Data Mining and Financial Data Analysis

Data Mining and Financial Data Analysis

Introduction:

Most marketers understand the value of collecting financial data, but also realize the challenges of leveraging this knowledge to create intelligent, proactive pathways back to the customer. Data mining - technologies and techniques for recognizing and tracking patterns within data - helps businesses sift through layers of seemingly unrelated data for meaningful relationships, where they can anticipate, rather than simply react to, customer needs as well as financial need. In this accessible introduction, we provides a business and technological overview of data mining and outlines how, along with sound business processes and complementary technologies, data mining can reinforce and redefine for financial analysis.

Objective:

1. The main objective of mining techniques is to discuss how customized data mining tools should be developed for financial data analysis.

2. Usage pattern, in terms of the purpose can be categories as per the need for financial analysis.

3. Develop a tool for financial analysis through data mining techniques.

Data mining:

Data mining is the procedure for extracting or mining knowledge for the large quantity of data or we can say data mining is "knowledge mining for data" or also we can say Knowledge Discovery in Database (KDD). Means data mining is : data collection , database creation, data management, data analysis and understanding.

There are some steps in the process of knowledge discovery in database, such as

1. Data cleaning. (To remove nose and inconsistent data)

2. Data integration. (Where multiple data source may be combined.)

3. Data selection. (Where data relevant to the analysis task are retrieved from the database.)

4. Data transformation. (Where data are transformed or consolidated into forms appropriate for mining by performing summary or aggregation operations, for instance)

5. Data mining. (An essential process where intelligent methods are applied in order to extract data patterns.)

6. Pattern evaluation. (To identify the truly interesting patterns representing knowledge based on some interesting measures.)

7. Knowledge presentation.(Where visualization and knowledge representation techniques are used to present the mined knowledge to the user.)

Data Warehouse:

A data warehouse is a repository of information collected from multiple sources, stored under a unified schema and which usually resides at a single site.

Text:

Most of the banks and financial institutions offer a wide verity of banking services such as checking, savings, business and individual customer transactions, credit and investment services like mutual funds etc. Some also offer insurance services and stock investment services.

There are different types of analysis available, but in this case we want to give one analysis known as "Evolution Analysis".

Data evolution analysis is used for the object whose behavior changes over time. Although this may include characterization, discrimination, association, classification, or clustering of time related data, means we can say this evolution analysis is done through the time series data analysis, sequence or periodicity pattern matching and similarity based data analysis.

Data collect from banking and financial sectors are often relatively complete, reliable and high quality, which gives the facility for analysis and data mining. Here we discuss few cases such as,

Eg, 1. Suppose we have stock market data of the last few years available. And we would like to invest in shares of best companies. A data mining study of stock exchange data may identify stock evolution regularities for overall stocks and for the stocks of particular companies. Such regularities may help predict future trends in stock market prices, contributing our decision making regarding stock investments.

Eg, 2. One may like to view the debt and revenue change by month, by region and by other factors along with minimum, maximum, total, average, and other statistical information. Data ware houses, give the facility for comparative analysis and outlier analysis all are play important roles in financial data analysis and mining.

Eg, 3. Loan payment prediction and customer credit analysis are critical to the business of the bank. There are many factors can strongly influence loan payment performance and customer credit rating. Data mining may help identify important factors and eliminate irrelevant one.

Factors related to the risk of loan payments like term of the loan, debt ratio, payment to income ratio, credit history and many more. The banks than decide whose profile shows relatively low risks according to the critical factor analysis.

We can perform the task faster and create a more sophisticated presentation with financial analysis software. These products condense complex data analyses into easy-to-understand graphic presentations. And there's a bonus: Such software can vault our practice to a more advanced business consulting level and help we attract new clients.

To help us find a program that best fits our needs-and our budget-we examined some of the leading packages that represent, by vendors' estimates, more than 90% of the market. Although all the packages are marketed as financial analysis software, they don't all perform every function needed for full-spectrum analyses. It should allow us to provide a unique service to clients.

The Products:

ACCPAC CFO (Comprehensive Financial Optimizer) is designed for small and medium-size enterprises and can help make business-planning decisions by modeling the impact of various options. This is accomplished by demonstrating the what-if outcomes of small changes. A roll forward feature prepares budgets or forecast reports in minutes. The program also generates a financial scorecard of key financial information and indicators.

Customized Financial Analysis by BizBench provides financial benchmarking to determine how a company compares to others in its industry by using the Risk Management Association (RMA) database. It also highlights key ratios that need improvement and year-to-year trend analysis. A unique function, Back Calculation, calculates the profit targets or the appropriate asset base to support existing sales and profitability. Its DuPont Model Analysis demonstrates how each ratio affects return on equity.

Financial Analysis CS reviews and compares a client's financial position with business peers or industry standards. It also can compare multiple locations of a single business to determine which are most profitable. Users who subscribe to the RMA option can integrate with Financial Analysis CS, which then lets them provide aggregated financial indicators of peers or industry standards, showing clients how their businesses compare.

iLumen regularly collects a client's financial information to provide ongoing analysis. It also provides benchmarking information, comparing the client's financial performance with industry peers. The system is Web-based and can monitor a client's performance on a monthly, quarterly and annual basis. The network can upload a trial balance file directly from any accounting software program and provide charts, graphs and ratios that demonstrate a company's performance for the period. Analysis tools are viewed through customized dashboards.

