Email Scraping & Excel Compilation
Budget: $10 – $30 USD
I need a clean, reliable list of email addresses pulled from three sources—Facebook, Twitter, and the public-facing pages of selected company websites. Once gathered, every address should be entered into an Excel file laid out in multiple columns so I can immediately sort and filter by details like platform, page URL, company name (when obvious), and, of course, the email itself.
I haven’t locked in a particular scraping method, so whether you rely on Python, Selenium, Beautiful Soup, custom APIs, or a well-honed manual workflow is up to you—as long as the data is accurate and the final workbook opens without errors.
Quality matters more than volume; duplicates, malformed addresses, or non-existent inboxes won’t be acceptable. If a page or site blocks automated access, please switch to a compliant workaround rather than forcing the issue.
Deliverables
• One Excel spreadsheet (.xlsx) with separate, clearly labeled columns for: Email Address | Source URL | Platform | Additional Notes
• A brief log or README describing the tools or scripts used, key search parameters, and any limitations encountered.
The project is complete once the spreadsheet is delivered, passes a quick spot-check for validity, and I understand how you compiled it so I can replicate or extend the list later.
I haven’t locked in a particular scraping method, so whether you rely on Python, Selenium, Beautiful Soup, custom APIs, or a well-honed manual workflow is up to you—as long as the data is accurate and the final workbook opens without errors.
Quality matters more than volume; duplicates, malformed addresses, or non-existent inboxes won’t be acceptable. If a page or site blocks automated access, please switch to a compliant workaround rather than forcing the issue.
Deliverables
• One Excel spreadsheet (.xlsx) with separate, clearly labeled columns for: Email Address | Source URL | Platform | Additional Notes
• A brief log or README describing the tools or scripts used, key search parameters, and any limitations encountered.
The project is complete once the spreadsheet is delivered, passes a quick spot-check for validity, and I understand how you compiled it so I can replicate or extend the list later.
Related categories:
Python
Data Entry
Excel
Web Scraping
Data Mining
Data Scraping
Selenium
Data Management