Abstract: The air-source heat pump system, known for its high energy efficiency and low environmental impact, is widely used in China for heating and cooling applications. However, the operational data of such systems is complex and variable that make it crucial to effectively analyze and extract key information in order to enhance the system's operational efficiency. This study employed Principal Component Analysis （PCA） and correlation analysis to deeply mine the operational data of the air-source heat pump system. PCA was used to extract the key features of the system, including temperature variation, power consumption, electrical performance, heat exchange efficiency, and environmental factors. The analysis helped identify the most influential factors affecting the system’s performance. The results of Pearson linear correlation analysis revealed strong correlations between input power and phase current, as well as a close relationship between heat exchange and the temperature difference at the heat exchanger outlet. Furthermore, the Coefficient of Performance （COP） showed a significant correlation with the heat exchange process, emphasizing the importance of enhancing heat transfer to improve energy efficiency. Spearman rank correlation analysis was also conducted, revealing that the rank correlation coefficients between input power and phase current, as well as between heat exchange rate and the temperature difference at the heat exchanger outlet, were both greater than 0.8. Additionally, the rank correlation coefficient for COP and heat exchange rate exceeded 0.7. These high rank correlation coefficients indicated that, even within a complex and nonlinear system, the relationships between these parameters remained highly significant. The results of this research demonstrate that PCA and correlation analysis are effective tools for extracting key information from the operational data of the air-source heat pump system. These techniques can significantly improve the efficiency and accuracy of performance prediction and fault diagnosis, providing valuable insights for the optimization and maintenance of the system. Today, these methods continue to play a crucial role in enhancing the performance and reliability of air-source heat pump systems.