Chapter 7 Conclusion

Limitations:

In Chapter 4 Missing Values, two plots are accidentally replaced by two irrelevant plots in other chapters. We cannot resolve this problem because the plots are correctly shown when we knit to html using local r-studio. The data source contains a lot of interesting information but some of them have missing values more than our expectations, such as CardAccepted column, thus we have to drop them. We are also interested in how COVID-19 impacts EV sales in NY. Although we see a decline in newly constructed EV charging stations, we don’t know how many new EV registrations added in 2020.

Future Directions:

As we discussed in the previous paragraph, we may observe different patterns in EV registration if 2020 data is released. Due to time limitation, in this project we only focused on New York State EV records. In fact, California, Washington and many other states have better EV sales than NY. Especially we saw a greater market share in California Bay area. As one of the future directions, we would like to source data from other states and compare time series patterns in newly registered EVs, as well as attributes of charging stations. Another direction could be making an interactive query map: for new EV owners who are interested in nearby EV charger locations, types, and operating times, the interactive query map could easily provide such information by selecting criteria. While there are existing online tools for locating EV chargers, we need to further explore how to make our tool unique, for example, incorporate other real time data such as traffic flow.