";

$a = new PDF2Text();
$a->setFilename('web-scraping-service.pdf'); //grab the pdf file reside in folder where PHP files resides.

$a->decodePDF();//converts PDF content to text
echo $a->output();

?>

“Web Scraping is a technique using which programmer can automate the copy paste manual work and save the time. This is PDF w eb scraping using PHP. We at Web Data Scraping offer Web Scraping and Data Scraping Service. Vist our website www.webdata-scraping.com”

For more complex extraction you can apply regular expression on the text you get and can parse text that you want from PDF. But keep in mind this has limitation and do not work with all types of PDF extraction.

But the wonderful use of this class is to make utility that allow user to search inside PDF when they search on web search bar. Last but not least, You can also find many PDF scraping software available in market that can do complex scraping from PDF files.

Source: http://webdata-scraping.com/data-scraping-pdf-files-using-php/

Powerful Web Scraping Software – Content Grabber Review

Powerful Web Scraping Software – Content Grabber Review

There are many web scraping software and cloud based web scraping services available in the market for extracting data from the websites. They vary widely in cost and features. In this article, I am going to introduce one such advanced web scraping tool “Content Grabber”, which is widely used and the best web scraping software in the market.

Content Grabber is used for web extraction, web scraping and web automation. It can extract content from complex websites and export it as structured data in a variety of formats like Excel Spreadsheets, XML, CSV and databases. Content Grabber can also extract data from highly dynamic websites. It can extract from AJAX-enabled websites, submit forms repeatedly to cover all possible input values, and manage website logins.

Content Grabber is designed to be reliable, scalable and customizable. It is specifically designed for users with a critical reliance on web scraping and web data extraction. It also enables you to make standalone web scraping agents which you can market and sell as your own royalty free web scraping software.

Applications of Content Grabber:

The following are the few applications of Content Grabber:

•     Data aggregation – for example news aggregation.
•     Competitive pricing and monitoring e.g. monitor dealers for price compliance.
•     Financial and Market Research e.g. Make proactive buying and selling decisions by continuously receiving corporate operational data.
•     Content Integration i.e. integration of data from various sources at one place.
•     Business Directory Scraping – for example: yellow pages scraping, yelp scraping, superpages scraping etc.
•     Extracting company data from yellow pages for scraping common data fields like Business Name, Address, Telephone, Fax, Email, Website and Category of Business.
•     Extracting eBay auction data like: eBay Product Name, Store Information, Buy it Now prices, Product Price, List Price, Seller Price and many more.
•     Extracting Amazon product data: Information such as Product title, cost, description, details, availability, shipping info, ASIN, rating, rank, etc can be extracted.

Content Grabber Features:

The following section highlights some of the key features of Content Grabber:

1. Point and Click Interface

The Content Grabber editor has an easy to use point and click interface that provides easy point and click configuration. One simply needs to click on web elements to configure website navigation and content capture.

2. Easy to Use

The Content Grabber point and click interface is so simple to use that it can easily be used by beginners and non-programmers. There is certain built in facilities that automatically detect and configure all commands. It will automatically create a list of links, lists of content, manage pagination, handle web pages, download or upload files and capture any action you perform on a web page. You can also manually configure the agent commands, so Content Grabber gives you both simplicity and control.

3. Reliable and Scalable

Content Grabber’s powerful features like testing and debugging, solid error handling and error recovery, allows agent to run in the most difficult scenarios. It easily handles and scrapes dynamic websites built with JavaScript and AJAX. Content Grabber’s Intelligent agents don’t break with most site structure changes. These features enable us to build reliable web scraping agents. There are various configurations and performance tuning options that makes Content Grabber scalable. You can build as many web scraping agents as you want with Content Grabber.

4. High Performance

Multi-threading is used to increase the performance in Content Grabber. Content Grabber uses optimized web browsers. It uses static browsers for static web pages and dynamic browsers for dynamic web pages. It has an ultra-fast HTML5 parser for ultra-fast web scraping. One can use many web browsers concurrently to boost performance.

5. Debugging, Logging and Error Handling

Content Grabber has robust support for debugging, error handling and logging. Using a debugger, you can test and debug the web scraping agents which helps you to build reliable and error free web scraping solutions because most of the issues are addressed at design time. Content Grabber allows agent logging with three detail levels: Log URLs, Log raw HTML, Log to database or file. Logs can be useful to identify problems that occurred during execution of a web scraping agent. Content Grabber supports automatic error handling and custom error handling through scripting. Error status reports can also be mailed to administrators.

6. Scripting

Content Grabber comes with a built in script editor with IntelliSense that one can use in case of some unusual requirements or to fine tune some process. Scripting can be used to control agent behaviour, content transformation, customize data export and delivery and to generate data inputs for agent.

7. Unlimited Web Scraping Agents

Content Grabber allows building an unlimited number of Self-Contained Web Scraping Agents. Self-Contained agents are a standalone executable that can be run independently, branded as your own and distributed royalty free. Content Grabber provides an easy to use and effective GUI to manage all the agents. One can view status and logs of all the agents or run and schedule the agents in one centralized location.

8. Automation

Require data on a schedule? Weekly? Everyday? Each hour? Content Grabber allows automating and publishing extracted data. Configure Content Grabber by telling what data you want once, and then schedule it to run automatically.

And much more

There are too many features that Content Grabber provides, but here are a few more that may be useful and interest you.

•     Schedule agents
•     Manage proxies
•     Custom notification criteria and messages
•     Email notifications
•     Handle websites logins
•     Capture Screenshots of web elements or entire web page or save as PDF.
•     Capture hidden content on web page.
•     Crawl entire website
•     Input data from almost any data source.
•     Auto scroll to load dynamic data
•     Handle complex JAVASCRIPT and AJAX actions
•     XPATH support
•     Convert Images to Text
•     CAPTCHA handling
•     Extract data from non-HTML documents like PDF and Word Documents
•     Multi-threading and multiple web browsers
•     Run agent from command line.

The above features come with the Professional edition license. Content Grabber’s Premium edition license is available with the following extra features:

1. Visual Studio 2013 integration

One can integrate Content Grabber to Visual Studio and take advantages of extra powerful script editing, debugging, and unit testing.

2. Remove Content Grabber branding

One can remove Content Grabber branding from the Content Grabber agents and distribute the executable.

3. Custom Design Templates

One can customize the Content Grabber agent user interface design with custom HTML templates – e.g. add your own company branding.

4. Royalty free distribution

One can distribute the Content Grabber agent to anybody without paying royalty fees and can run agents from the command line anywhere.

5. Programming Interface

Programming interfaces like Desktop API, Web API and windows service for building and editing agents.

6. Custom Web Scraping Application Development:

Content Grabber provides API and Visual Studio Integration which developer can use to build custom web scraping applications. It provides full control of the user interface and export functionality. One can develop both Desktop as well as Web based custom web scraping applications using the Content Grabber programming interface. It is a great tool and provides opportunity for developers to build general web scraping applications and sell those to generate revenue.

