- Kum Hyun Lee (khl2139@columbia.edu)
- Mengying Xu (mx2238@columbia.edu)
- Yi Hyun Kim (yk2906@columbia.edu)
Click here to view our website.
This project aims to explore how the Covid-19 pandemic has impacted the housing market by focusing on comparing the sales price across NYC. The project will track how the waves of Covid-19 cases affected the price fluctuations by conducting data analysis on quarterly tabular, spatial and text data, with illustrations.
Research Questions:
- How has Covid-19 affected the housing market via housing prices over time?
- How has COVID-19 affected the NYC housing market? Are there any regional variations in the housing price fluctuations?
- How has the overall perspective on Covid-19 changed over time?
The website has been coded using HTML, CSS, and JavaScript from scratch to build a simple, yet user-friendly website.
Part 1 examines Covid-19 rate and sales prices in all five boroughs in NYC from the 3rd quarter of 2020 to the 1st quarter of 2022. ggplot2 and ggplotly in R is used to create the visualizations.
This section maps out the changes in the NYC Covid-19 case rates and housing prices by quarter using ggplot2. Specific neighborhoods are consulted from the analysis.
Two hypothesis are tested in this section:
- The association between Covid-19 and housing prices is negative.
- The association between Covid-19 and housing prices is positive.
The final section studies the changes of perspective on Covid-19 over time (2020 Q3 vs. 2021 Q4) by conducting sentiment analysis and creating word clouds using Python.
- Covid-19: Case Rate by MODZCTA
- Housing: NYC Housing Sales Data
- Mapping: Modified Zip Code Tabulation Areas (MODZCTA)
- Text Analysis: Tweets
The codes we did for data analysis and producing visualizations can be found here and the codes used for building the website can be found here .
Our process book that logs our work from start to end can be found here
- Note: this can only be viewed by LionMail.