PlanGuru by New Horizon Technologies can generate client-ready integrated balance sheets, income statements and cash-flow statements. The program includes tools for analyzing data, making projections, forecasting and budgeting. It also supports multiple resulting scenarios. The system can calculate up to 21 financial ratios as well as the breakeven point. PlanGuru uses a spreadsheet-style interface and wizards that guide users through data entry. It can import from Excel, QuickBooks, Peachtree and plain text files. It comes in professional and consultant editions. An add-on, called the Business Analyzer, calculates benchmarks.

ProfitCents by Sageworks is Web-based, so it requires no software or updates. It integrates with QuickBooks, CCH, Caseware, Creative Solutions and Best Software applications. It also provides a wide variety of businesses analyses for nonprofits and sole proprietorships. The company offers free consulting, training and customer support. It's also available in Spanish.

ProfitSystem fx Profit Driver by CCH Tax and Accounting provides a wide range of financial diagnostics and analytics. It provides data in spreadsheet form and can calculate benchmarking against industry standards. The program can track up to 40 periods.

Source : http://ezinearticles.com/?Data-Mining-and-Financial-Data-Analysis&id=2752017

Importance of Data Mining Services in Business

Importance of Data Mining Services in Business

Data mining is used in re-establishment of hidden information of the data of the algorithms. It helps to extract the useful information starting from the data, which can be useful to make practical interpretations for the decision making.
It can be technically defined as automated extraction of hidden information of great databases for the predictive analysis. In other words, it is the retrieval of useful information from large masses of data, which is also presented in an analyzed form for specific decision-making. Although data mining is a relatively new term, the technology is not. It is thus also known as Knowledge discovery in databases since it grip searching for implied information in large databases.
It is primarily used today by companies with a strong customer focus - retail, financial, communication and marketing organizations. It is having lot of importance because of its huge applicability. It is being used increasingly in business applications for understanding and then predicting valuable data, like consumer buying actions and buying tendency, profiles of customers, industry analysis, etc. It is used in several applications like market research, consumer behavior, direct marketing, bioinformatics, genetics, text analysis, e-commerce, customer relationship management and financial services.

However, the use of some advanced technologies makes it a decision making tool as well. It is used in market research, industry research and for competitor analysis. It has applications in major industries like direct marketing, e-commerce, customer relationship management, scientific tests, genetics, financial services and utilities.

Data mining consists of major elements:

    Extract and load operation data onto the data store system.
    Store and manage the data in a multidimensional database system.
    Provide data access to business analysts and information technology professionals.
    Analyze the data by application software.
    Present the data in a useful format, such as a graph or table.

The use of data mining in business makes the data more related in application. There are several kinds of data mining: text mining, web mining, relational databases, graphic data mining, audio mining and video mining, which are all used in business intelligence applications. Data mining software is used to analyze consumer data and trends in banking as well as many other industries.

Outsourcing Web Research offer complete Data Mining Services and Solutions to quickly collective data and information from multiple Internet sources for your Business needs in a cost efficient manner.

Sourec : http://ezinearticles.com/?Importance-of-Data-Mining-Services-in-Business&id=2601221

Data Extraction Services For Better Outputs in Your Business

Data Extraction Services For Better Outputs in Your Business

Data Extraction can be defined as the process of retrieving data from an unstructured source in order to process it further or store it. It is very useful for large organizations who deal with large amount of data on a daily basis that need to be processed into meaningful information and stored for later use. The data extraction is a systematic way to extract and structure data from scattered and semi-structured electronic documents, as found on the web and in various data warehouses.

In today's highly competitive business world, vital business information such as customer statistics, competitor's operational figures and inter-company sales figures play an important role in making strategic decisions. By signing on this service provider, you will be get access to critivcal data from various sources like websites, databases, images and documents.

It can help you take strategic business decisions that can shape your business' goals. Whether you need customer information, nuggets into your competitor's operations and figure out your organization's performance, it is highly critical to have data at your fingertips as and when you want it. Your company may be crippled with tons of data and it may prove a headache to control and convert the data into useful information. Data extraction services enable you get data quickly and in the right format.

Few areas where Data Extraction can help you are:

    Capturing financial data
    Generating better sales leads
    Conducting market research, survey and analysis
    Conducting product research and analysis
    Track, extract and harvest product pricing data
    Searching for specific job postings
    Duplicating an online database
    Acquiring real estate data
    Processing auction information
    Searching online newspapers for latest pricing information
    Extracting and summarize news stories from online news sources

Outsourcing companies provide custom made data extraction services to the client's requirements. The different types of data extraction services;

    Web extraction
    Database extraction

Outsourcing is the beneficial option for large organizations seeking to manage large information. Outsourcing this services helps businesses in managing their data effectively, which in turn enables business to experience an increase in profits. By outsourcing, you can certainly increase your competitive edge and save costs too!

This article is courtesy of Web Scraping Expert - an executive at Outsourcing Web Research offer high quality and time bound comprehensive range of data extraction services at affordable rates. For more info please visit us at: http://www.webscrapingexpert.com/ or directly send your requirements at: info@webscrapingexpert.com

Source:http://ezinearticles.com/?Data-Extraction-Services-For-Better-Outputs-in-Your-Business&id=2760257

Increasing Accessibility by Scraping Information From PDF

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

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

How to scrape search results from search engines like Google, Bing and Yahoo

How to scrape search results from search engines like Google, Bing and Yahoo

Search giants like Google, Yahoo and Bing made their empire on scraping others content. However, they don’t want you to scrape them. How ironic, isn’t it?