Are you looking for web scraping services? Do you need any assistance related to Content Grabber? We can probably help you to achieve your scraping-based project goals. We would be more than happy to hear from you.

Source: http://webdata-scraping.com/powerful-web-scraping-software-content-grabber/

How Web Scraping for Brand Monitoring is used in Retail Sector

How Web Scraping for Brand Monitoring is used in Retail Sector

Structured or unstructured, business data always plays an instrumental part in driving growth, development, and innovation for your dream venture. Irrespective of industrial sectors or verticals, big data, seems to be of paramount significance for every business or enterprise.

The unsurpassed popularity and increasing importance of big data gave birth to the concept of web scraping, thus enhancing growth opportunities for startups. Large or small, every business establishment will now achieve successful website monitoring and tracking.
How web scraping serves your branding need?

Web scraping helps in extracting unorganized data and ordering it into organized and manageable formats. So if your brand is being talked about in multiple ways (on social media, on expert forums, in comments etc.), you can set the scraping tool algorithm to fetch only data that contains reference about the brand. As an outcome, marketers and business owners around the brand can gauge brand sentiment and tweak their launch marketing campaign to enhance visibility.

Look around and you will discover numerous web scraping solutions ranging from manual to fully automated systems. From Reputation Tracking to Website monitoring, your web scraper can help create amazing insights from seemingly random bits of data (both in structured as well as unstructured format).
Using web scraping

The concept of web scraping revolutionizes the use of big data for business. With its availability across sectors, retailers are on cloud nine. Here’s how the retail market is utilizing the power of Web Scraping for brand monitoring.

Determining pricing strategy

The retail market is filled with competition. Whether it is products or pricing strategies, every retailer competes hard to stay ahead of the growth curve. Web scraping techniques will help you crawl price comparison sites’ pricing data, product descriptions, as well as images to receive data for comparison, affiliation, or analytics.

As a result, retailers will have the opportunity to trade their products at competitive prices, thus increasing profit margins by a whopping 10%.

Tracking online presence

Current trends in ecommerce herald the need for a strong online presence. Web scraping takes cue from this particular aspect, thus scraping reviews and profiles on websites. By providing you a crystal clear picture of product performance, customer behavior, and interactions, web scraping will help you achieve Online Brand Intelligence and monitoring.
Detection of fraudulent reviews

Present-day purchasers have this unique habit of referring to reviews, before finalizing their purchase decisions. Web scraping helps in the identification of opinion-spamming, thus figuring out fake reviews. It will further extend support in detecting, reviewing, streamlining, or blocking reviews, according to your business needs.
Online reputation management

Web data scraping helps in figuring out avenues to take your ORM objectives forward. With the help of the scraped data, you learn about both the impactful as well as vulnerable areas for online reputation management. You will have the web crawler identifying demographic opinions such as age group, gender, sentiments, and GEO location.

Social media analytics

Since social media happens to be one of the most crucial factors for retailers, it will be imperative to Scrape Social Media websites and extract data from Twitter. The web scraping technology will help you watch your brand in Social Media along with fetching Data for social media analytics. With social media channels such as Twitter monitoring services, you will strengthen your firm’s’ branding even more than before.
Advantages of BM

As a business, you might want to monitor your brand in social media to gain deep insights about your brand’s popularity and the current consumer behavior. Brand monitoring companies will watch your brand in social media and come up with crucial data for social media analytics. This process has immense benefits for your business, these are summarized over here –

Locate Infringers

Leading brands often face the challenge thrown by infringers. When brand monitoring companies keep a close look at products available in the market, there is less probability of a copyright infringement. The biggest infringement happens in the packaging, naming and presentation of products. With constant monitoring and legal support provided by the Trademark Law, businesses could remain protected from unethical competitors and illicit business practices.

Manage Consumer Reaction and Competitor’s Challenges

A good business keeps a check on the current consumer sentiment in the targeted demographic and positively manages the same in the interest of their brand. The feedback from your consumers could be affirmative or negative but if you have a hold on the social media channels, web platforms and forums, you, as a brand will be able to propagate trust at all times.

When competitor brands indulge in backbiting or false publicity about your brand, you can easily tame their negative comments by throwing in a positive image in front of your target audience. So, brand monitoring and its active implementation do help in positive image building and management for businesses.
Why Web scraping for BM?

Web scraping for brand monitoring gives you a second pair of eyes to look at your brand as a general consumer. Considering the flowing consumer sentiment in the market during a specific business season, you could correct or simply innovate better ways to mold the target audience in your brand’s favor. Through a systematic approach towards online brand intelligence and monitoring, future business strategies and possible brand responses could be designed, keeping your business actively prepared for both types of scenarios.

For effective web scraping, businesses extract data from Twitter that helps them understand ‘what’s trending’ in their business domain. They also come closer to reality in terms of brand perception, user interaction and brand visibility in the notions of their clientele. Web scraping professionals or companies scrape social media websites to gather relevant data related to your brand or your competitor’s that has the potential to affect your growth as a business. Management and organization of this data is done to extract out significant and reference building facts. Future strategy for your brand is designed by brand monitoring professionals keeping in mind the facts accumulated through web scraping. The data obtained through web scraping helps in –

Knowing the actual brand potential,
Expanding brand coverage,
Devising brand penetration,
Analyzing scope and possibilities for a brand and
Design thoughtful and insightful brand strategies.

In simple words, web scraping provides a business enough base of information that could be used to devise future plans and to make suggestive changes in the current business strategy.

Advantages of Web scraping for BM

Web scraping has made things seamless for businesses involved in managing their brands and active brand monitoring. There is no doubt, that web scraping for brand monitoring comes with immense benefits, some of these are –

Improved customer insight

When you have in hand and factual knowledge about your consumer base through social media channels, you are in a strong position to portray your positive image as a brand. With more realistic data on your hands, you could develop strategies more effectively and make realistic goals for your brand’s improvement. Social media insights also allows marketers to create highly targeted and custom marketing messages – thus leading to better likelihood of sales conversion.

Monitoring your Competition

Web scraping helps you realize where your brand stands in the market among the competition. The actual penetration of your brand in the targeted segment helps in getting a clear picture of your present business scenario. Through careful removal of competition in your concerned business category, you could strengthen your brand image.

Staying Informed

When your brand monitoring team is keeping track of all social media channels, it becomes easier for you to stay informed about latest comments about your business on sites like Facebook, Twitter and social forums etc. You could have deep knowledge about the consumer behavior related to your brand and your competitors on these web destinations.

Improved Consumer Satisfaction and Sales

Reputation tracking done through web scraping helps in generating planned response at times of crisis. It also mends the communication gap between consumer and the brand, hence improving the consumer satisfaction. This automatically translates into trust building and brand loyalty improving your brand’s sales.

