Az Residential Real Estate Analysis

-Decided on libraries to import. Includes pandas, json, requests, plotly express, hvplot, geopandas, numpy and url.

-Read in a nested json and cvs files of residential properties for sale in PHX and surrounding areas, and sorted through the atrributes to get our dataframes in a clean format.

-Using urlopen, we read other json files into a sperate dataframe to plot and compare with our other data.

-Analyzed and plotted the data using plotly, hvplot, and geopandas.

-Plots included a map of hotspots, a histogram of price, and other maps showing differences in price between neighborhoods.

You can run this locally with the jupyterlab file, as long as you are in a pyviz enviroment.
There is also a powerpoint attached detailing our findings in an easy-to-interpret manner.

Our goal was to

 

 

 

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