Utilize data visualization skills, including aggregation, interactive visualizations, and geospatial analysis, to find properties in the San Francisco market that are viable investment opportunities.
- Calculate and plot the housing units per year.
- Calculate and plot the average prices per square foot.
- Compare the average prices by neighborhood.
- Build an interactive neighborhood map.
- Compose your data story.
Utilize numerical and visual aggregation to calculate the number of housing units per year, and then visualize the results as a bar chart.
Answer the following question:
- What's the overall trend in housing units over the period that you're analyzing?
Utilize numerical and visual aggregation to calculate the average prices per square foot, and then visualize the results as a bar chart.
Utilize interactive visualizations and widgets to explore the average sale price per square foot by neighborhood.
Explore the geospatial relationships in the data by using interactive visualizations with hvPlot and GeoViews. To build your map, use the sfo_data_df DataFrame (created during the initial import), which includes the neighborhood location data with the average prices.
Based on the visualizations that you created, answer the following questions:
- How does the trend in rental income growth compare to the trend in sales prices? Does this same trend hold true for all the neighborhoods across San Francisco?
- What insights can you share with your company about the potential one-click, buy-and-rent strategy that they're pursuing? Do neighborhoods exist that you would suggest for investment, and why?