To sign off

By granting opportunities to monitor your social media data, web scraping is undoubtedly helping retail businesses take a significant step towards perfect branding. If you are one of the key players in this sector, there’s reason for celebration ahead!

Source: https://www.promptcloud.com/blog/How-Web-Scraping-for-Brand-Monitoring-is-used-in-Retail-Sector

How Web Scraping can Help you Detect Weak spots in your Business

How Web Scraping can Help you Detect Weak spots in your Business

Business intelligence is not a new term. Businesses have always been employing experts for analysing the progress, market and industry trends to keep their growth graph going up. Now that we have big data and the tool to gather this data – Web scraping, business intelligence has become even more fruitful. In fact, business intelligence has become a necessary thing to survive now that the competition is fierce in every industry. This is the reason why most enterprises depend on web scraping solutions to gather the data relevant to their businesses. This data is highly insightful and dependable enough to make critical business decisions. Business intelligence from web scraping is definitely a game changer for companies as it can supply relevant and actionable data with minimal effort.

Most businesses have weak spots that are being overlooked or hidden from the plain sight. These weak spots, if left unnoticed can gradually result in the downfall of your company. Here is how you can use data acquired through web scraping to detect weak spots in your business and strengthen them.

Competitor analysis

Many a times, you can find out the flaws in your business by keeping a close watch on your competitors. Competitor analysis is something that we owe to web scraping as the level of competitive intelligence that you can derive from web scraping has never been achievable in the past. With crawling forums and social media sites where your target audience is, you can easily find out if your competitor is leveraging something you have overlooked. Competitor analysis is all about staying updated to each and every action by your competitors, so that you can always be prepared for their next strategic move. If your competitors are doing better than you, this data can be used to make a comparison between your business and theirs which would give you insights on where you lack.

Brand monitoring on Social media

With social media platforms acting like platforms where businesses and customers can interact with each other, the data available on these sites are increasingly becoming relevant to businesses. Any issues in your business operations will also reflect on your customer sentiments. Social media is a goldmine of sentiment data that can help you detect issues within your company. By analysing the posts that mention your brand or product on social media sites, you can identify what department of your company is functioning well and what isn’t.

For example, if you are an Ecommerce portal and many users are complaining about delivery issues from your company on social media, you might want to switch to a better logistics partner who does a better job. The ability to identify such issues at the earliest is extremely important and that’s where web scraping becomes a life saver. With social media scraping, monitoring your brand on social media is easy like never before and the chances of minor issues escalating to bigger ones is almost non-existent. Brand monitoring is extremely crucial if you are a business operating in the online space. Social media scraping solutions are provided by many leading web scraping companies, which totally eliminates the technical complications associated with the process for you.

Finding untapped opportunities

There are always new and untapped markets and opportunities that are relevant to your business. Finding them is not going to be an easy task with manual and outdated methods of research. Web scraping can fill this gap and help you find opportunities that your company can make use of to leverage your reach and progress. Sometimes, targeting the right audience makes all the difference that you’ve been trying to make. By using web crawling to find mentions of your relevant keywords on the web, you can easily stay updated on your niche and fill in to any new untapped markets. Web crawling for keywords is better explained in our previous blog.

Bottom line

It is not a cakewalk to stay ahead in the competition considering how competitive every industry has become in this digital age. It is crucial to find the weak spots and untapped opportunities of your business before someone else does. Of course, you can always use some help from the technology when you need it. Web scraping is clearly the best way to find and gather data that would help you figure these out. With web crawling solutions that can completely take care of this niche process, nothing is stopping you from using the data and insights that the web has in stock for your business.

Source: https://www.promptcloud.com/blog/web-scraping-detect-weak-spots-business

ERP Data Conversions - Best Practices and Steps

ERP Data Conversions - Best Practices and Steps

Every company who has gone through an ERP project has gone through the painful process of getting the data ready for the new system. The process of executing this typically goes through the following steps:

(1) Extract or define

(2) Clean and transform

(3) Load

(4) Validate and verify

This process is typically executed multiple times (2 - 5+ times depending on complexity) through an ERP project to ensure that the good data ends up in the new system. If the data is either incorrect, not well enough cleaned or adjusted or loaded incorrectly in to the new system it can cause serious problems as the new system is launched.

(1) Extract or define

This involves extracting the data from legacy systems, which are to be decommissioned. In some cases the data may not exist in a legacy system, as the old process may be spreadsheet-based and has to be created from scratch. Typically this involves creating some extraction programs or leveraging existing reports to get the data in to a format which can be put in to a spreadsheet or a data management application.

(2) Data cleansing

Once extracted it normally reviewed is for accuracy by the business, supported by the IT team, and/or adjusted if incorrect or in a structure which the new ERP system does not understand. Depending on the level of change and data quality this can represent a significant effort involving many business stakeholders and required to go through multiple cycles.

(3) Load data to new system

As the data gets structured to a format which the receiving ERP system can handle the load programs may also be build to handle certain changes as part of the process of getting the data converted in to the new system. Data is loaded in to interface tables and loaded in to the new system's core master data and transactions tables.

When loading the data in to the new system the inter-dependency of the different data elements is key to consider and validate the cross dependencies. Exceptions are dealt with and go in to lessons learned and to modify extracts, data cleansing or load process in to the next cycle.

(4) Validate and verify

The final phase of the data conversion process is to verify the converted data through extracts, reports or manually to ensure that all the data went in correctly. This may also include both internal and external audit groups and all the key data owners. Part of the testing will also include attempting to transact using the converted data successfully.

The topmost success factors or best practices to execute a successful conversion I would prioritize as follows:

(1) Start the data conversion early enough by assessing the quality of the data. Starting too late can result in either costly project delays or decisions to load garbage and "deal with it later" resulting in an increase in problems as the new system is launched.

(2) Identify and assign data owners and customers (often forgotten) for the different elements. Ensure that not only the data owners sign-off on the data conversions but that also the key users of the data are involved in reviewing the selection criteria's, data cleansing process and load verification.

(3) Run sufficient enough rounds of testing of the data, including not only validating the loads but also transacting with the converted data.

(4) Depending on the complexity, evaluate possible tools beyond spreadsheets and custom programming to help with the data conversion process for cleansing, transformation and load process.

(5) Don't under-estimate the effort in cleansing and validating the converted data.

(6) Define processes and consider other tools to help how the accuracy of the data will be maintained after the system goes live.

Source: http://ezinearticles.com/?ERP-Data-Conversions---Best-Practices-and-Steps&id=7263314

Web Scraping Best Practices

Web Scraping Best Practices

Extracting data from the World Wide Web has several challenges as more webmasters are working day and night to lower cases of scraping and crawling of their data in order to survive in the competitive world. There are various other problems you may face when web scraping and most of them can be avoided by adapting and implementing certain web scraping best practices as discussed in this article.

