Abstract: For the comprehensive ranking of urban economic level and environmental level in China, there have been some index system ranking methods, but most of them involve multivariate data. With the rapid change of data acquisition technology, data become more and more complex. The observational data produced in some fields is no longer a single type of data, but a combination of various types of data. This paper studies how to rank them when the index system involves functional data. In this paper, four ranking methods are proposed and compared. The results are as follows: when the functional data is contaminated, the entropy weight method results are relatively stable; when the scalar data is contaminated, the multivariate modified banding depth is more stable. The research shows that the selection of ranking methods for multi-type data depends on the characteristics of the data. This research enriches the comprehensive ranking of multi-type data and has good practical significance.