Search engine performance is a very important metric all digital marketers want to measure and improve. I’m sure you will be using some great SEO tools to check how your keywords perform. All great SEO tool comes with a search keyword ranking feature. The tools will tell you how your keywords are performing in google, yahoo bing etc.

 How will you get data from search engines If you want to build a keyword ranking app?

 These search engines have API’s but the daily query limit is very low and not useful for the commercial purpose. The only solution is to scrape search results. Search engine giants obviously know this :). Once they know that you are scraping, they will  block your IP, Period!

 How do Search engines detect bots?

 Here are the common methods of detection of bots.

* IP address: Search engines can detect if there are too many requests coming from a single IP. If a high amount of traffic is detected, they will throw a captcha.

 * Search patterns: Search engines match traffic patterns to an existing set of patterns and if there is huge variation, they will classify this as a bot.

 If you don’t have access to sophisticated technology, it is impossible to scrape search engines like google, Bing or Yahoo.

 How to avoid detection

There are some things you can do to  avoid detection.

    Scrape slowly and don’t try to squeeze everything at once.
    Switch user agents between queries
    Scrape randomly and don’t follow the same pattern
    Use intelligent IP rotations
    Clear Cookies after each IP change or disable them completely

Thanks for reading this blog post.

Source: http://blog.datahut.co/how-to-scrape-search-results-from-search-engines-like-google-bing-and-yahoo/

Why Outsourcing Data Mining Services?

Why Outsourcing Data Mining Services?

Are huge volumes of raw data waiting to be converted into information that you can use? Your organization's hunt for valuable information ends with valuable data mining, which can help to bring more accuracy and clarity in decision making process.

Nowadays world is information hungry and with Internet offering flexible communication, there is remarkable flow of data. It is significant to make the data available in a readily workable format where it can be of great help to your business. Then filtered data is of considerable use to the organization and efficient this services to increase profits, smooth work flow and ameliorating overall risks.

Data mining is a process that engages sorting through vast amounts of data and seeking out the pertinent information. Most of the instance data mining is conducted by professional, business organizations and financial analysts, although there are many growing fields that are finding the benefits of using in their business.

Data mining is helpful in every decision to make it quick and feasible. The information obtained by it is used for several applications for decision-making relating to direct marketing, e-commerce, customer relationship management, healthcare, scientific tests, telecommunications, financial services and utilities.

Data mining services include:

•     Congregation data from websites into excel database
•     Searching & collecting contact information from websites
•     Using software to extract data from websites
•     Extracting and summarizing stories from news sources
•     Gathering information about competitors business

In this globalization era, handling your important data is becoming a headache for many business verticals. Then outsourcing is profitable option for your business. Since all projects are customized to suit the exact needs of the customer, huge savings in terms of time, money and infrastructure can be realized.

Advantages of Outsourcing Data Mining Services:

•     Skilled and qualified technical staff who are proficient in English
•     Improved technology scalability
•     Advanced infrastructure resources
•     Quick turnaround time
•     Cost-effective prices
•     Secure Network systems to ensure data safety
•     Increased market coverage

Outsourcing will help you to focus on your core business operations and thus improve overall productivity. So data mining outsourcing is become wise choice for business. Outsourcing of this services helps businesses to manage their data effectively, which in turn enable them to achieve higher profits.

Source: http://ezinearticles.com/?Why-Outsourcing-Data-Mining-Services?&id=3066061

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 Web Data Extraction Services Will Save Your Time and Money by Automatic Data Collection

Data scrape is the process of extracting data from web by using software program from proven website only. Extracted data any one can use for any purposes as per the desires in various industries as the web having every important data of the world. We provide best of the web data extracting software. We have the expertise and one of kind knowledge in web data extraction, image scrapping, screen scrapping, email extract services, data mining, web grabbing.

Who can use Data Scraping Services?

Data scraping and extraction services can be used by any organization, company, or any firm who would like to have a data from particular industry, data of targeted customer, particular company, or anything which is available on net like data of email id, website name, search term or anything which is available on web. Most of time a marketing company like to use data scraping and data extraction services to do marketing for a particular product in certain industry and to reach the targeted customer for example if X company like to contact a restaurant of California city, so our software can extract the data of restaurant of California city and a marketing company can use this data to market their restaurant kind of product. MLM and Network marketing company also use data extraction and data scrapping services to to find a new customer by extracting data of certain prospective customer and can contact customer by telephone, sending a postcard, email marketing, and this way they build their huge network and build large group for their own product and company.

We helped many companies to find particular data as per their need for example.

Web Data Extraction

Web pages are built using text-based mark-up languages (HTML and XHTML), and frequently contain a wealth of useful data in text form. However, most web pages are designed for human end-users and not for ease of automated use. Because of this, tool kits that scrape web content were created. A web scraper is an API to extract data from a web site. We help you to create a kind of API which helps you to scrape data as per your need. We provide quality and affordable web Data Extraction application

Data Collection

Normally, data transfer between programs is accomplished using info structures suited for automated processing by computers, not people. Such interchange formats and protocols are typically rigidly structured, well-documented, easily parsed, and keep ambiguity to a minimum. Very often, these transmissions are not human-readable at all. That's why the key element that distinguishes data scraping from regular parsing is that the output being scraped was intended for display to an end-user.