Have knowledge of the scraping tools

Acquiring adequate knowledge of hurdles that may be encountered during web scraping, you will be able to have a smooth web scraping experience and be on the safe side of the law. Conduct a thorough research on the types of tools you will use for scraping and crawling. Firsthand knowledge on these tools will help you find the data you need without being blocked.

Proper proxy software that acts as the middle party works well when you know how to work around HTTP and HTML protocols. Use tools that can change crawling patterns, URLs and data retrieved even when you are crawling on one domain. This will help you abide to the rules and regulations that come with web scraping activities and escaping any legal issues.
Conduct your scraping activities during off-peak hours

You may opt to extract data during times that less people have access for instance over the weekends, during late night hours, public holidays among others. Visiting a website on several instances to retrieve the same type of data is a waste of bandwidth. It is always advisable to download the entire site content to your computer and thereafter you can access it whenever need arises.
Hide your scrapping activities

There is a thin line between ethical and unethical crawling hence you should completely evade being on the top user list of a particular website. Cover up your track as best as you can by making use of proxy IPs to avoid any legal problems. You may also use multiple IP addresses or VPN services to conceal your scrapping activities and lower chances of landing on a website’s blacklist.

Website owners today are very protective of their data and any other information existing under their unique url. Be keen when going through the terms and conditions indicated by websites as they may consider crawling as an infringement of their privacy. Simple etiquette goes a long way. Your web scraping efforts will be fruitful if the site owner supports the idea of sharing data.
Keep record of your activities

Web scraping involves large amount of data.Due to this you may not always remember each and every piece of information you have acquired, gathering statistics will help you monitor your activities.
Load data in phases

Web scraping demands a lot of patience from you when using the crawlers to get needed information. Take the process in a slow manner by loading data one piece at a time. Several parallel request to the same domain can crush the entire site or retrace the scrapping attempts back to your local machine.

Loading data small bits will save you the hustle of scrapping afresh in case that your activity has been interrupted because you will have already stored part of the data required. You can reduce the loading data on an individual domain through various techniques such as caching pages that you have scrapped to escape redundancy occurrences. Use auto throttling mechanisms to increase the amount of traffic to the website and pause for breaks between requests to prevent getting banned.
Conclusion

Through these few mentioned web scraping best practices you will be able to work around website and gather the data required as per clients’ request without major hurdles along the way. The ultimate goal of every web scraper is to be able to access vital information and at the same time remain on the good side of the law.

Source: http://nocodewebscraping.com/web-scraping-best-practices/

Data Mining vs Screen-Scraping

Data Mining vs Screen-Scraping

Data mining isn't screen-scraping. I know that some people in the room may disagree with that statement, but they're actually two almost completely different concepts.

In a nutshell, you might state it this way: screen-scraping allows you to get information, where data mining allows you to analyze information. That's a pretty big simplification, so I'll elaborate a bit.

The term "screen-scraping" comes from the old mainframe terminal days where people worked on computers with green and black screens containing only text. Screen-scraping was used to extract characters from the screens so that they could be analyzed. Fast-forwarding to the web world of today, screen-scraping now most commonly refers to extracting information from web sites. That is, computer programs can "crawl" or "spider" through web sites, pulling out data. People often do this to build things like comparison shopping engines, archive web pages, or simply download text to a spreadsheet so that it can be filtered and analyzed.

Data mining, on the other hand, is defined by Wikipedia as the "practice of automatically searching large stores of data for patterns." In other words, you already have the data, and you're now analyzing it to learn useful things about it. Data mining often involves lots of complex algorithms based on statistical methods. It has nothing to do with how you got the data in the first place. In data mining you only care about analyzing what's already there.

The difficulty is that people who don't know the term "screen-scraping" will try Googling for anything that resembles it. We include a number of these terms on our web site to help such folks; for example, we created pages entitled Text Data Mining, Automated Data Collection, Web Site Data Extraction, and even Web Site Ripper (I suppose "scraping" is sort of like "ripping"). So it presents a bit of a problem-we don't necessarily want to perpetuate a misconception (i.e., screen-scraping = data mining), but we also have to use terminology that people will actually use.

Source: http://ezinearticles.com/?Data-Mining-vs-Screen-Scraping&id=146813

Best Alternative For Linkedin Data Scraping

Best Alternative For Linkedin Data Scraping

When I started my career in sales, one of the things that my VP of sales told me is that ” In sales, assumptions are the mother of all f**k ups “. I know the F word sounds a bit inappropriate, but that is the exact word he used. He was trying to convey the simple point that every prospect is different, so don’t guess, use data to come up with decisions.

I joined Datahut and we are working on a product that helps sales people. I thought I should discuss it with you guys and take your feedback.

Let me tell you how the idea evolved itself. At Datahut, we get to hear a lot of problems customers want to solve. Almost 30 percent of all the inbound leads ask us to help them with lead generation.

Most of them simply ask, “Can you scrape Linkedin for me”?

Every time, we politely refused.

But not anymore, we figured out a way to solve their problem without scraping Linkedin.

This should raise some questions in your mind.

1) What problem is he trying to solve?– Most of the time their sales team does not have the accurate data about the prospects. This leads to a total chaos. It will end up in a waste of both time and money by selling the leads that are not sales qualified.

2) Why do they need data specifically from Linkedin? – LinkedIn is the world’s largest business network. In his view, there is no better place to find leads for his business than Linkedin. It is right in a way.

3) Ok, then what is wrong in scraping Linkedin? – Scraping Linkedin is against its terms and it can lead to legal issues. Linkedin has an excellent anti-scraping mechanism which can make the scraping costly.

4) How severe is the problem? – The problem has a direct impact on the revenues as the productivity of the sales team is too low. Without enough sales, the company is a joke.

5) Is there a better way? – Of course yes. The people with profiles in LinkedIn are in other sites too. eg. Google plus, CrunchBase etc. If we can mine and correlate the data, we can generate leads with rich information. It will have better quality than scraping LinkedIn.

6) What to do when the machine intelligence fails? – We have to use human intelligence. Period!

Datahut is working on a platform that can help you get leads that match your ideal buyer persona. It will be a complete Business intelligence platform powered by machine and human intelligence for an efficient lead research & discovery.We named it Leadintel. We’ve also established some partnerships that help to enrich the data and saves the trouble of lawsuits.

We are opening our platform for beta users. You can request an invitation using the contact form. What do you think about this? What are your suggestions?

Thanks for reading this blog post. Datahut offers affordable data extraction services (DaaS) . If you need help with your web scraping projects let us know and we will be glad to help.

Source:http://blog.datahut.co/best-alternative-for-linkedin-data-scraping/

Python 3 web-scraping examples with public data

Someone on the NICAR-L listserv asked for advice on the best Python libraries for web scraping. My advice below includes what I did for last spring’s Computational Journalism class, specifically, the Search-Script-Scrape project, which involved 101-web-scraping exercises in Python.

