Characterizing mobile networks' data traffic in the time and space domains is critical in improving how these networks are dynamically configured. In this paper, we study the NetMob 2023 Data Challenge dataset. We first establish the existence of a weekly pattern for the total traffic in each major city in France. We show that the daily pattern is essentially the same from Monday till Thursday but with more traffic on Wednesday. Some deviations are clearly visible on Friday. Using the IRIS zones, we try to group zones exhibiting similar patterns. We find that four or five different clusters can best characterize the traffic in most cities. Identifying these clusters is a valuable step in optimizing the placement of network functions. Finally, we analyze the percentage of traffic generated by different applications, showing that, while the overall percentage of traffic generated by an application is similar in each city, the spatial diversity for a given application varies from city to city.