Email Extractor

A tool which helps you to extract the email ids from any reliable sources automatically that is called a email extractor. It basically services the function of collecting business contacts from various web pages, HTML files, text files or any other format without duplicates email ids.

Screen scrapping

Screen scraping referred to the practice of reading text information from a computer display terminal's screen and collecting visual data from a source, instead of parsing data as in web scraping.

Data Mining Services

Data Mining Services is the process of extracting patterns from information. Datamining is becoming an increasingly important tool to transform the data into information. Any format including MS excels, CSV, HTML and many such formats according to your requirements.

Web spider

A Web spider is a computer program that browses the World Wide Web in a methodical, automated manner or in an orderly fashion. Many sites, in particular search engines, use spidering as a means of providing up-to-date data.

Web Grabber

Web grabber is just a other name of the data scraping or data extraction.

Web Bot

Web Bot is software program that is claimed to be able to predict future events by tracking keywords entered on the Internet. Web bot software is the best program to pull out articles, blog, relevant website content and many such website related data We have worked with many clients for data extracting, data scrapping and data mining they are really happy with our services we provide very quality services and make your work data work very easy and automatic.

Source: http://ezinearticles.com/?How-Web-Data-Extraction-Services-Will-Save-Your-Time-and-Money-by-Automatic-Data-Collection&id=5159023

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/

Run Code Template – New Feature Added to Fminer Web Scraping Tool

Run Code Template – New Feature Added to Fminer Web Scraping Tool

Fminer is one of the powerful web scraping software, I already given brief of all the Fminer features in previous post. In this post I am going to introduce one of the interesting feature of fminer which is Run Code Template that is recently added to Fminer, this feature is similar to “Fminer Run Code” action but it’s different in a way you can use it. The Run Code Action you can use inside the data scraping flow and python code get executed when scraper start running.

While Run Code Templates are the saved python code snippets that you can run on the data tables after scraping completes. Assume if you get white space in scraped data then you can easily trim this left and right spaces by just executing “strip_column” template, see the code of that template below.

'''Strip all data of a column in data table
Remove the blank of data in the head and the tail.
'''

tabName = '[%table1|data table%]'
colName = '[%table1.column1|table column for strip%]'

tab = tables[tabName]
for i, row in enumerate(tab):
    row[colName] = row[colName].strip()   
    tab.edit_row(i, row)

This template comes with Fminer and few other template like “merge_tables_with_same_columns”.  Below are the steps how you can execute template python code on scraped data.

Step 1: Click on second icon from right that says “Run Code” under the Data section

Step 2: One popup will appear, you need to click on “Templates” icon and choose the template you want to execute and then click on Ok.

Step 3: Now the window will appear for configuration that will ask you to choose the table and column under that table on which you want to execute the code. Now click on Ok again.

Step 4: Now you can see the code of that template, now you can click on execute icon and script will start running, based on number of records it will take time to finish execution.

In many web scraping projects I found this template code very handy for cleaning data and making life easy. Templates are stored at following path so you can create your own template with customized code.

C:\Program Files (x86)\FMiner\templates

I have created one template which I use to remove HTML code that comes while scraping badly organized HTML pages. Below is the code of template for stripping html:

'''Strip HTML will remove all html tags of a column in data table.
'''
import re
tabName = '[%table1|data table%]'
colName = '[%table1.column1|table column for substring%]'
colNew = '[%table1.column1|table column to add new data%]'
tab = tables[tabName]
for i, row in enumerate(tab):
    cleanr =re.compile('<.*?>')
    cleantext = re.sub(cleanr,'', row[colName])
    row[colNew] = cleantext 
    tab.edit_row(i, row)

Stay connected as I am going to post more code templates that will make your web scraping life easy and manipulate data on fly.

Source: http://webdata-scraping.com/run-code-template-new-feature-added-fminer-web-scraping-tool/

Calculate your ROI on Web Scraping using our ROI Calculator

Calculate your ROI on Web Scraping using our ROI Calculator

Staying atop the competition is a vital thing for the survival and growth of businesses these days. Ever since big data came into the picture, web scraping has become something businesses from every industry has to invest in. If your company is not in a technically advanced industry, web scraping could even be a nightmare to start with. Wondering if going with in-house web scraping is right for you? In house or outsourcing, in the end it’s all about the returns on investment.

ROI Calculator

Considering the numerous factors that determine how much web scraping can cost you, it’s not easy to calculate the ROI on your in-house web scraping.

In house web scraping is certainly a challenging process. If you plan on going down this way, here is a brief list of prerequisites.

Engineers

Technically skilled labour is an essential requirement for web scraping. Since, web scraping techniques are complicated, it needs good programming skills to write, run and maintain the scraping bots. The cost of labour can be one of the drawbacks with doing in house web scraping.

Hardware Resources

Web scraping is a resource hungry process which requires high end servers and lots of bandwidth. Without the adequate resources, you might end up losing important data. The cost of quality servers could easily make you want to reconsider doing web scraping on your own. Not to mention the doubling up of these resources in order to keep the data intact, espcially if you’re looking at large scale.

Maintainability and ukeep of your tech stack

Once you have your servers and other technical components setup, the real deal only starts. You have to ensure availability of your servers, data backups, restoring previous states, failovers, among many other complications associated with managing servers and fixing them up when something goes wrong. You need to allocate resources (both people and hardware) to take care of the above.