Best Python libraries for web scraping

For the remainder of this post, I assume you’re using Python 3.x, though the code examples will be virtually the same for 2.x. For my class last year, I had everyone install the Anaconda Python distribution, which comes with all the libraries needed to complete the Search-Script-Scrape exercises, including the ones mentioned specifically below:

The best package for general web requests, such as downloading a file or submitting a POST request to a form, is the simply-named requests library (“HTTP for Humans”).

Here’s an overly verbose example:

import requests
base_url = 'http://maps.googleapis.com/maps/api/geocode/json'
my_params = {'address': '100 Broadway, New York, NY, U.S.A',
             'language': 'ca'}
response = requests.get(base_url, params = my_params)
results = response.json()['results']
x_geo = results[0]['geometry']['location']
print(x_geo['lng'], x_geo['lat'])
# -74.01110299999999 40.7079445

For the parsing of HTML and XML, Beautiful Soup 4 seems to be the most frequently recommended. I never got around to using it because it was malfunctioning on my particular installation of Anaconda on OS X.
But I’ve found lxml to be perfectly fine. I believe both lxml and bs4 have similar capabilities – you can even specify lxml to be the parser for bs4. I think bs4 might have a friendlier syntax, but again, I don’t know, as I’ve gotten by with lxml just fine:

import requests
from lxml import html
page = requests.get("http://www.example.com").text
doc = html.fromstring(page)
link = doc.cssselect("a")[0]
print(link.text_content())
# More information...
print(link.attrib['href'])
# http://www.iana.org/domains/example

The standard urllib package also has a lot of useful utilities – I frequently use the methods from urllib.parse. Python 2 also has urllib but the methods are arranged differently.

Here’s an example of using the urljoin method to resolve the relative links on the California state data for high school test scores. The use of os.path.basename is simply for saving the each spreadsheet to your local hard drive:

from os.path import basename
from urllib.parse import urljoin
from lxml import html
import requests
base_url = 'http://www.cde.ca.gov/ds/sp/ai/'
page = requests.get(base_url).text
doc = html.fromstring(page)
hrefs = [a.attrib['href'] for a in doc.cssselect('a')]
xls_hrefs = [href for href in hrefs if 'xls' in href]
for href in xls_hrefs:
  print(href) # e.g. documents/sat02.xls
  url = urljoin(base_url, href)
  with open("/tmp/" + basename(url), 'wb') as f:
    print("Downloading", url)
    # Downloading http://www.cde.ca.gov/ds/sp/ai/documents/sat02.xls
    data = requests.get(url).content
    f.write(data)

And that’s about all you need for the majority of web-scraping work – at least the part that involves reading HTML and downloading files.
Examples of sites to scrape

The 101 scraping exercises didn’t go so great, as I didn’t give enough specifics about what the exact answers should be (e.g. round the numbers? Use complete sentences?) or even where the data files actually were – as it so happens, not everyone Googles things the same way I do. And I should’ve made them do it on a weekly basis, rather than waiting till the end of the quarter to try to cram them in before finals week.

The Github repo lists each exercise with the solution code, the relevant URL, and the number of lines in the solution code.

The exercises run the gamut of simple parsing of static HTML, to inspecting AJAX-heavy sites in which knowledge of the network panel is required to discover the JSON files to grab. In many of these exercises, the HTML-parsing is the trivial part – just a few lines to parse the HTML to dynamically find the URL for the zip or Excel file to download (via requests)…and then 40 to 50 lines of unzipping/reading/filtering to get the answer. That part is beyond what typically considered “web-scraping” and falls more into “data wrangling”.

I didn’t sort the exercises on the list by difficulty, and many of the solutions are not particulary great code. Sometimes I wrote the solution as if I were teaching it to a beginner. But other times I solved the problem using the style in the most randomly bizarre way relative to how I would normally solve it – hey, writing 100+ scrapers gets boring.

But here are a few representative exercises with some explanation:
1. Number of datasets currently listed on data.gov

I think data.gov actually has an API, but this script relies on finding the easiest tag to grab from the front page and extracting the text, i.e. the 186,569 from the text string, "186,569 datasets found". This is obviously not a very robust script, as it will break when data.gov is redesigned. But it serves as a quick and easy HTML-parsing example.
29. Number of days until Texas’s next scheduled execution

Texas’s death penalty site is probably one of the best places to practice web scraping, as the HTML is pretty straightforward on the main landing pages (there are several, for scheduled and past executions, and current inmate roster), which have enough interesting tabular data to collect. But you can make it more complex by traversing the links to collect inmate data, mugshots, and final words. This script just finds the first person on the scheduled list and does some math to print the number of days until the execution (I probably made the datetime handling more convoluted than it needs to be in the provided solution)
3. The number of people who visited a U.S. government website using Internet Explorer 6.0 in the last 90 days

The analytics.usa.gov site is a great place to practice AJAX-data scraping. It’s a very simple and robust site, but either you are aware of AJAX and know how to use the network panel (and in this case, locate ie.json, or you will have no clue how to scrape even a single number on this webpage. I think the difference between static HTML and AJAX sites is one of the tougher things to teach novices. But they pretty much have to learn the difference given how many of today’s websites use both static and dynamically-rendered pages.
6. From 2010 to 2013, the change in median cost of health, dental, and vision coverage for California city employees

There’s actually no HTML parsing if you assume the URLs for the data files can be hard coded. So besides the nominal use of the requests library, this ends up being a data-wrangling exercise: download two specific zip files, unzip them, read the CSV files, filter the dictionaries, then do some math.
90. The currently serving U.S. congressmember with the most Twitter followers

Another example with no HTML parsing, but probably the most complicated example. You have to download and parse Sunlight Foundation’s CSV of Congressmember data to get all the Twitter usernames. Then authenticate with Twitter’s API, then perform mulitple batch lookups to get the data for all 500+ of the Congressional Twitter usernames. Then join the sorted result with the actual Congressmember identity. I probably shouldn’t have assigned this one.
HTML is not necessary

I included no-HTML exercises because there are plenty of data programming exercises that don’t have to deal with the specific nitty-gritty of the Web, such as understanding HTTP and/or HTML. It’s not just that a lot of public data has moved to JSON (e.g. the FEC API) – but that much of the best public data is found in bulk CSV and database files. These files can be programmatically fetched with simple usage of the requests library.

It’s not that parsing HTML isn’t a whole boatload of fun – and being able to do so is a useful skill if you want to build websites. But I believe novices have more than enough to learn from in sorting/filtering dictionaries and lists without worrying about learning how a website works.

Besides analytics.usa.gov, the data.usajobs.gov API, which lists federal job openings, is a great one to explore, because its data structure is simple and the site is robust. Here’s a Python exercise with the USAJobs API; and here’s one in Bash.

