Web Scraping a Business Directory - repost

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Bids
19
Avg Bid (CAD)
$138
Project Budget (CAD)
$30 - $250

Project Description:
I've tried scraping the following website but can't parse the data for some reason http://www.manta.com/
I want the following information on Real Estate companies in Calgary, Alberta, Canada (here's an example http://www.manta.com/ic/mx148ht/ca/mrlc-corp):

Company Name
Address
Website
Phone Number
Company Description
SIC Code
NAICS Code
Contact Name
Contact Position
Location Type
Revenue
Employees
Years in Business

This information can be selected using the following code:

item['company'] = hxs.select('//h1[@class="company-name"]/text()').extract()
item['address'] = hxs.select('//div[@itemprop="streetAddress"]/text()').extract()
item['website'] = hxs.select('//dl[@class="website_info"]/dd/span/text()').extract()
item['phone'] = hxs.select('//dd[@class="tel"]/text()').extract()
item['description'] = hxs.select('//p[@itemprop="description"]/text()').extract()
item['contact_name'] = hxs.select('//span[@itemprop="name"]/text()').extract()
item['contact_position'] = hxs.select('//em[@itemprop="jobTitle"]/text()').extract()
item['location_type'] = hxs.select('//table[@class="table-data"]/tr[1]/td/text()').extract()
item['SIC'] = hxs.select('//table[@class="table-data"]/tr[4]/td/text()').extract()
item['NAICS'] = hxs.select('//table[@class="table-data"]/tr[5]/td/text()').extract()
item['revenue'] = hxs.select('//table[@class="table-data"]/tr[2]/td/text()').extract()
item['employees'] = hxs.select('//table[@class="table-data"]/tr[3]/td/text()').extract()
item['years_business'] = hxs.select('//table[@class="table-data"]/tr[8]/td/text()').extract()

This MUST be done using Scrapy, the web crawling framework written in Python.

Your deliverable is an excel spreadsheet with the above information on each company. There are 1,355 Real Estate companies in Calgary, Canada, so I'm expecting that many rows.

For proof that you scraped the appropriate information I require a screenshot of the excel spreadsheet showing the last 20 rows. If the information on those last 20 companies matches what is found on Manta I will pay you the agreed price in exchange for the excel file.
I may have additional work for you if you complete this task successfully.

Skills required:
Data Mining, Python, Web Scraping
About the employer:
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