Doctor Data Merger
by muhammetakkurtt
Merge doctor profiles with patient reviews automatically. Get a complete, analysis-ready dataset for healthcare research, market analysis, or app development.
Opens on Apify.com
About Doctor Data Merger
Ever tried to get a complete picture of a doctor's practice? You end with their credentials in one spreadsheet and patient reviews scattered across a dozen sites. It's a mess. The Doctor Data Merger actor fixes that. I use it to automatically pull structured doctor profiles—think specialties, education, locations—and merge them with real patient feedback from review platforms. It saves me hours of manual copy-pasting and lets me focus on the actual analysis. It's perfect for a few key jobs. Healthcare analysts can build richer datasets for market research. Researchers can correlate clinical backgrounds with patient satisfaction trends. Even developers building healthcare apps can populate their directories with comprehensive, up-to-date info. You get a clean, unified dataset delivered in JSON or CSV, ready for your database or next visualization project. It runs on Apify, so you can schedule it or integrate it into a larger workflow without managing servers. If you need to understand the full story behind a medical practice, this is how you get the data without the headache.
What does this actor do?
Doctor Data Merger is a web scraping and automation tool available on the Apify platform. It's designed to help you extract data and automate tasks efficiently in the cloud.
Key Features
- Cloud-based execution - no local setup required
- Scalable infrastructure for large-scale operations
- API access for integration with your applications
- Built-in proxy rotation and anti-blocking measures
- Scheduled runs and webhooks for automation
How to Use
- Click "Try This Actor" to open it on Apify
- Create a free Apify account if you don't have one
- Configure the input parameters as needed
- Run the actor and download your results
Documentation
Doctor Data Merger
Overview
This actor merges doctor profile data with corresponding review data from specific Apify scrapers. It takes outputs from two separate dataset runs—one containing doctor information and one containing reviews—and combines them into a single, comprehensive dataset.
Key Features
- Data Integration: Merges doctor profiles from scrapers like Doktortakvimi Scraper, ZnanyLekarz Scraper, Jameda Scraper, and others with their matching reviews from the corresponding review scrapers.
- Filtered Output: Only outputs merged records for doctors who have at least one review.
- Data Cleaning: Automatically replaces line breaks in review text with a single space.
Input/Output
Input Parameters (required):
* doctorInfoDatasetId: The dataset ID containing the doctor profile information.
* doctorReviewsDatasetId: The dataset ID containing the doctor reviews.
Output Dataset:
The actor creates a new dataset where each item is a merged doctor+review record containing these fields:
* doctor_id, name, city, region, specialization
* review_count, overall_rating, newest_review_date
* telemedicine, url, fetch_time
* review_rating, review_text, review_date
How to Use
- First, run the required scraper pair (e.g.,
Doktortakvimi ScraperandDoktortakvimi Reviews Scraper) to populate the source datasets. - Run the Doctor Data Merger actor.
- In the actor input, provide the two dataset IDs from the previous scraper runs:
doctorInfoDatasetIddoctorReviewsDatasetId
- After the run completes, the merged data will be available in the actor's default output dataset.
Categories
Common Use Cases
Market Research
Gather competitive intelligence and market data
Lead Generation
Extract contact information for sales outreach
Price Monitoring
Track competitor pricing and product changes
Content Aggregation
Collect and organize content from multiple sources
Ready to Get Started?
Try Doctor Data Merger now on Apify. Free tier available with no credit card required.
Start Free TrialActor Information
- Developer
- muhammetakkurtt
- Pricing
- Paid
- Total Runs
- 422
- Active Users
- 9
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