There’s also the Google Maps geocoding API, which can be hit up for a bit before you run into rate limits, and you get the bonus of teaching geocoding concepts. The NYTimes API requires creating an account, but you not only get good APIs for some political data, but for content data (i.e. articles, bestselling books) that is interesting fodder for journalism-related analysis.

But if you want to scrape HTML, then the Texas death penalty pages are the way to go, because of the simplicity of the HTML and the numerous ways you can traverse the pages and collect interesting data points. Besides the previously mentioned Texas Python scraping exercise, here’s one for Florida’s list of executions. And here’s a Bash exercise that scrapes data from Texas, Florida, and California and does a simple demographic analysis.

If you want more interesting public datasets – most of which require only a minimal of HTML-parsing to fetch – check out the list I talked about in last week’s info session on Stanford’s Computational Journalism Lab.

Source URL :  http://blog.danwin.com/examples-of-web-scraping-in-python-3-x-for-data-journalists/

Python 3 web-scraping examples with public data

Someone on the NICAR-L listserv asked for advice on the best Python libraries for web scraping. My advice below includes what I did for last spring’s Computational Journalism class, specifically, the Search-Script-Scrape project, which involved 101-web-scraping exercises in Python.

Best Python libraries for web scraping

For the remainder of this post, I assume you’re using Python 3.x, though the code examples will be virtually the same for 2.x. For my class last year, I had everyone install the Anaconda Python distribution, which comes with all the libraries needed to complete the Search-Script-Scrape exercises, including the ones mentioned specifically below:
The best package for general web requests, such as downloading a file or submitting a POST request to a form, is the simply-named requests library (“HTTP for Humans”).

Here’s an overly verbose example:

import requests
base_url = 'http://maps.googleapis.com/maps/api/geocode/json'
my_params = {'address': '100 Broadway, New York, NY, U.S.A',
             'language': 'ca'}
response = requests.get(base_url, params = my_params)
results = response.json()['results']
x_geo = results[0]['geometry']['location']
print(x_geo['lng'], x_geo['lat'])
# -74.01110299999999 40.7079445

For the parsing of HTML and XML, Beautiful Soup 4 seems to be the most frequently recommended. I never got around to using it because it was malfunctioning on my particular installation of Anaconda on OS X.
But I’ve found lxml to be perfectly fine. I believe both lxml and bs4 have similar capabilities – you can even specify lxml to be the parser for bs4. I think bs4 might have a friendlier syntax, but again, I don’t know, as I’ve gotten by with lxml just fine:

import requests
from lxml import html
page = requests.get("http://www.example.com").text
doc = html.fromstring(page)
link = doc.cssselect("a")[0]
print(link.text_content())
# More information...
print(link.attrib['href'])
# http://www.iana.org/domains/example

The standard urllib package also has a lot of useful utilities – I frequently use the methods from urllib.parse. Python 2 also has urllib but the methods are arranged differently.

Here’s an example of using the urljoin method to resolve the relative links on the California state data for high school test scores. The use of os.path.basename is simply for saving the each spreadsheet to your local hard drive:

from os.path import basename
from urllib.parse import urljoin
from lxml import html
import requests
base_url = 'http://www.cde.ca.gov/ds/sp/ai/'
page = requests.get(base_url).text
doc = html.fromstring(page)
hrefs = [a.attrib['href'] for a in doc.cssselect('a')]
xls_hrefs = [href for href in hrefs if 'xls' in href]
for href in xls_hrefs:
  print(href) # e.g. documents/sat02.xls
  url = urljoin(base_url, href)
  with open("/tmp/" + basename(url), 'wb') as f:
    print("Downloading", url)
    # Downloading http://www.cde.ca.gov/ds/sp/ai/documents/sat02.xls
    data = requests.get(url).content
    f.write(data)

And that’s about all you need for the majority of web-scraping work – at least the part that involves reading HTML and downloading files.
Examples of sites to scrape

The 101 scraping exercises didn’t go so great, as I didn’t give enough specifics about what the exact answers should be (e.g. round the numbers? Use complete sentences?) or even where the data files actually were – as it so happens, not everyone Googles things the same way I do. And I should’ve made them do it on a weekly basis, rather than waiting till the end of the quarter to try to cram them in before finals week.

The Github repo lists each exercise with the solution code, the relevant URL, and the number of lines in the solution code.

The exercises run the gamut of simple parsing of static HTML, to inspecting AJAX-heavy sites in which knowledge of the network panel is required to discover the JSON files to grab. In many of these exercises, the HTML-parsing is the trivial part – just a few lines to parse the HTML to dynamically find the URL for the zip or Excel file to download (via requests)…and then 40 to 50 lines of unzipping/reading/filtering to get the answer. That part is beyond what typically considered “web-scraping” and falls more into “data wrangling”.

I didn’t sort the exercises on the list by difficulty, and many of the solutions are not particulary great code. Sometimes I wrote the solution as if I were teaching it to a beginner. But other times I solved the problem using the style in the most randomly bizarre way relative to how I would normally solve it – hey, writing 100+ scrapers gets boring.

But here are a few representative exercises with some explanation:
1. Number of datasets currently listed on data.gov

I think data.gov actually has an API, but this script relies on finding the easiest tag to grab from the front page and extracting the text, i.e. the 186,569 from the text string, "186,569 datasets found". This is obviously not a very robust script, as it will break when data.gov is redesigned. But it serves as a quick and easy HTML-parsing example.
29. Number of days until Texas’s next scheduled execution

Texas’s death penalty site is probably one of the best places to practice web scraping, as the HTML is pretty straightforward on the main landing pages (there are several, for scheduled and past executions, and current inmate roster), which have enough interesting tabular data to collect. But you can make it more complex by traversing the links to collect inmate data, mugshots, and final words. This script just finds the first person on the scheduled list and does some math to print the number of days until the execution (I probably made the datetime handling more convoluted than it needs to be in the provided solution)
3. The number of people who visited a U.S. government website using Internet Explorer 6.0 in the last 90 days

The analytics.usa.gov site is a great place to practice AJAX-data scraping. It’s a very simple and robust site, but either you are aware of AJAX and know how to use the network panel (and in this case, locate ie.json, or you will have no clue how to scrape even a single number on this webpage. I think the difference between static HTML and AJAX sites is one of the tougher things to teach novices. But they pretty much have to learn the difference given how many of today’s websites use both static and dynamically-rendered pages.
6. From 2010 to 2013, the change in median cost of health, dental, and vision coverage for California city employees

There’s actually no HTML parsing if you assume the URLs for the data files can be hard coded. So besides the nominal use of the requests library, this ends up being a data-wrangling exercise: download two specific zip files, unzip them, read the CSV files, filter the dictionaries, then do some math.
90. The currently serving U.S. congressmember with the most Twitter followers

Another example with no HTML parsing, but probably the most complicated example. You have to download and parse Sunlight Foundation’s CSV of Congressmember data to get all the Twitter usernames. Then authenticate with Twitter’s API, then perform mulitple batch lookups to get the data for all 500+ of the Congressional Twitter usernames. Then join the sorted result with the actual Congressmember identity. I probably shouldn’t have assigned this one.
HTML is not necessary

I included no-HTML exercises because there are plenty of data programming exercises that don’t have to deal with the specific nitty-gritty of the Web, such as understanding HTTP and/or HTML. It’s not just that a lot of public data has moved to JSON (e.g. the FEC API) – but that much of the best public data is found in bulk CSV and database files. These files can be programmatically fetched with simple usage of the requests library.

