Despite the clear benefits of electric vehicles (EVs) in terms of reducing greenhouse gas emissions and traditional energy consumptions, the popularization of EVs remains a challenge in the short run. When considering electric taxis, urban planners must face the additional issue of providing battery swapping services. While previous studies focused on planning battery swapping stations for private EVs, we investigate ways of supporting the upgrade of an entire urban taxi system, with demands differing both in scale and nature. With this insight, we analyze the historical sensing data of taxi routes, and evaluate the battery swapping demand profile, as well as the driving time between positions in the road network. Based on these inputs, we propose a method to calculate an optimized battery swapping station scheme. Our strategies are then evaluated via a real world 366-day, 3,976-taxi dataset. The results show that compared to uniform deployment, our planning scheme reduces the average time-cost by 67.2%.