Time

Time is something that we cannot really include in the equation when it comes to calculating the returns. But it is definitely a factor that defines if web scraping in house is worth it. Although web scraping is the fastest way to acquire data, the initial setup and maintenance are time consuming and complicated. This could easily lead to conflicts when you have to distribute your time between web scraping and other business activities that are crucial for your company.

Try the ROI Calculator

We came up with an ROI calculator to easily calculate your returns on investment with our web scraping services. Using this, you could easily compare the cost of in house web scraping with PromptCloud’s dedicated web scraping services. Find out how much you can save by going the PromptCloud way.

Source: https://www.promptcloud.com/blog/calculate-roi-on-web-scraping

Calculate your ROI on Web Scraping using our ROI Calculator

Calculate your ROI on Web Scraping using our ROI Calculator

Staying atop the competition is a vital thing for the survival and growth of businesses these days. Ever since big data came into the picture, web scraping has become something businesses from every industry has to invest in. If your company is not in a technically advanced industry, web scraping could even be a nightmare to start with. Wondering if going with in-house web scraping is right for you? In house or outsourcing, in the end it’s all about the returns on investment.

ROI Calculator

Considering the numerous factors that determine how much web scraping can cost you, it’s not easy to calculate the ROI on your in-house web scraping.

In house web scraping is certainly a challenging process. If you plan on going down this way, here is a brief list of prerequisites.

Engineers

Technically skilled labour is an essential requirement for web scraping. Since, web scraping techniques are complicated, it needs good programming skills to write, run and maintain the scraping bots. The cost of labour can be one of the drawbacks with doing in house web scraping.

Hardware Resources

Web scraping is a resource hungry process which requires high end servers and lots of bandwidth. Without the adequate resources, you might end up losing important data. The cost of quality servers could easily make you want to reconsider doing web scraping on your own. Not to mention the doubling up of these resources in order to keep the data intact, espcially if you’re looking at large scale.

Maintainability and ukeep of your tech stack

Once you have your servers and other technical components setup, the real deal only starts. You have to ensure availability of your servers, data backups, restoring previous states, failovers, among many other complications associated with managing servers and fixing them up when something goes wrong. You need to allocate resources (both people and hardware) to take care of the above.

Time

Time is something that we cannot really include in the equation when it comes to calculating the returns. But it is definitely a factor that defines if web scraping in house is worth it. Although web scraping is the fastest way to acquire data, the initial setup and maintenance are time consuming and complicated. This could easily lead to conflicts when you have to distribute your time between web scraping and other business activities that are crucial for your company.

Try the ROI Calculator

We came up with an ROI calculator to easily calculate your returns on investment with our web scraping services. Using this, you could easily compare the cost of in house web scraping with PromptCloud’s dedicated web scraping services. Find out how much you can save by going the PromptCloud way.

Source: https://www.promptcloud.com/blog/calculate-roi-on-web-scraping

How to use Social Media Scraping to be your Competitors’ Nightmare

How to use Social Media Scraping to be your Competitors’ Nightmare

Big data and competitive intelligence have been in the limelight for quite some time now. The almost magical power of big data to help a company make just the right decisions have been talked about a lot. When it comes to big data, the kind of benefits that a business can get totally depends upon the sources they acquire it from. Social media is one of the best sources from where you can get data that helps your business in a multitude of ways. Now that every business is deep rooted on the internet, social media data becomes all the more relevant and crucial. Here is how you can use data scraped from social media sites to get an edge in the competition.

Keeping watch on your competitors

Social media is the best place to watch your competitors’ activity and take counter initiatives to keep up or take over them. If you want to know what your competitors are up to, a social media scraping setup for scraping the posts that mention your competitors’ brand/product names can do the trick. This can also be used to learn a thing or two from their activities on social media so that you can take respective measures to stay ahead of them. For example, you could know if your competitor is running a special promotional offer at the moment and come up with something better than theirs to keep up. This can do wonders if you are in a highly competitive industry like Ecommerce where the competition is intense. If you are not using some help from web scraping technology to keep a close watch on your competitors, you could easily get left over in this fast-paced business scene.

Solving customer issues at the earliest

Customers are vocal about their experience with different products and services on social media sites these days. If you have a customer whose issue was left unsolved, there is a good chance that he/she will take it to the social media to vent the frustration. Watching out for such instances and giving them prompt support should be something you should do if you want to retain these customers and stop them from ruining your brand’s image. By scraping social media sites for posts that mention your product/service, you can easily find out if there are such grievances from customers. This can make sure to an extent that you don’t let unhappy customers stay that way, which eventually hurts your business in the long run. Customers can make or break your company, so using social media scraping to serve the customers better can help you succeed eventually.

Sentiment analysis

Social media data can play a good job at helping you understand user sentiments. With the help of social media scraping, a business can get the big picture about general perception of their brand by their users. This can go a long way since this level of feedback can help you fix unnoticed issues with your company and service quickly. By rectifying them, you can make your brand more appealing to the customers. Sentiment analysis will provide you with the opportunity to transform your business into how customers want it to be. Social media scraping is the one and only way to have access to this user sentiment data which can help you optimize your business for the customers.

Web crawling for social media data

When social media data possess so much value to businesses, it makes sense to look for efficient ways to gather and use this data. Manually scrolling through millions of tweets doesn’t make sense, this is why you should use social media scraping to aggregate the relevant data for your business. Besides, web scraping technologies make it possible to handle huge amounts of data with ease. Since the size of data is huge when it comes to business related requirements, web scraping is the only scalable solution worth considering. To make things even simpler, there are reliable web scraping solutions that offer social media scraping services for brand monitoring.

