Google Maps Data Extraction -- 2
Budget: ₹600 – ₹800 INR
For an upcoming market-research project, from a google map saved link a json file and a csv file has been extracted via google takeout and will be shared to you and you have to extract phone number from all those businesses.
• Business name
• Full street address (including city, state and ZIP)
• Primary phone number
The scrape must span all states and territories so the end result reflects a true national snapshot. An Excel or CSV file is fine for delivery; please keep one row per location and label columns clearly.
If you intend to automate with Python, Selenium, Scrapy, the Google Maps API or a similar approach, note that accuracy and duplicate handling matter more to me than the tool you choose. Captcha-handling and rate-limiting should be built in so the run completes cleanly without blocks.
Acceptance criteria
1. At least 95 % of returned rows contain the four core fields above.
2. No obvious duplicates (same name, phone and address).
3. File opens error-free in Excel 2016+.
4. A brief “how it was done” note or reusable script so I can refresh the data later if needed.
Reviews/ratings are not essential for this phase, but if your method captures them effortlessly feel free to include them in extra columns.
• Business name
• Full street address (including city, state and ZIP)
• Primary phone number
The scrape must span all states and territories so the end result reflects a true national snapshot. An Excel or CSV file is fine for delivery; please keep one row per location and label columns clearly.
If you intend to automate with Python, Selenium, Scrapy, the Google Maps API or a similar approach, note that accuracy and duplicate handling matter more to me than the tool you choose. Captcha-handling and rate-limiting should be built in so the run completes cleanly without blocks.
Acceptance criteria
1. At least 95 % of returned rows contain the four core fields above.
2. No obvious duplicates (same name, phone and address).
3. File opens error-free in Excel 2016+.
4. A brief “how it was done” note or reusable script so I can refresh the data later if needed.
Reviews/ratings are not essential for this phase, but if your method captures them effortlessly feel free to include them in extra columns.
Related categories:
Python
Web Scraping
Data Mining
Geospatial
Google Maps API
Scrapy
Data Extraction
Selenium