Data Scraping – Will Definitely Benefit a Business Startup

With increasingly data shared using internet, the data collected as well as the usage cases are increasing with an unbelievable pace. We’ve entered into the “Big Data” age and data scraping is among the resources to supply big data engines, the latest data for analytical analytics, contest monitoring, or just to steal the data.

From the technology viewpoint, competent data scraping is fairly complicated. It has many open-source projects that allow anybody to run a web data scraper through him. Nevertheless it’s the entire different story while it needs to be an interior of the business as well as that you require not only maintaining your scrapers but also scaling them as well as extract the data smartly as you need.

That is the reason why different services are selling the “data scraping” as service. Their work is taking care about all the technical characteristics so that you can have the data required without any industrial knowledge. Fundamentally all these startups pay attention for collecting the data and then extract its value for selling it to the customers.

Let’s take some examples:

• Sales Intelligence – The scrapers monitor competitors, marketplaces, online directories, and data from the public markets to discover leads. For instance, some tool’s track websites that drop or add JavaScript tags from the competitors therefore you can call them as eligible leads.
• Price Intelligence – A very ordinary use is the price monitoring. If this is in with e-commerce, travel, or property industry monitoring competitors’ prices as well as adjusting yours consequently is generally the key. All these services monitor the prices and using the analytical algorithms they may provide you advice about where the puck can be.
• Marketing – Data scraping may also be used for monitoring how the competitors are doing. From the reviews they have on the marketplaces to get coverage as well as financially published data one can find out a lot. Concerned about marketing, there is a development hacking class which teaches how to use scraping for the marketing objectives.

Finance intelligence, economic intelligence, etc have more and more financial, political, and economical data accessible online with the newer type of services that collect and add up of that, are increasing.

Let’s go through some points concerned with the market:

• It’s tough to evaluate how huge the data scraping market is as this is with the intersection of many big industries like sales, IT security, finance and marketing intelligence. This method is certainly a small part of all these industries however is expected to increase in the coming years.
• It’s a secured bet to indicate that increasingly SaaS will get pioneering applications for the web data scraping as well as progressively startups will use data scraping services from the safety viewpoint.
• As all the startups are generally entering huge markets using niche products / approaches (web data scraping isn’t a solution of everything, it’s more like a feature) they are expected to be obtained by superior players (within the safety, sales, or marketing tools industries). The technological barriers are also there.

Source URL : http://www.3idatascraping.com/data-scraping-will-definitely-benefit-a-business-startup.php

Web Scraping Services : Making Modern File Formats More Accessible

Data scraping is the process of automatically sorting through information contained on the internet inside html, PDF or other documents and collecting relevant information to into databases and spreadsheets for later retrieval. On most websites, the text is easily and accessibly written in the source code but an increasing number of businesses are using Adobe PDF format (Portable Document Format: A format which can be viewed by the free Adobe Acrobat software on almost any operating system. See below for a link.). The advantage of PDF format is that the document looks exactly the same no matter which computer you view it from making it ideal for business forms, specification sheets, etc.; the disadvantage is that the text is converted into an image from which you often cannot easily copy and paste. PDF Scraping is the process of data scraping information contained in PDF files. To PDF scrape a PDF document, you must employ a more diverse set of tools.

There are two main types of PDF files: those built from a text file and those built from an image (likely scanned in). Adobe's own software is capable of PDF scraping from text-based PDF files but special tools are needed for PDF scraping text from image-based PDF files. The primary tool for PDF scraping is the OCR program. OCR, or Optical Character Recognition, programs scan a document for small pictures that they can separate into letters. These pictures are then compared to actual letters and if matches are found, the letters are copied into a file. OCR programs can perform PDF scraping of image-based PDF files quite accurately but they are not perfect.

Once the OCR program or Adobe program has finished PDF scraping a document, you can search through the data to find the parts you are most interested in. This information can then be stored into your favorite database or spreadsheet program. Some PDF scraping programs can sort the data into databases and/or spreadsheets automatically making your job that much easier.

Quite often you will not find a PDF scraping program that will obtain exactly the data you want without customization. Surprisingly a search on Google only turned up one business, that will create a customized PDF scraping utility for your project. A handful of off the shelf utilities claim to be customizable, but seem to require a bit of programming knowledge and time commitment to use effectively. Obtaining the data yourself with one of these tools may be possible but will likely prove quite tedious and time consuming. It may be advisable to contract a company that specializes in PDF scraping to do it for you quickly and professionally.