Bottom line

Since social media has become an integral part of online businesses, the data available on these sites possess immense value to companies in every industry. Social media scraping can be used for brand monitoring and gaining competitive intelligence that can be used to optimize your business model for maximum effectiveness. This will in turn make your company stand out from the competition and the added advantage of insights gained from social media data will help you to take over your competitors.

Source: https://www.promptcloud.com/blog/social-media-scraping-for-competitive-intelligence

How Web Data Extraction Services Will Save Your Time and Money by Automatic Data Collection

How Web Data Extraction Services Will Save Your Time and Money by Automatic Data Collection

Data scrape is the process of extracting data from web by using software program from proven website only. Extracted data any one can use for any purposes as per the desires in various industries as the web having every important data of the world. We provide best of the web data extracting software. We have the expertise and one of kind knowledge in web data extraction, image scrapping, screen scrapping, email extract services, data mining, web grabbing.

Who can use Data Scraping Services?

Data scraping and extraction services can be used by any organization, company, or any firm who would like to have a data from particular industry, data of targeted customer, particular company, or anything which is available on net like data of email id, website name, search term or anything which is available on web. Most of time a marketing company like to use data scraping and data extraction services to do marketing for a particular product in certain industry and to reach the targeted customer for example if X company like to contact a restaurant of California city, so our software can extract the data of restaurant of California city and a marketing company can use this data to market their restaurant kind of product. MLM and Network marketing company also use data extraction and data scrapping services to to find a new customer by extracting data of certain prospective customer and can contact customer by telephone, sending a postcard, email marketing, and this way they build their huge network and build large group for their own product and company.

We helped many companies to find particular data as per their need for example.

Web Data Extraction

Web pages are built using text-based mark-up languages (HTML and XHTML), and frequently contain a wealth of useful data in text form. However, most web pages are designed for human end-users and not for ease of automated use. Because of this, tool kits that scrape web content were created. A web scraper is an API to extract data from a web site. We help you to create a kind of API which helps you to scrape data as per your need. We provide quality and affordable web Data Extraction application

Data Collection

Normally, data transfer between programs is accomplished using info structures suited for automated processing by computers, not people. Such interchange formats and protocols are typically rigidly structured, well-documented, easily parsed, and keep ambiguity to a minimum. Very often, these transmissions are not human-readable at all. That's why the key element that distinguishes data scraping from regular parsing is that the output being scraped was intended for display to an end-user.

Email Extractor

A tool which helps you to extract the email ids from any reliable sources automatically that is called a email extractor. It basically services the function of collecting business contacts from various web pages, HTML files, text files or any other format without duplicates email ids.

Screen scrapping

Screen scraping referred to the practice of reading text information from a computer display terminal's screen and collecting visual data from a source, instead of parsing data as in web scraping.

Data Mining Services

Data Mining Services is the process of extracting patterns from information. Datamining is becoming an increasingly important tool to transform the data into information. Any format including MS excels, CSV, HTML and many such formats according to your requirements.

Web spider

A Web spider is a computer program that browses the World Wide Web in a methodical, automated manner or in an orderly fashion. Many sites, in particular search engines, use spidering as a means of providing up-to-date data.

Web Grabber

Web grabber is just a other name of the data scraping or data extraction.

Web Bot

Web Bot is software program that is claimed to be able to predict future events by tracking keywords entered on the Internet. Web bot software is the best program to pull out articles, blog, relevant website content and many such website related data We have worked with many clients for data extracting, data scrapping and data mining they are really happy with our services we provide very quality services and make your work data work very easy and automatic.

Source: http://ezinearticles.com/?How-Web-Data-Extraction-Services-Will-Save-Your-Time-and-Money-by-Automatic-Data-Collection&id=5159023

How to Scrape a Website into Excel without programming

How to Scrape a Website into Excel without programming

This web scraping tutorial will teach you visually step by step how to scrape or extract or pull data from websites using import.io(Free Tool) without programming skills into Excel.

Personally, I use web scraping for analysing my competitors’ best-performing blog posts or content such as what blog posts or content received most comments or social media shares.

In this tutorial,We will scrape the following data from a blog:

    All blog posts URLs.
    Authors names for each post.
    Blog posts titles.
    The number of social media shares each post received.

Then we will use the extracted data to determine what are the popular blog posts and their authors,which posts received much engagement from users through social media shares and on page comments.

Let’s get started.

Step 1:Install import.io app

The first step is to install import.io app.A free web scraping tool and one of the best web scraping software.It is available for Windows,Mac and Linux platforms.Import.io offers advanced data extraction features without coding by allowing you to create custom APIs or crawl entire websites.

After installation, you will need to sign up for an account.It is completely free so don’t worry.I will not cover the installation process.Once everything is set correctly you will see something similar to the window below after your first login.

Step 2:Choose how to scrape data using import.io extractor

With import.io you can do data extraction by creating custom APIs or crawling the entire websites.It comes equipped with different tools for data extraction such as magic,extractor,crawler and connector.

In this tutorial,I will use a tool called “extractor” to create a custom API for our data extraction process.

To get started click the “new” red button on the right top of the page and then click “Start Extractor” button on the pop-up window.

After clicking  “Start Extractor” the Import.io app internal browser window will open as shown below.

Step 3:Data scraping process

Now after the import.io browser is open navigate to the blog URL you want to scrape data from. Then once you already navigated to the target blog URL turn on extraction.In this tutorial,I will use this blog URL bongo5.com  for data extraction.

