The main subject of this repository is web scraping. In a nutshell, four web scrapers were developed with Python as use cases to portray different web data extraction scenarios:

1. HTML tag-based extraction
2. JSON var-based extraction
3. JSON API-response-based extraction

To extract the list of world heritage sites designated by UNESCO.

py script: web_scraping_unesco_world_heritage_sites.py
csv output: unesco_world_heritage_sites.csv

To extract multiple tables on the world's best cities to live compiled by the Global Finance magazine.

py script: web_scraping_best_cities_to_live.py
csv output: best_cities_to_live.csv

To extract the Rolling Stone list on the greatest albums of all time.

py script: web_scraping_rs_500_greatest_albums.py
csv output: rs_album_list.csv

To extract data of all hardcover fiction/nonfiction books for all the best sellers lists of the New York Times.

py script: web_scraping_nyt_api.py
csv output: nyt_bestsellers_books.csv