Let's explore some real world examples of the uses of PDF scraping technology. A group at Cornell University wanted to improve a database of technical documents in PDF format by taking the old PDF file where the links and references were just images of text and changing the links and references into working clickable links thus making the database easy to navigate and cross-reference. They employed a PDF scraping utility to deconstruct the PDF files and figure out where the links were. They then could create a simple script to re-create the PDF files with working links replacing the old text image.

A computer hardware vendor wanted to display specifications data for his hardware on his website. He hired a company to perform PDF scraping of the hardware documentation on the manufacturers' website and save the PDF scraped data into a database he could use to update his webpage automatically.

PDF Scraping is just collecting information that is available on the public internet. PDF Scraping does not violate copyright laws.

PDF Scraping is a great new technology that can significantly reduce your workload if it involves retrieving information from PDF files. Applications exist that can help you with smaller, easier PDF Scraping projects but companies exist that will create custom applications for larger or more intricate PDF Scraping jobs.

Source URL :  http://yellowpagesdatascraping.blogspot.in/2015/06/web-scraping-services-making-modern.html

Scraping the Bottom of the Barrel - The Perils of Online Article Marketing

Many online article marketers so desperately wish to succeed, they want to dump corporate life and work for themselves out of their home. They decide they are going to create an online money making website. Therefore, they look around to see what everyone else is doing, and watch the methods others use to attract online buyers, and then they mimic their marketing, their strategies, and their business models.

Still, if you are copying what other people (less ethical people) are doing in online article marketing, those which are scraping the bottom of the barrel and using false advertising and misrepresentations, then all you are really doing is perpetuating distrust on the Internet. Therefore, you are hurting everyone, including people like me. You must realize that people like me don't appreciate that.

Let me give you a few examples of some of the things going on out there, thing that are being done by people who are ethically challenged. Far too many people write articles and then on their byline they send the Internet surfer or reader of the article to a website that has a squeeze page. The squeeze page has no real information on it, rather it asks for their name and e-mail address.

If the would-be Internet surfer is unwise enough to type in their name and email address they will be spammed by e-mail, receiving various hard-sell marketing pieces. Then, if the Internet Surfer does decide to put in their e-mail address, the website grants them access and then takes them to the page with information about what they are selling, or their online marketing "make you a millionaire" scheme.

Generally, these are five page sales letters, with tons of testimonials of people you've never heard of, and may not actually exist, and all sorts of unsubstantiated earnings claims of how much money you will make if you give them $39.35 by way of PayPal, for this limited offer "Now!" And they will send you an E-book with a strategic plan of how you can duplicate what they are doing. The reality is whatever they are doing is questionable to begin with.

Source URL  : http://ezinearticles.com/?Scraping-the-Bottom-of-the-Barrel---The-Perils-of-Online-Article-Marketing&id=2710103

Beginner’s guide to Web Scraping in Python (using Beautiful Soup)

Introduction

The need and importance of extracting data from the web is becoming increasingly loud and clear. Every few weeks, I find myself in a situation where we need to extract data from the web. For example, last week we were thinking of creating an index of hotness and sentiment about various data science courses available on the internet. This would not only require finding out new courses, but also scrape the web for their reviews and then summarizing them in a few metrics! This is one of the problems / products, whose efficacy depends more on web scrapping and information extraction (data collection) than the techniques used to summarize the data.

Ways to extract information from web

There are several ways to extract information from the web. Use of APIs being probably the best way to extract data from a website. Almost all large websites like Twitter, Facebook, Google, Twitter, StackOverflow provide APIs to access their data in a more structured manner. If you can get what you need through an API, it is almost always preferred approach over web scrapping. This is because if you are getting access to structured data from the provider, why would you want to create an engine to extract the same information.

Sadly, not all websites provide an API. Some do it because they do not want the readers to extract huge information in structured way, while others don’t provide APIs due to lack of technical knowledge. What do you do in these cases? Well, we need to scrape the website to fetch the information.

There might be a few other ways like RSS feeds, but they are limited in their use and hence I am not including them in the discussion here.

What is Web Scraping?

Web scraping is a computer software technique of extracting information from websites. This technique mostly focuses on the transformation of unstructured data (HTML format) on the web into structured data (database or spreadsheet).

