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Project Motivation
Project Motivation
We are aiming to analyze the supply and demand of EV charging stations across Washington State. We are looking at the number of electric vehicles registered in the state based on their city of registration to see if there is a sufficient number of stations located in the area.
Furthermore, we are looking at the potential influence of socioeconomic characteristics of the cities on EV adoption. Our analysis will concentrate on the median household income and maximum level of education attainment of the population as possible factors affecting the EV adoption rates.
Our project is especially relevant in the context of the recent trends directed towards greener cities and better ecology. The successful transition to electric vehicles relies heavily on the confidence of car owners in the availability and accessibility of charging infrastructure.
By investigating the connection between socioeconomic characteristics and EV adoption, our research aims to contribute essential information that can facilitate possible infrastructure improvements, fostering a more sustainable and eco-friendly transportation landscape.
Tools and Technology used:
Tools and Technology used:
Data Preprocessing, EDA and ML model: Python
Data Preprocessing, EDA and ML model: Python
Data Visualization: Tableau, ArcGIS
Data Visualization: Tableau, ArcGIS
Video Editing: Zoom, Adobe Premier
Video Editing: Zoom, Adobe Premier
Our Approach:
Our Approach:
Acquisition of datasets.
Preprocessing and cleaning of data included:
Using the crosswalk database to switch from ZCTA to ZIP
Removing missing values
Identifying columns of interest across the datasets
Joining tables to create one dataset.
Exploratory Data Analysis in Tableau and Python
Data visualization in ArcGIS
Data modeling
Drawing conclusions and further research suggestions
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