Project 1: Home Value Patterns Due to COVID-19

By: Jenni Davis, Jason Sheridan, Anna Sours, Austin Olea, & Mark Blankenship

Hypothesis: Where COVID-19 cases are higher in counties with major cities, home values will increase in the surrounding counties.

Guiding Questions:

• How are people migrating throughout the US since COVID 19 began?
• Has this impacted home values?
• Is there a relationship between cases and the housing market?

Data Sources:

COVID-19 Cases:

• NY Times US states & counties
• Texts files with state, county, date, cases, etc.
• US census data
  • Shapefiles
• API calls
  • Coordinates
• New dependencies for mapping
  • geopandas
  • folium

Home values:

• Zillow Home Value Index (ZHVI) from zillow.com
  • CSV files updated monthly
  • ZHVI values for Metro & U.S.
  • Monthly values from 1/31/1996 - 12/31/2020

COVID-19 Data Exploration

Analysis 1:

NY Times US states & counties

• Q: What states have the highest count of COVID-19 cases? And of those states, which counties had the highest count of COVID-19 cases?

Exploration & Data Wrangling:

• NY Times data *US states & counties data - date, state, county, cases, etc.

  • Methods:
    • Filtering
    • Grouping
    • Stats
    • Dropping values
    • Sorting values
    • Horizontal bar chart

Analysis 2:

API calls, US census data & geopandas

• Q: Can we take the NYTimes data and layer it onto a map of the United States and have it display state name and maximum case counts?

Exploration & Data Wrangling:

• API calls *Coordinates

• US census data *Shapefiles

• Geopandas

• Methods:

  • API calls
  • Shapefiles
  • Export/Import csv files
  • More: filtering, grouping, dropping
  • Adding/renaming columns
  • Merging

• States determined for further analysis:
  • California
  • Texas
  • Florida

Analysis 3:

More mapping…?

• Q: Can we use heat maps and markers to better highlight the counties with maximum cases and their surrounding counties?

Exploration & Data Wrangling:

• Folium

  • Mapping library

  • Methods:

    • Gmaps
    • Heatmaps
    • Folium
    • Lists...
    • Lists of coordinates...
    • Lists of cities...
    • LISTS!

Home Values of Counties with high COVID-19 Cases

California

Florida

Texas

Percent Change in Home Values

• The blue bars show the average home value increase over the 3 years prior to covid.

• pre_covid_annual=((((feb2020-mar2017)/feb2020)/3)*100).values[0]

• The orange bars show the home value increase from March 2020, when the covid lockdowns began until December 2020.

  • covid_annual=(((dec2020-mar2020)/dec2020)*100).values[0]

Comparing the home values of the pre-Covid and during Covid time frames for the counties with the highest number of covid cases as well as the surrounding counties, most of the surrounging counties did see a greater percentage increase in home values after the Covid lockdowns began than in the years before Covid.

California

Florida

Texas

Conclusion Summary

• In the majority of the metro-area counties analyzed, home values increased at a greater rate in 2020 than the average rate from 2017-2019. It also appears that values increased at a proportionally higher level in areas with lower COVID-19 cases.

Implications of findings

• What does our conclusion mean?
  • According to these metrics, in most areas, we found increased home values in counties surrounding cities with highest COVID-19 cases. This could be due to a desire to leave more densely populated areas, away from areas with higher COVID cases.
• What are next steps/further analysis?
  • Analyze data from counties with major cities with fewer COVID-19 cases
  • Analyze housing values against other market factors to further understand the impact of COVID-19
  • Analyze type and size of home purchased against the type of home sold by a particular buyer