The objective of this project is to identify the best locations in Kuala Lumpur for opening a new shopping mall using data science methodologies and machine learning techniques. By extracting data from Wikipedia and Foursquare API, it aims to analyze neighborhood demographics, geographical coordinates, and existing venue data to make informed recommendations. The project employs web scraping for data extraction, data cleaning, and wrangling processes to ensure data accuracy.
Using K-means clustering, the project will group similar neighborhoods to identify potential locations for new shopping malls. The project will also utilize map visualization techniques with Folium to visually present the findings. This comprehensive approach leverages various data science skills, including web scraping, API integration, machine learning, and data visualization, to provide data-driven recommendations to property developers in Kuala Lumpur.