Census

A post showing how PROC HTTP and LIBNAME JSON can be used to directly work with the Census API from SAS.

The Census Bureau has updated its population estimates for 2020 with county level data. This means any projects that have had to rely on the 2019 estimates can now switch to the 2020 estimates. ...

A popular beginners machine learning problem is the prediction of housing prices. A frequently used data set for this purpose uses housing prices in California along some additional gathered through the 1990 Census. One such data set is available here at Kaggle. Unfortunately, that data set is rather old. And I live in North Carolina, not California! So I figured I might as well create a new housing data set, but this time with more up-to-date information and using North Carolina as the state to be analyzed. One thing that may be interesting about North Carlina as compared to California is the position of major populations centers. In California, major population centers are near the beach, while major population centers in North Carolina are in the interior of the state. Both large citites and proximity to the beach tend to correlate with higher housing prices. In California, unlike in North Carolina, both of these go together. ...

The Census Bureau makes an incredible amount of data available online. In this post, I will summarize how to get access to this data via Python by using the Census Bureau’s API. The Census Bureau makes a pretty useful guide available here - I recommend checking it out. ...