Research Question
How have public drinking complaints in New York City evolved over time because of the coronavirus pandemic, and how do these trends vary across boroughs and incident types?
This research is driven by my curious desire to uncover trends in urban dynamics and public safety, especially as these topics become an increasing priority for New Yorkers. Understanding the temporal evolution of public drinking complaints provides insights into the changing social, economic, and environmental factors influencing the city. By examining the impact of external factors like pandemic restrictions and economic strain, this research sheds light on how crises can exacerbate certain social issues. Furthermore, analyzing variations across boroughs helps identify localized patterns and disparities, informing targeted interventions and resource allocation. Investigating incident types allows for a nuanced understanding of where and how public drinking occurs, enabling policymakers and law enforcement agencies to develop more effective strategies for prevention and enforcement. Overall, answering this research question contributes to enhancing public health, safety, and quality of life in NYC.
Methodology and Results
In my first dashboard, I set out to unveil overarching trends within public drinking complaints in NYC. Employing a line graph spanning from 2010 to 2023, equipped with a borough filter, I showcased a striking surge in reported complaints, notably doubling from 2019 to 2020. This sharp uptick, spurred by pandemic restrictions, economic strain, and a burgeoning homeless population, underscored the city’s evolving landscape. I chose a line graph for this visualization because line graphs are the most effective at tracking the progression or regression of a variable over time. To further validate my hypothesis that there were a higher number of complaints in the summer, I delved into seasonal variations by leveraging a monthly bar graph. I used a bar graph because the vertical bars make it simple to see a difference in magnitude between each month’s data point, providing a clear representation of changes over time. Confirming expectations, I revealed a peak in public alcohol complaints during warmer months, attributed to the reopening of public spaces and marquee events like music festivals and parades.
Transitioning to my second dashboard, I aimed to pinpoint the borough(s) driving the noted surge in complaints between 2019 and 2020. Employing an interactive pie chart with a year filter, I discerned a notable shift: while the Bronx and Queens accounted for 45% of complaints from 2010 to 2019, this figure surged to 62% post-2020. I chose to use a pie chart with an interactive year filter to allow the user to see the proportion of each borough’s reported complaints by year(s). Further exploration via an interactive map and an address-centric graph highlighted that 7 addresses in the Bronx were associated with a staggering 1,639 incidents and two addresses in Queens were linked to 229 incidents from 2020 to 2023. These incident addresses were mainly residential building addresses. I thought that the interactive map and address-centric graph complemented each other seamlessly. The map offers users a visual representation of how influential the top incident addresses are in driving neighborhoods and boroughs with the highest complaint proportions in the city.
Driven by curiosity, I embarked on a deeper dive into incident types and locations through a third dashboard. Employing an interactive pie chart and line chart, I dissected the breakdown of incident locations by borough and year. I used two pie charts- one representing the years 2010 to 2019 and the other covering 2020 to 2023- to draw attention to the disparity in location breakdown between pre-pandemic and post-pandemic periods. The line chart provides a broader perspective on the location breakdown throughout the years. Notably, I uncovered a near twofold increase in complaints regarding drinking in store/commercial premises post-2020 across all boroughs, except Staten Island. Interestingly, while citywide trends indicated a decline in residential-based complaints post-2020, the Bronx exhibited a slight increase, highlighting its distinct role within the city’s public alcohol complaints.
Moving Forward
In the future, there are several directions that could enhance this project to further explore and understand public drinking complaints in NYC. For example, adding geospatial analysis by incorporating the proximity of alcohol-selling establishments or homeless shelters could allow me to better understand the distribution of complaints. It could also be helpful to integrate datasets about median income per zip code or emergency room admissions related to alcohol intoxication to provide a more holistic understanding of alcohol-related issues in the city.
In conclusion, this research journey has provided valuable insights into the endless choices in data visualizations but also into the trends of public drinking complaints in NYC, offering a foundation for future explorations.
