使用python将内容写入Excel

Question

I have extracted the data from the page,using selenium python http://www.cmdgroup.com/construction-projects/project/1001622072

Here is the Extracted Data looks like,

Location:
Larkspur, CA
Status:
Postbids Unavailable, BIDS: 05/10/2012
Value:
$ 75,000.00
Documents:
Available with subscription
Categories
Offices
Subbid/Pkg:
GCs Request Subbids On Select Trades: Gutter, Deck Waterproofing & Window Installation
Scope:
Office Scope of work includes: Removal of existing Dex-O-Tex Weatherwear waterproofing system, sheet metal flashing at interior and exterior perimeter of deck, along with wood siding and trim in areas affected by work; Removal and re-installation of exist
Notes:
1. NO CALLS To Owner/Architect. Please Direct Project Inquiries To Bidding GCs Only. 2. SD Deacon Requests Project Inquiries & Bids To Malcolm McFarland At (916)969-0900, Fax (916)735-0800 Or malcolm.mcfarland@deacon.com 3. Please Note There Will Be A Pre
Details:
[Division 3]: Concrete Restoration & Cleaning. [Division 6]: Rough Carpentry, Finish Carpentry. [Division 7]: Waterproofing. [Division 8]: Metal Windows. [Division 9]: Painting. [Division 15]: Plumbing Piping.
Contract Conditions:
Invited Bidders Only

I want this data to write into a Excel File,using python

Headers

Location,Status,BIDS,Value,Categories,Subbid/Pkg,Scope,Notes,Details,Contract Conditions

"Larkspur, CA","Postbids Unavailable",05/10/12,"$ 75,000.00",Offices,"GCs Request Subbids On Select Trades:
 Gutter, Deck Waterproofing & Window Installation","Office Scope of work includes: Removal of existing Dex-O-Tex Weatherwear waterproofing system, 
sheet metal flashing at interior and exterior perimeter of deck, along with wood siding 
And trim in areas affected by work; Removal and re-installation of exist","1. NO CALLS To Owner/Architect. Please Direct Project Inquiries To Bidding GCs Only. 2. SD Deacon Requests Project Inquiries & Bids To Malcolm McFarland At (916)969-0900, Fax (916)735-0800 Or malcolm.mcfarland@deacon.com 3. Please Note There Will Be A Pre","[Division 3]: Concrete Restoration & Cleaning. [Division 6]: Rough Carpentry, Finish Carpentry. [Division 7]: Waterproofing. [Division 8]: Metal Windows. [Division 9]: Painting. [Division 15]: Plumbing Piping.","Invited Bidders Only"

Thanks in advance.

Answer 1

If you can convert your data type to anything that looks remotely like a 2D array or a list of lists, you can create a pandas dataframe out of it and use the to_excel() method. To help you further though, we need to know more about the structure of your data, not just how it looks when it's formatted and printed.