Design of a Web Crawler for Water Quality Monitoring Data and Data Visualization

This is the authors' abstract. We don't add key points for this paper.

Many countries are paying more and more attention to the protection of water resources at present, and how to protect water resources has received extensive attention from society. Water quality monitoring is the key work to water resources protection. How to efficiently collect and analyze water quality monitoring data is an important aspect of water resources protection. In this paper, python programming tools and regular expressions were used to design a web crawler for the acquisition of water quality monitoring data from Global Freshwater Quality Database (GEMStat) sites, and the multi-thread parallelism was added to improve the efficiency in the process of downloading and parsing. In order to analyze and process the crawled water quality data, Pandas and Pyecharts are used to visualize the water quality data to show the intrinsic correlation and spatiotemporal relationship of the data.