In this challenge, your job is to use your data visualization skills, including aggregation, interactive visualizations, and geospatial analysis, to find properties in the San Francisco market that are viable investment opportunities.
Use the san_francisco_housing.ipynb notebook to visualize and analyze the real-estate data.
Note that this assignment requires you to create a visualization by using hvPlot and GeoViews. Additionally, you need to read the sfo_neighborhoods_census_data.csv file from the Resources folder into the notebook and create the DataFrame that you’ll use in the analysis.
The main task in this Challenge is to visualize and analyze the real-estate data in your Jupyter notebook. Use the san_francisco_housing.ipynb notebook to complete the following tasks:
-
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.