You can perform web scrapping in various ways, including use of Google Docs to almost every programming language. I would resort to Python because of its ease and rich eocsystem. It has a library known as ‘Beautiful Soup’ which assists this task. In this article, I’ll show you the easiest way to learn web scraping using python programming.

For those of you, who need a non-programming way to extract information out of web pages, you can also look at import.io . It provides a GUI driven interface to perform all basic web scraping operations. The hackers can continue to read this article!

Libraries required for web scraping

As we know, python is a open source programming language. You may find many libraries to perform one function. Hence, it is necessary to find the best to use library. I prefer Beautiful Soup (python library), since it is easy and intuitive to work on. Precisely, I’ll use two Python modules for scraping data:

Urllib2: It is a Python module which can be used for fetching URLs. It defines functions and classes to help with URL actions (basic and digest authentication, redirections, cookies, etc). For more detail refer to the documentation page.

Beautiful Soup: It is an incredible tool for pulling out information from a webpage. You can use it to extract tables, lists, paragraph and you can also put filters to extract information from web pages. In this article, we will use latest version Beautiful Soup 4. You can look at the installation instruction in its documentation page.

Beautiful Soup does not fetch the web page for us. That’s why, I use urllib2 in combination with the BeautifulSoup library.

Python has several other options for HTML scraping in addition to Beatiful Soup. Here are some others:

    -mechanize
    -scrapemark
    -scrapy

Basics – Get familiar with HTML (Tags)

While performing web scarping, we deal with html tags. Thus, we must have good understanding of them.                      
 you already know basics of HTML, you can skip this section. Below is the basic syntax of HTML:
  This syntax has various tags as elaborated below:

    <!DOCTYPE html> : HTML documents must start with a type declaration
      HTML document is contained between <html> and </html>
      The visible part of the HTML document is between <body> and </body>
       HTML headings are defined with the <h1> to <h6> tags
       HTML paragraphs are defined with the <

Scrapping a web Page using Beautiful Soup

Here, I am scraping data from a Wikipedia page. Our final goal is to extract list of state, union territory capitals in India. And some basic detail like establishment, former capital and others form this wikipedia page. Let’s learn with doing this project step wise step:

Import necessary libraries:

#import the library used to query a website
import urllib2
#specify the url
wiki = "https://en.wikipedia.org/wiki/List_of_state_and_union_territory_capitals_in_India"
#Query the website and return the html to the variable 'page'
page = urllib2.urlopen(wiki)
#import the Beautiful soup functions to parse the data returned from the website
from bs4 import Beautiful Soup
#Parse the html in the 'page' variable, and store it in Beautiful Soup format
soup = Beautiful Soup(page)

Use function “prettify” to look at nested structure of HTML page

Above, you can see that structure of the HTML tags. This will help you to know about different available tags and how can you play with these to extract information.

Work with HTML tags

    soup.<tag>: Return content between opening and closing tag including tag.
    In[30]:soup.title
    Out[30]:<title>List of state and union territory capitals in India - Wikipedia, the free encyclopedia</title>
    soup.<tag>.string: Return string within given tag
    In [38]:soup.title.string
    Out[38]:u'List of state and union territory capitals in India - Wikipedia, the free encyclopedia'

Find all the links within page’s <a> tags::  We know that, we can tag a link using tag “<a>”. So, we should go with option soup.a and it should return the links available in the web page. Let’s do it.

    In [40]:soup.a
    Out[40]:<a id="top"></a>

Above, you can see that, we have only one output. Now to extract all the links within <a>, we will use

Above, it is showing all links including titles, links and other information.  Now to show only links, we need to iterate over each a tag and then return the link using attribute “href” with get.

Find the right table: As we are seeking a table to extract information about state capitals, we should identify the right table first. Let’s write the command to extract information within all table tags.

all_tables=soup.find_all('table')

Now to identify the right table, we will use attribute “class” of table and use it to filter the right table. In chrome, you can check the class name by right click on the required table of web page –> Inspect element –> Copy the class name OR go through the output of above command find the class name of right table.

right_table=soup.find('table', class_='wikitable sortable plainrowheaders')

\right_table

Extract the information to DataFrame: Here, we need to iterate through each row (tr) and then assign each element of tr (td) to a variable and append it to a list. Let’s first look at the HTML structure of the table (I am not going to extract information for table heading <th>)
Above, you can notice that second element of <tr> is within tag <th> not <td> so we need to take care for this. Now to access value of each element, we will use “find(text=True)” option with each element.  Let’s look at the code