It’s not that parsing HTML isn’t a whole boatload of fun – and being able to do so is a useful skill if you want to build websites. But I believe novices have more than enough to learn from in sorting/filtering dictionaries and lists without worrying about learning how a website works.

Besides analytics.usa.gov, the data.usajobs.gov API, which lists federal job openings, is a great one to explore, because its data structure is simple and the site is robust. Here’s a Python exercise with the USAJobs API; and here’s one in Bash.

There’s also the Google Maps geocoding API, which can be hit up for a bit before you run into rate limits, and you get the bonus of teaching geocoding concepts. The NYTimes API requires creating an account, but you not only get good APIs for some political data, but for content data (i.e. articles, bestselling books) that is interesting fodder for journalism-related analysis.

But if you want to scrape HTML, then the Texas death penalty pages are the way to go, because of the simplicity of the HTML and the numerous ways you can traverse the pages and collect interesting data points. Besides the previously mentioned Texas Python scraping exercise, here’s one for Florida’s list of executions. And here’s a Bash exercise that scrapes data from Texas, Florida, and California and does a simple demographic analysis.

If you want more interesting public datasets – most of which require only a minimal of HTML-parsing to fetch – check out the list I talked about in last week’s info session on Stanford’s Computational Journalism Lab.

Source URL :  http://blog.danwin.com/examples-of-web-scraping-in-python-3-x-for-data-journalists/

Web Data Scraping: Practical Uses

Whether in the form of media, text or data in diverse other formats—the internet serves to be a huge storehouse of the world’s information. While browsing for commercial or business needs alike, users are exposed to numerous web pages that contain data in just about every form. Even though access to such data is extremely critical for garnering success in the contemporary world, unfortunately most of it is not open. More often than not, business websites restrict the accessibility options to such data and do not allow visitors to save or display them for reuse on their local storage devices, or onto their own websites.  This is where web data extraction tools come in handy.

Read on for a closer look into some of the common areas of data scraping usage.

• Gathering of data from diverse sources for analysis: In case a business necessitates the collection and analysis of data specific to certain categories from multiple websites, then it helps refer to web data integration experts or those related to the field of data scraping linked with categories like industrial equipment, real estate, automobiles, marketing, business contacts, electronic gadgets and so forth.

• Collection of data in different formats: Different websites are known to publish information and structured data in different formats. So, it may not be possible for organizations to see all the required data a one place, at any given time. Data scrapers allow the extraction of information spanning across multiple pages under various sections, on to a single database or spreadsheet.  This makes it easy for users to analyze (or visualize) the data.

• Helps Research: Data is an important and integral part of all kinds of research – marketing, academic or scientific. A data scraper helps in gathering structured data with ease.

• Market analysis for businesses: Companies that cater to products or services connected to specific domains require comprehensive data of products and services that are of similar kind, and which have a tendency of appearing in the market on a daily basis.

Web scraping software solutions from reputed companies are successful in keeping a constant watch on this kind of data and allow users to get access required information from diverse sources – all at the click of a button.
Go for data extraction to take your business to the next levels of success – you will not be disappointed.

Source URL : http://www.3idatascraping.com/web-data-scraping-practical-uses.php

Data Scraping - What Are Hand-Scraped Hardwood Floors and What Are the Benefits?

If you love the look of hardwood flooring with lots of character, then you may want to check out hand-scraped hardwood flooring. Hand-scraped wood provides a warm vintage look, providing the floor instant character. These types of scraped hardwoods are suitable for living rooms, dining rooms, hallways and bedrooms. But what exactly is hand-scraped hardwood flooring?

Well, it is literally what you think it is. Hand-scraped hardwood flooring is created by hand using specialized wood working tools to make each board unique and giving an overall "old worn" appearance.

At Innovation Builders we offer solid wood floors finished on site with an actual hand-scraping technique followed by stain and sealer. Solid wood floors are installed by an expert team of technicians who work each board with skilled craftsman-like attention to detail. Following the scraping procedure the floor is stained by hand with a customer selected stain color, and then protected with multiple coats of sealing and finishing polyurethane. This finishing process of staining, sealing and coating the wood floors contributes to providing the look and durability of an old reclaimed wood floor, but with today's tough, urethane finishes.

There are many, many benefits to hand-scraped wood flooring. Overall, these floors are extremely durable and hard wearing, providing years of trouble-free use. These wood floors remain looking newer for longer because the texture that the process provides hides the typical dents, dings and scratches that other floors can't hide so easily. That's great news for households with kids, dogs, and cats.

These types of wood flooring have another unique advantage as well. When you do scratch these floors during their lifetime, the scratches are easily repaired. As long as the scratch isn't too deep you can make them practically disappear without ever having to hire a professional. It's simple to hide the scratch by using a color-matched stain marker or repair kit that is readily available through local flooring distributors. These features make hand-scraped hardwood flooring a lot more durable and hassle-free to maintain than other types of wood flooring.

The expert processes utilized in the creation of these floors provides a custom look of worn wood with deep color and subtle highlights. When the light hits the wood at different times during the day, it provides an understated but powerful effect of depth and beauty. They instantly offer your rooms a rustic look full of character, allowing your home to become a warm and inviting environment. The rustic look of this wood provides a texture, style and rustic appeal that cannot be matched by any other type of flooring.

Hand-Scraped Hardwood Flooring is a floor that says welcome and adds a touch of elegance to any home. If you are looking to buy a new home and you haven't had the opportunity to see or feel hand scraped hardwoods, stop in any of the model homes at Innovation Builders in Keller, North Richland Hills or Grand Prairie, Texas and check it out!

Source URL :   http://yellowpagesdatascraping.blogspot.in/2015/06/data-scraping-what-are-hand-scraped.html

Increasing Accessibility by Scraping Information From PDF

You may have heard about data scraping which is a method that is being used by computer programs in extracting data from an output that comes from another program. To put it simply, this is a process which involves the automatic sorting of information that can be found on different resources including the internet which is inside an html file, PDF or any other documents. In addition to that, there is the collection of pertinent information. These pieces of information will be contained into the databases or spreadsheets so that the users can retrieve them later.

