In Progress

Scrarp results in several business categories from 2 Business directories .Need to get uinque results with no double entries,a and export in results bt area too.

Python web scrarping. Need to collect serveral results for 5 business categories or more from 2 separate Business Directories ( urls) , and set up python scraper for 5-6 more business categories in both directory sites. Need to collect business name, Address, telephone , email city, prefecture.

The results need to be in specific database format for all results. When we collect all data in main database then need to split the results in separate database for each separate area.

So need to know how to get filtering database results by area or business activity and then to create these new databases separate one for each area

Need to get unique results and to delete double entries from databases.

Need instructions how to set up the scraper for various url for these 2 directories sites ( 2 urls).

Although instructions how could we get filtering results and create new separate data by area and business activity.

Intructions how to get unique results.

Python Scraper need to be set up to our pc remotly.

Skills: Data Mining, Python, Web Scraping

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About the Employer:
( 259 reviews ) Chania Crete, Greece

Project ID: #19936119

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BoyVit85

[login to view URL] Credit is my motto. I am expert web scraping. I can do your job with BS4 ,Perl script,Scrapy Seleinum framework of python. And You can know my skill as u see my profile. I can do any project in your demand More

$55 USD in 1 day
(4 Reviews)
3.2

12 freelancers are bidding on average $50 for this job

yongjin818

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(66 Reviews)
6.0
susanna2018

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(31 Reviews)
5.3
amalphateam

Hello, sir. Scrapping expert here. Thanks for your job posting! I read your job description carefully and I have confidence to do it. I am a C, C++, C#, QT, Python, JAVA Developer with +6 years experience and your proj More

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4.0
developersperhr

will collect data from yelp including phone numbers and emails that I will look for on each companies website (not that not all companies have their emails listed). Data contains of 56 columns : Name Street Address More

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(1 Review)
2.1
josemavare338

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0.0