The observed transition towards electric vehicles (EVs) globally calls for a well-planned rollout of public charging stations to accommodate the anticipated increasing EV charging demand. Grid operators face challenges with infrastructure expansion while also seeing new opportunities open, such as utilizing charging load patterns to balance grid power flows. Currently, there is limited availability of insights covering the locally heterogeneous behavior observed at public charging points distributed across population centers. This research fills this research gap by examining real world charging data. By combining charging session data with geospatial information, we can extract characteristics of local EV charging demand load curves. The study provides insights through the analysis of temporal patterns in demand, distribution of charging events across various urban areas, and characteristics of electrical load profiles, which are instrumental in planning further infrastructure expansion. The analysis clearly shows distinct charging demand during the weekdays and weekends, different charging demand splits across various location types, and also the difference in the charging behavior depending on the type of the area surrounding the chargers.