Most of the websites today have text that can be accessed and written easily in the source code. However, there are now other businesses nowadays that choose to make use of Adobe PDF files or Portable Document Format. This is a type of file that can be viewed by simply using the free software known as the Adobe Acrobat. Almost any operating system supports the said software. There are many advantages when you choose to utilize PDF files. Among them is that the document that you have looks exactly the same even if you put it in another computer so that you can view it. Therefore, this makes it ideal for business documents or even specification sheets. Of course there are disadvantages as well. One of which is that the text that is contained in the file is converted into an image. In this case, it is often that you may have problems with this when it comes to the copying and pasting.

This is why there are some that start scraping information from PDF. This is often called PDF scraping in which this is the process that is just like data scraping only that you will be getting information that is contained in your PDF files. In order for you to begin scraping information from PDF, you must choose and exploit a tool that is specifically designed for this process. However, you will find that it is not easy to locate the right tool that will enable you to perform PDF scraping effectively. This is because most of the tools today have problems in obtaining exactly the same data that you want without personalizing them.

Nevertheless, if you search well enough, you will be able to encounter the program that you are looking for. There is no need for you to have programming language knowledge in order for you to use them. You can easily specify your own preferences and the software will do the rest of the work for you. There are also companies out there that you can contact and they will perform the task since they have the right tools that they can use. If you choose to do things manually, you will find that this is indeed tedious and complicated whereas if you compare this to having professionals do the job for you, they will be able to finish it in no time at all. Scraping information from PDF is a process where you collect the information that can be found on the internet and this does not infringe copyright laws.

 Source  URL : http://ezinearticles.com/?Increasing-Accessibility-by-Scraping-Information-From-PDF&id=4593863

Web Scraping to Create Open Data

Open data is the idea that some data should be freely available to everyone to use and republish as they wish, without restrictions from
copyright, patents or other mechanisms of control.

My first experience with open data was in the year 2010. I wanted to create a better app for Bicing, the local bike sharing system in
Barcelona. Their website was a nightmare to use and I was tired of needing to walk to each station, trying to guess which ones had bicycles.
There was no app for Android, other than a couple of unofficial attempts that didn’t work at all.

I began as most would; I searched the internet and found a library named python-bicing that was somehow able to retrieve station and
bike information. This was my first time using Python and, after some investigation, I learned what the code was doing: accessing the
official website, parsing the JavaScript that generated their buggy map and giving back a nice chunk of Python objects that represented
bike share stations.

This I learned was called web scraping. It was like I had figured out a magic trick that would allow me to always be able to access the data I
needed without having to rely on faulty websites.

The rise of OpenBicing and CityBikes

Shortly after, I launched OpenBicing, an Android app for the local bike sharing system in Barcelona, together with a backend that used
python-bicing. I also shared a public API that provided this information so that nobody else had to do the dirty work ever again.

Since other cities were having the same problem, we expanded the scope of the project worldwide and renamed it CityBikes. That was 6
years ago.

To date, CityBikes is the most comprehensive and widely used open API for bike sharing information, with support for over 400 cities
worldwide. Our API processes around 10 requests per second and we scrape each of the 418 feeds about every three minutes. Making our
core library available for anyone to contribute has been crucial in maintaining and adding coverage for all of the supported systems.

The open data fallacy

We are usually regarded as “an open data project” even though less than 10% of our feeds come from properly licensed, documented and
machine-readable feeds. The remaining 90% is composed of 188 feeds that are machine-readable, but not licensed nor documented and
230 that are entirely maintained by scraping HTML pages.

North American BikeShare Association) recently published GBFS (General Bikeshare Feed Specification). This is clearly a step in the right
direction, but I can’t help but look at the almost 60% of services we currently support through scraping and wonder how long it will take the
remaining organizations to release their information, if ever. This is even more the case considering these numbers aren’t even taking into
account worldwide coverage.

Over the last few years there has been a progression by transportation companies and city councils toward providing their information as
“open data”. Directive 2003/98/EC encourages EU member states to release information regarding public services.

Yet, in most cases, there’s little action in enforcing Public Private Partnerships (PPP) to release their public information under a non-
restrictive license or even to transfer ownership of the data to city councils to be included in their open data portals.

Even with the increasing number of companies and institutions interested in participating in open data, by no means should we consider
open data a reality or something to be taken for granted. I firmly believe in the future and benefits of open data, I have seen them
happening all around CityBikes, but as technologists we need to stress the fact that the data is not out there yet.

The benefits of open data

When I started this project, I sought to make a difference in Barcelona. Now you can find tons of bike sharing apps that use our API on all
major platforms. It doesn’t matter that these are not our own apps. They are solving the same problem we were trying to fix, so their
success is our success.

Besides popular apps like Moovit or CityMapper, there are many neat projects out there, some of which are published under free software
licenses. Ideally, a city council could create a customization of any of these apps for their own use.

Most official applications for bike sharing systems have terrible ratings. The core business of transportation companies is running a service,

so they have no real motivation to create an engaging UI or innovate further. In some cases, the city council does not even own the rights to
the data, being completely at the mercy of the company providing the transportation service.

Open data over apps

When providing public services, city councils and companies often get lost in what they should offer as an aid to the service. They focus on
a nice map or a flashy application, rather than providing the data behind these service aids. Maps, apps, and websites have a limited focus
and usually serve a single purpose. On the other hand, data is malleable and the purest form of representation. While you can’t create
something new from looking and playing with a static map (except, of course, if you scrape it), data can be used to create countless
different iterations. It can even provide a bridge that will allow anyone to participate, improve and build on top of these public services.

Wrap Up

At this point, you might wonder why I care so much about bike sharing. To me it’s not about bike sharing anymore. CityBikes is just too
good of an open data metaphor, a simulation in which public information is freely accessible to everyone. It shows the benefits of open
data and the deficiencies that arise from the lack thereof.

We shouldn’t have to create open data by scraping websites. This information should be already available, easily accessed and provided in
a machine-readable format from the original providers, be they city councils or transportation companies. However, until there’s another
option, we’ll always have scraping.


Source : https://blog.scrapinghub.com/2016/03/30/web-scraping-to-create-open-data/

Taking a cue from the Ryanair screen scraping judgment

Screen scraping is the best way to aggregate web data much faster than a human possibly can. However, is there any such thing known as ethical web scraping?

Well it’s not scraping in itself that is good or bad. What matters is how you use the scraped data. It would be extremely unethical to steal data, republish it or use it to cause harm to a business. This was clearly established when the EU passed a judgment in favour of Ryanair.

The EU’s highest court passed a judgment in favour of Ryan air, and this will positively prevent people from scraping and using others data in an unethical manner. Ryanair had claimed that PR Aviation scraped its data regarding the flight scheduled and then used it to allow people book Ryanair flights via the PR Aviation website and this is clearly an infringement of database rights.

Source:http://www.habiledata.com/blog/taking-cue-ryanair-screen-scraping-judgment/