#Generate lists

A=[]
B=[]
C=[]
D=[]
E=[]
F=[]
G=[]
for row in right_table.findAll("tr"):

    cells = row.findAll('td')
    states=row.findAll('th') #To store second column data
    if len(cells)==6: #Only extract table body not heading
        A.append(cells[0].find(text=True))
        B.append(states[0].find(text=True))
        C.append(cells[1].find(text=True))
        D.append(cells[2].find(text=True))
        E.append(cells[3].find(text=True))
        F.append(cells[4].find(text=True))
        G.append(cells[5].find(text=True))

#import pandas to convert list to data frame

import pandas as pd
df=pd.DataFrame(A,columns=['Number'])
df['State/UT']=B
df['Admin_Capital']=C
df['Legislative_Capital']=D
df['Judiciary_Capital']=E
df['Year_Capital']=F
df['Former_Capital']=G
df

Similarly, you can perform various other types of web scraping using “Beautiful Soup“. This will reduce your manual efforts to collect data from web pages. You can also look at the other attributes like .parent, .contents, .descendants and .next_sibling, .prev_sibling and various attributes to navigate using tag name. These will help you to scrap the web pages effectively.-

But, why can’t I just use Regular Expressions?

Now, if you know regular expressions, you might be thinking that you can write code using regular expression which can do the same thing for you. I definitely had this question. In my experience with Beautiful Soup and Regular expressions to do same thing I found out:

Code written in Beautiful Soup is usually more robust than the one written using regular expressions. Codes written with regular expressions need to be altered with any changes in pages. Even Beautiful Soup needs that in some cases, it is just that Beautiful Soup is relatively better.

Regular expressions are much faster than Beautiful Soup, usually by a factor of 100 in giving the same outcome.

So, it boils down to speed vs. robustness of the code and there is no universal winner here. If the information you are looking for can be extracted with simple regex statements, you should go ahead and use them. For almost any complex work, I usually recommend BeautifulSoup more than regex.

End Note

In this article, we looked at web scraping methods using “Beautiful Soup” and “urllib2” in Python. We also looked at the basics of HTML and perform the web scraping step by step while solving a challenge. I’d recommend you to practice this and use it for collecting data from web pages.


 Source : http://www.analyticsvidhya.com/blog/2015/10/beginner-guide-web-scraping-beautiful-soup-python/

Web scraping in under 60 seconds: the magic of import.io

This post was written by Rubén Moya, School of Data fellow in Mexico, and originally posted on Escuela de Datos.
Import.io is a very powerful and easy-to-use tool for data extraction that has the aim of getting data from any website in a structured way.
It is meant for non-programmers that need data (and for programmers who don’t want to overcomplicate their lives).
I almost forgot!! Apart from everything, it is also a free tool (o_O)

The purpose of this post is to teach you how to scrape a website and make a dataset and/or API in under 60 seconds. Are you ready?

It’s very simple. You just have to go to http://magic.import.io; post the URL of the site you want to scrape, and push the “GET DATA” button.
Yes! It is that simple! No plugins, downloads, previous knowledge or registration are necessary. You can do this from any browser; it even
works on tablets and smartphones.

For example: if we want to have a table with the information on all items related to Chewbacca on MercadoLibre (a Latin American version
of eBay), we just need to go to that site and make a search – then copy and paste the link (http://listado.mercadolibre.com.mx/chewbacca)
on Import.io, and push the “GET DATA” button.

You’ll notice that now you have all the information on a table, and all you need to do is remove the columns you don’t need. To do this, just
place the mouse pointer on top of the column you want to delete, and an “X” will appear.

Finally, it’s enough for you to click on “download” to get it in a csv file.
In our example, we have 373 pages with 48 articles each. So this option will be very useful for us.

Good news for those of us who are a bit more technically-oriented! There is a button that says “GET API” and this one is good to, well,
generate an API that will update the data on each request. For this you need to create an account (which is also free of cost).

As you saw, we can scrape any website in under 60 seconds, even if it includes tons of results pages. This truly is magic, no? For more
complex things that require logins, entering subwebs, automatized searches, et cetera, there is downloadable import.io software… But I’ll
explain that in a different post.

