This article introduces the concept and various methods of sensitivity analysis—including one‑factor, multi‑factor, variance‑based, and Monte Carlo approaches—explains Sobol indices, outlines step‑by‑step procedures, and demonstrates their application with a Python case study on urban air‑quality modeling.
This article walks through reading Excel air‑quality data with pandas and creating four‑panel visualizations of AQI, pollutants, temperature and humidity using Matplotlib, providing complete code and tips for handling common plotting pitfalls.
Using Python's BeautifulSoup library, this guide walks you through building a web scraper that extracts real‑time weather details—including region, AQI, primary pollutant, and PM2.5 concentration—from the Green Breath website, handling missing data and providing console output for any Chinese city.
This guide demonstrates how to use Python's BeautifulSoup library to crawl the Green Breath website, extract real‑time weather and PM2.5 information, handle missing data with conditional checks, and display the results directly in the PyCharm console, providing a practical example of web‑scraping for environmental monitoring.
