In the study of criminal incidence, the lack of graphical specialized tools makes it difficult to properly communicate in a consistent way, and with simple terms, its spatio-temporal evolution. In this work, we propose the application of a count-based trajectory time series analysis to study the spatio-temporal evolution of larceny theft in Mexico City. This framework helps describing the spatio-temporal evolution of an event by identifying and grouping the individual location dynamics that contribute in the description of the types and magnitude of different changes in space. These changes can be expressed in terms of gains, losses, and possible alternations that generate exchange of criminal incidence without observing significant gross loss or gain in incidence. We highlight the characteristics that are beneficial to the interpretation of the spatio-temporal evolution of crime incidence and the drawbacks of using this technique. We conclude that while there is a general decreasing trend of crime incidence, the graphical method is sensitive to show internal patterns such as gains, losses and alternation, that are important to analyze key spatio-temporal patterns throughout the years. This approach is intended to be useful for evaluating strategies for the reduction of criminal incidence.