Source : http://schoolofdata.org/2014/12/09/web-scraping-in-under-60-seconds-the-magic-of-import-io/

Exploring Web Data Extraction And Its Different Techniques

Web scraping or web data extraction is a distinctive process based on computer software to extract information from different websites. Mostly business organizations are dependent on the web resources for collecting crucial information relating to decision making. With the analysis of such data, they can identify the existing trends of market, details, prices, and product specification. Looking at the time consuming process of manual data extraction, the prominence of data extraction techniques increases.

Different data scraping techniques

Several data extraction techniques are available for the businesses to extract useful information for successful operations. Some of them may include:

    Logical extraction: It comprises logical data extraction of complete source system as well as incremental.
    Physical extraction: This technique involves two different mechanisms for web scrapping that include both online as well as offline.
    HTTP programming: You can also extract data from both dynamic and static websites by implying the technique of socket programming. It allows you to post HTTP requests on the remote web servers.
    Web scraping software: Several software tools are available in the market that serves your individual needs of extracting data with ease. It automatically attempts to recognize the structure of data for a page and extracts the content for further analysis.
    Web scrapping tools: Besides the availability of reliable software, numerous user-friendly web scrapping tools are also helpful in simplifying the entire web scraping process.

Hire a website scrapper

Hiring a suitable website scraper that offers website data extraction services for all your business requirements is an ideal way amongst all other techniques. It provides you filtered and reliable data according to your need for analysis. Some of the major advantages of using website scrapping services may include:

    Automation of data.
    It can retrieve web pages of both static as well as dynamic websites.
    It is also capable of transforming the content into useful information.
    Provides reliable and accurate data.
    It also recognizes several semantic annotations.

Scraping service versus tools

Web scraping services gain more privilege than other tools and software. The basic reason behind this preference is that the service providers are comparatively cheaper than the tools. In fact, they maintain better accuracy and reliability of data.

Summary: It is advisable to look out for suitable web data extraction services instead of any tools or software. This helps in acquiring customized and structured data for your business in legal manner.


 Source : http://www.web-parsing.com/blog/exploring-web-data-extraction-and-its-different-techniques/

Extensive Benefits of Data Mining Services to Marketing – Retail and Outreach Sectors…!!!

There is a vast ocean out there – An ocean of information on internet which is massive, brimming with a lot of data; in fact, it is constantly getting updated, increase the volume with each passing day. In fact, it is believed that around 90% of total information generated in the last two years, is now available on the internet.

Picking right set of information from this heap of data is like searching a needle in the haystack. It is almost next to impossible to search it manually – You need a powerful magnet in form of data mining service provider…!!!

Data mining services work like a magnet – It helps you in finding the right kind of information from huge databases available in the digital world. And with databases getting mammoth every minute, the importance of partnering with a professional and reliable data mining company cannot be overlooked.Though, loaded with a lot of negative connotations; data mining still reigns like a king! In fact, in order to truly appreciate the concept behind data mining, one needs to know it in its entirety.

Every coin has two sides – If there is a brighter side; there tends to be a dark side as well. Though, advantages of web extraction, outweighs disadvantages the fact is it is always the dark underbelly that is highlighted and shown to the world. However, as wise men say, focus on positive sides – Lets see what amazing advantages it can offer to your business and how well you can gain from hiring a professional data mining services.

Upside or Advantage of Data Extraction Services:

While data mining is used primarily in business, it is interesting to know that benefits of data mining goes beyond and across boundaries; it helps various industries as well.

Marketing/Retailing

Data mining can prove to be extremely helpful to the marketers and retailers who are looking out for potential clients as well as aspires to maintain consumer satisfaction. This is one of the methods that allows the businesses to know their potential clients better by acquiring their personal information and preferences.

Not just data extraction helps in determining the trends in goods and services by presenting an overview of online data. With adequate information, you can improve your goods and services, along with changing or choosing the ones which are more in demand. Consequently, success in business has been made quicker and easier these days because of data mining.

Streamline Outreach

Outreach forms an integral part of any business – And to effectively carry out outreach activities; one needs to have a huge cache of database, that can help the marketers to learn how to approach a particular set of customers. Information like that includes relevant e-mail addresses, mailing addresses or social media pages needs to be streamlined any mailers to get the best results.

Data extraction makes this easier; since it gets all the updated information; and in process saves your time and money.

And as it is “the lotus flower grows in mud, but makes our world fragrant” – data mining services is marred by criticism and controversy; however, its extensive advantages outweighs these negativity to a great extent.

Source : http://www.habiledata.com/blog/extensive-benefits-of-data-mining-services-to-marketing-retail-and-outreach-sectors/