In this blog, we will practice web data scraping by scraping names, addresses, cuisine types, and star ratings of Michelin-Star restaurants in Singapore to know cuisine-type distribution and geolocations.
There isn’t a single website that effortlessly contains both; therefore, we recognized a news website with an address and an official Michelin website having cuisine types. We have used rvest and selector gadgets to gather data and made some cleaning, like a minority of lessons get prearranged with various CSS ids in a frame, and cuisine types comprise both Chinese and English words.
Then we used BatchGeo to get geocoding using addresses that are somewhat accurate and conveniently offer a map, excluding it isn’t apparent whether it offers latitude or longitude data in the output.
They are mainly centrally positioned in about 3 clusters:
From Tanjong Pagar to City Hall (city center)
Within the Botanic or Orchard Gardens area (touristy/shopping area)
3 within Sentosa, one each from 1-star (named Osia), 2-star (named L’Atelier de Joel Robuchon), and 3-star (named Joel Robuchon), all are touristy or rich residential areas
In the next step, we can match restaurant names (different spellings) from any two sources to get cuisine type, group them through geographical districts and recognize distances to various residential areas.
You can find the scraped data here. Thank you for reading this blog. You can always contact Food Data Scrape for more information or all food data scraping service requirements.