Research on the Application of Intelligent Tourism Data Analysis Based on Python

Abstract

With the rapid development of technology, smart tourism has become a disruptive innovation in the tourism industry. This article explores the key role and application scenarios of Python-based data analysis applications in the field of smart tourism. Firstly, we focused on the tourism destination recommendation system and provided a detailed introduction to the principles and applications of personalized recommendation algorithms. These algorithms utilize Python's data analysis libraries, such as Pandas and NumPy, to process a large amount of user data to provide personalized destination recommendations for tourists. Secondly, the field of real-time transportation and route planning was studied, with a focus on real-time traffic data analysis and intelligent route optimization. Python's data processing and machine learning tools are used to analyze traffic conditions, provide the best routes, and help tourists avoid traffic congestion. Finally, we focused on attraction management and experience improvement. Tourist behavior analysis uses Python's data science technologies, such as data mining, to gain insights into tourists' needs and behavior patterns. This enables attraction managers to better optimize service processes, provide personalized guides, and improve the tourist experience.