A city-scale dataset of public electric vehicle charging transactions and infrastructure

With the rapid adoption of electric vehicles in megacities, the operation of public charging infrastructure has generated a large volume of real-world transaction data. These data are essential for characterizing urban-scale charging demand, facility utilization patterns, and operational mechanisms. However, most publicly available electric vehicle charging datasets are constrained by limited spatial coverage, small sample sizes, or coarse data granularity. In particular, there is a lack of transaction-level data for public charging infrastructure that are resolved at the charging connector level, which limits their suitability for systematic analyses at the city scale. Here, we release a city-scale public charging transaction dataset derived from charging station operators in Beijing, China. The dataset covers public charging stations across all administrative districts of Beijing and contains transaction records from January and July 2025. It comprises 8.544 million charging transactions generated by 8,553 public charging stations. The released dataset is organized into separate transaction-level and station-level tables. The transaction-level table contains anonymized charging transaction information, while the station-level table contains anonymized station attributes. This enables the characterization of temporal patterns of charging demand and aggregated spatial characteristics of public charging infrastructure in Beijing. Owing to its large sample size and anonymized transaction-level and station-level information, this dataset supports analyses of charging behavior and public charging infrastructure characteristics at aggregated spatial and temporal scales. It also provides an empirical basis for the evaluation and optimization of public charging systems in megacities.