Abstract:Variables for individuals are developed with dynamic characteristics in many panel data sets when we deal with agriculture insurance pricing．In papers for panel data clustering,the similaritycoefficients are computed by the numerical character,distribution character,and fluctuant character,butthe clustering results cannot reflect the dynamic characteristics．This paper proposes the method to applyadaptive affinity propagation clustering(ad-AP),which is improved from affinity propagation clustering,to optimize panel data set,and compute the best exemplars of each individual which constitute a new dataset．Then panel data clustering analysis is transform into the new dataset clustering analysis．Experimentalresults on china agriculture insurance show the validity,practicability and interpretability of the design forpanel data with dynamic characteristics．