In this project, our group examines the EVCS (Electric Vehicle Charging Stations) with major roadway street networks in the urban Southern California region to extract its complex network properties and to find the correlation between various data attributes using data science methods. Some data inputs include the 2019 American Community Survey (ACS) census data for demographic correlation, electric vehicle (EV) registration as well as Longitudinal Employer-Household Dynamics (LEHD) commute flow data for estimating local charging demand. Through this data aggregation, we find many electric vehicles to be located in West Los Angeles and in Orange County where higher income individuals also reside. In addition, we find an imbalance in the number of job destinations with the number of chargers available in some Zip Codes. Using open-source python packages, we clustered the EVCS into six groups within our study region to study their correlated characteristics both demographically and geospatially.
For the full project report, see PDF file under the repo directory.