In this research, the identification of time and space patterns of bus passengers through the study, processing and statistical analysis of transaction data of Automatic Fare Collection in the public transportation system of Isfahan has been made. Spatial analysis has been made in the form of a survey of transitions between different lines, and time analysis has led to clustering of bus passengers. It was found that trips with a transfer share has a large share of bus trips. Repeated transitions identified between lines. In places with high passenger line chaneges, a high percentage of them without any other activity ride from the first line to the second line. For each type of transfers between the lines, an exclusive statistical analysis is presented. In the process of clustering, first, the atribiutes that include the monthly characteristics of individuals were defined and calculated using the software SQL. Finally, clustering was performed using calculated characteristics. The people using the public transportation service and the type of people in each category were identified and the share of each group of passengers was determined from the total public transportation passengers. The results of this research are used by urban transport managers and planners and help to improve urban public transportation.