You can see from the window below I already navigated to www.bongo5.com but extraction switch is still off.

Turn extraction switch “ON” as shown in the window below and move to the next step.

Step 4:Training the “columns” or specifying the data we want to scrape

In this step,I will specify exactly what kind of data I want to scrape from the blog.On import.io app specifying the data you want to scrape is referred to as “training the columns”.Columns represent the data set I want to scrape(post titles,authors’ names and posts URLs).

In order to understand this step, you need to know the difference between a blog page and a blog post.A page might have a single post or multiple posts depending on the blog configuration.

A blog might have several blog posts,even hundreds or thousands of posts.But I will take only one session to train the “extractor” about the data I want to extract.I will do so by using an import.io visual highlighter.Once the data extraction is turned on the-the highlighter will appear by default.

I will do the training session for a single post in a single blog page with multiple posts then the extractor will extract data automatically for the remaining posts on the “same” blog page.
Step 4a:Creating “post_title” column

I will start by renaming “my_column” into the name of the data I want to scrape.Our goal in this tutorial is to scrape the blog posts titles,posts URLs,authors names and get social statistics later so I will create columns for posts titles,posts URLs,authors names.Later on, I will teach you how to get social statistics for the post URLs.

After editing “my_column” into “post_title” then point the mouse cursor over to any of the Posts title on the same blog page and the visual highlighter will automatically appear.Using the highlighter I can select the data I want to extract.

You can see below I selected one of the blog post titles on the page.The rectangular box with orange border is the visual highlighter.

The app will ask you how is the data arranged on the page.Since I have more than one post in a single page then you have rows of repeating data.This blog is having 25 posts per page.So you will select “many rows”.Sometimes you might have a single post on a page for that case you need to select “Just one row”.

Source: http://nocodewebscraping.com/web-scraping-for-dummies-tutorial-with-import-io-without-coding/

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

Tips for scraping business directories

Tips for scraping business directories

Are you looking to scrape business directories to generate leads?

Here are a few tips for scraping business directories.

Web scraping is not rocket science. But there are good and bad and worst ways of doing it.

Generating sales qualified leads is always a headache. The old school ways are to buy a list from sites like Data.com. But they are quite expensive.

Scraping business directories can help generate sales qualified leads. The following tips can help you scrape data from business directories efficiently.

1) Choose a good framework to write the web scrapers. This can help save a lot of time and trouble. Python Scrapy is our favourite, but there are other non-pythonic frameworks too.

2) The business directories might be having anti-scraping mechanisms. You have to use IP rotating services to do the scrape. Using IP rotating services, crawl with multiple changing IP addresses which can cover your tracks.

3) Some sites really don’t want you to scrape and they will block the bot. In these cases, you may need to disguise your web scraper as a human being. Browser automation tools like selenium can help you do this.

4) Web sites will update their data quite often. The scraper bot should be able to update the data according to the changes. This is a hard task and you need professional services to do that.

One of the easiest ways to generate leads is to scrape from business directories and use enrich them. We made Leadintel for lead research and enrichment.

Source: http://blog.datahut.co/tips-for-scraping-business-directories/

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

ECJ clarifies Database Directive scope in screen scraping case

EC on the legal protection of databases (Database Directive) in a case concerning the extraction of data from a third party’s website by means of automated systems or software for commercial purposes (so called 'screen scraping').

Flight data extracted

The case, Ryanair Ltd vs. PR Aviation BV, C-30/14, is of interest to a range of companies such as price comparison websites. It stemmed from  Dutch company PR Aviation operation of a website where consumers can search through flight data of low-cost airlines  (including Ryanair), compare prices and, on payment of a commission, book a flight. The relevant flight data is extracted from third-parties’ websites by means of ‘screen scraping’ practices.

Ryanair claimed that PR Aviation’s activity:

• amounted to infringement of copyright (relating to the structure and architecture of the database) and of the so-called sui generis database right (i.e. the right granted to the ‘maker’ of the database where certain investments have been made to obtain, verify, or present the contents of a database) under the Netherlands law implementing the Database Directive;

• constituted breach of contract. In this respect, Ryanair claimed that a contract existed with PR Aviation for the use of its website. Access to the latter requires acceptance, by clicking a box, of the airline’s general terms and conditions which, amongst others, prohibit unauthorized ‘screen scraping’ practices for commercial purposes.

Ryanair asked Dutch courts to prohibit the infringement and order damages. In recent years the company has been engaged in several legal cases against web scrapers across Europe.

The Local Court, Utrecht, and the Court of Appeals of Amsterdam dismissed Ryanair’s claims on different grounds. The Court of Appeals, in particular, cited PR Aviation’s screen scraping of Ryanair’s website as amounting to a “normal use” of said website within the meaning of the lawful user exceptions under Sections 6 and 8 of the Database Directive, which cannot be derogated by contract (Section 15).

Ryanair appealed

Ryanair appealed the decision before the Netherlands Supreme Court (Hoge Raad der Nederlanden), which decided to refer the following question to the ECJ for a preliminary ruling: “Does the application of [Directive 96/9] also extend to online databases which are not protected by copyright on the basis of Chapter II of said directive or by a sui generis right on the basis of Chapter III, in the sense that the freedom to use such databases through the (whether or not analogous) application of Article[s] 6(1) and 8, in conjunction with Article 15 [of Directive 96/9] may not be limited contractually?.”

