Sales of Electric Vehicles (EVs) in the United States have grown fast in the past decade. We analyze the Electric Vehicle Drive Clean Rebate data from the New York State Energy Research and Development Authority (NYSERDA) to understand consumer behavior in EV purchasing and their potential environmental impact. Based on completed rebate applications since 2017, this dataset features the make and model of the EV that consumers purchased, the geographic location of EV consumers, transaction type to obtain the EV, projected environmental impact, and tax incentive issued. This analysis consists of a mapped and calculated statistical data analysis over an established period. Using the SAP Analytics Cloud (SAC), we first import and clean the data to generate statistical snapshots for some primary attributes. Next, different EV options were evaluated based on environmental carbon footprints and rebate amounts. Finally, visualization, geo, and time-series analysis presented further insights and recommendations. This analysis helps the reader to understand consumers' EV buying behavior, such as the change of most popular maker and model over time, acceptance of EVs in different regions in New York State, and funds required to support clean air initiatives. Conclusions from the current study will facilitate the use of renewable energy, reduce reliance on fossil fuels, and accelerate economic growth sustainably, in addition to analyzing the trend of rebate funding size over the years and predicting future funding.

翻译：过去十年间，美国电动汽车（EV）的销量快速增长。本研究通过分析纽约州能源研究与开发局（NYSERDA）提供的"电动汽车清洁驾驶退税"数据，旨在理解消费者在EV购买中的行为及其潜在环境影响。该数据集基于2017年以来的完整退税申请，包含消费者所购EV的制造商与型号、消费者的地理位置、获取EV的交易类型、预估环境影响以及发放的税收优惠。本研究在既定时间段内开展了地图化与计算化的统计数据解析。我们首先利用SAP分析云（SAC）导入并清洗数据，生成若干主要属性的统计快照；随后，基于环境碳足迹与退税金额对不同EV选项进行评估；最后，通过可视化、地理空间分析及时间序列分析呈现了进一步的洞察与建议。本分析有助于读者理解消费者的EV购买行为，例如热门制造商与型号随时间的变化、纽约州不同区域对EV的接受程度，以及支持清洁空气倡议所需的资金。除分析历年退税资金规模趋势并预测未来资金需求外，当前研究的结论还将促进可再生能源利用、减少对化石燃料的依赖，并可持续地加速经济增长。