How to Build a Job Market Heatmap with Web Scraping

Job postings reveal where the economy is heading. Which skills are in demand, which cities are hiring, and which industries are growing. In this tutorial, we'll scrape job listings and build an interactive heatmap. What We'll Build Multi-site job listing scraper Geographic and skill-based analysis Interactive heatmap visualization Trend tracking over time Setup pip install requests beautifulsoup4 pandas folium geopy Job Listing Scraper import requests from bs4 import BeautifulSoup import time from datetime import datetime SCRAPER_API_KEY = " YOUR_KEY " def scrape_job_listings ( keyword , location = "" , page = 1 ): """ Scrape job listings from a job board. """ url = ( f " https://www.indeed.com/jobs " f " ?q= { keyword } &l= { location } &start= { page * 10 } " ) api_url = ( f " http://api.scraperapi.com?api_key= { SCRAPER_API_KEY } " f " &url= { url } " ) response = requests . get ( api_url , timeout = 60 ) soup = BeautifulSoup ( response . text , " html.parser " ) jobs = [] for card