The ECJ’s ruling

The ECJ (without the need of the opinion of the advocate general) ruled that the Database Directive is not applicable to databases which are not protected either by copyright or by the sui generis database right. Therefore, exceptions to restricted acts set forth by Sections 6 and 8 of the Directive do not prevent the database owner from establishing contractual limitations on its use by third parties. In other words, restrictions to the freedom to contract set forth by the Database Directive do not apply in cases of unprotected databases. Whether Ryanair’s website may be entitled to copyright or sui generis database right protection needs to be determined by the competent national court.

The ECJ’s decision is not particularly striking from a legal standpoint. Yet, it could have a significant impact on the business model of price comparison websites, aggregators, and similar businesses. Owners of databases that could not rely on intellectual property protection may contractually prevent extraction and use (“scraping”) of content from their online databases. Thus, unprotected databases could receive greater protection than the one granted by IP law.

Antitrust implications

However, the lawfulness of contractual restrictions prohibiting access and reuse of data through screen scraping practices should be assessed under an antitrust perspective. In this respect, in 2013 the Court of Milan ruled that Ryanair’s refusal to grant access to its database to the online travel agency Viaggiare S.r.l. amounted to an abuse of dominant position in the downstream market of information and intermediation on flights (decision of June 4, 2013 Viaggiare S.r.l. vs Ryanair Ltd). Indeed, a balance should be struck between the need to compensate the efforts and investments made by the creator of the database with the interest of third parties to be granted with access to information (especially in those cases where the latter are not entitled to copyright protection).

Additionally, web scraping triggers other issues which have not been considered by the ECJ’s ruling. These include, but are not limited to trademark law (i.e., whether the use of a company’s names/logos by the web scraper without consent may amount to trademark infringement), data protection (e.g., in case the scraping involves personal data), or unfair competition.


Source URL :http://yellowpagesdatascraping.blogspot.in/2015/07/ecj-clarifies-database-directive-scope.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/

Web Scraping – Ethical Data Collection Activity or an Illegal Practice?

Abiding by the definition, web scrapping is a method to extract data from website. There can be different reasons to perform this task, such as for reporting, market research, to determine share indexes, know website updates, product rate updates, to monitor data, and so on. Besides these, data theft is another of the prominent motives behind web data extraction, which ultimately holds the use of a web scraper as unethical and at times, illegal.

Technical definition

In technical terms, data scraping is a method of collecting data from a website through specific software. These software programs or web scrapers give the website owners the impression of human web surfing and extract a big volume of data, which is usually difficult for any user visitor to access manually. The apps simulate human exploration of online data by embedding web browsers, or implementing HTTP to fulfill the cause of data extractors.

Relation with data mining

Usually, data mining refers to analyzing data from varied perspectives and transforming it to meaningful information that could help in boosting sales or mitigating financial risks in a business. As for web scraping, it involves extraction of analytical data from the web. At present, web scrapping comprises major source of data extraction carried out by data miners. This is because almost everything is now available online and for any data miner, this resource is no less than a gold mine.

The web scraping process

In this data scraping method, the experts look out for tricks to format the URLs into pages that include the usable information. The web scrapers then parse the DOM tree to extract data from the website. In simple language, the web scrapers process the semi-structured or unstructured data pages of the desired website and then convert the resulting data into a well structured form. The users can harvest or modify the structured data in a better manner.

Web scraping – legal or unethical?

It solely relies on your intentions, whether you are doing this activity in the interest of the masses or just wish to satisfy your personal interests. If it is for a goodwill, such as to research on share index to predict the market situation in the coming days, it is fine. Another positive example could be to identify the trend of market and suggest a client on viable business boosting methods accordingly.

However, if you are doing web scraping for personal gratification then it may well be termed as intrusion into one’s personal data. For example, if you are hacking into the database of a university to steal the academic articles and using them in your own project. Any such instance is definitely an act of stealth and may accompany relevant punishment. Concisely, to get hold of someone’s creative work for individual gains is unethical. Such people also deploy several bots to for data scraping or spinning, which in turn choke the search engine results and hardly useful to the internet.

Considerations that deem web scraping illegal

Generally, web scraping is illegal in two instances:

1. When you violate the terms and conditions of the service of the concerned website:

Most of the data-oriented websites disallow data scraping. Hence, if you are trying to extract data from that website, the owner has all the rights to sue you on the offense of breach of contract.

2. When you publish scraped content:

This is yet another condition that may delve you into violating the right of the copyright holders. If you are only scraping the content for fair use, it may be permissible. However, companies often hold all the publishing rights and may file suit against you if you publish their data without their permission.

Remedy to illegal web scraping

Despite running the apprehensions of getting identified, unethical web scrapers deter to steal data from websites. Hence, the web owners themselves need to be alert enough not to fall prey to such fraudulent activities. Indeed, it is your data and you won’t like it to get compromised at any cost. Just like there are many web scraping tools available online, you can also opt for applications that offer protection against web data extraction as a fruitful remedy. These software safeguard your website content from hacking attacks such as bots, denial of service, brute force, session opening and transaction anomalies, and more.

Summary: Technology has two facets – good and bad. It depends on us which one to adopt; the same holds in the case of web scraping as well. We should make sure to use this innovation for the benefit of society and not to steal away some one’s creativity, which is indeed unethical and at times, illegal

Source : http://www.web-parsing.com/blog/ethical-data-collection-activity-or-an-illegal-practice