Interactive Bay Area Rental Price Heatmap by Census Tract

In our last post, our Chief Data Scientist plotted average rental prices per square foot in each ZIP Code in the San Francisco Bay Area through a quick hack using new mapping packages for R-Studio.  In true startup style, we have iterated on that and now have something better based on the feedback that we received.  


How have we iterated you ask?  Well, we have iterated in three major ways:  

First, we have made the map web-based and interactive.  Now you can “mouse” over different areas to get information instead of tediously matching areas with our raw data.  Also, in response to some of the comments, it is now easier to see different cities and towns underneath our pricing information.

Second, in tune with our quest to provide the most granular information possible, we have mapped the data by census tract.  According to the Census Bureau, Census tracts are designed to be “relatively homogeneous units with respect to population characteristics, economic status, and living conditions… census tracts average about 4,000 inhabitants.”  We look forward to leveraging the public data available from the US Census to analyze things like income and demographics compared to rent in the near future.

Finally, whereas we presented the average price per square foot the last time, we presented the median price per square foot here.  We have discussed this in a previous post, but medians tend to be a more telling depiction of pricing than averages because there is a lower likelihood of an outlier skewing the sample.

As we noted in our last post, it is always somewhat astounding to see the disparities of rent pricing in seemingly close geographic locales.  But even more basically, it is incredibly eye-popping how high rents are generally.  Then again, this should come as no surprise, as according to David Crowe of the National Homebuilders’ Association, “[a]ll of the net addition to households since 2004 has been in rentals.”

To play with the web-based map, please go here.  Let us know what you think.

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