I have just released an update to my blsAPI R package. Some users noticed the return.data.frame parameter was returning some strange results. I resolved the bugs and made the output cleaner. I appreciate hearing back from users on ways to improve the package. For more information on the blsAPI package, please see my GitHub repository.
As part of the Developing Data Products Coursera course I was introduced to ŷhat. ŷhat is a great product that allows developers to create models in R or Python and the publish them to their platform. You can then send the hosted model parameters and get a prediction from it.
My model (available on GitHub of course) it a k-nearest counties model. It is loosely based on the idea of k-nearest neighbors however the only dimensions it compares on it latitude and longitude. You provide the model with a latitude and longitude and the number of counties you want it to return (k) and the model will give the name of the county, FIPS code, and distance for your points.
I could see myself using this in developing visualizations where I have a series of points and want to know which county the points fall in. I could also see using this to support geocoded information. I recently had to aggregate geocoded information into metropolitan areas. I used Google’s geocoding API to try to tease out the county name of the point, but didn’t have the FIPS code to aggregate to the MSA level. ŷhat is a great product which I recommend to anyone looking for a simple yet effective way to make awesome data products.
I have completed the Data Scientist Toolbox course and have received my certificate. I am currently waiting for the grading process to complete with R Programming. I completed this course with distinction.
I have been putting my rudimentary skill to use at work. You can check out what I have done on GitHub (https://github.com/mikeasilva/cgr-work).
I have begun developing a R wrapper for the FRED API. It is hosted on GitHub at: https://github.com/mikeasilva/fredAPI. You will need to sign up for a FRED API key to use the wrapper.
Let’s say you want to pull Annual Real Gross National Product. Here’s how you could do it:
> fred <- fredAPI()
> fred$key('My FRED API key here')
> xml <- fred$series_observations('GNPCA')
As part of the Coursera’s “The Data Scientist’s Toolbox” course I have created a GitHub account. You can see my work at https://github.com/mikeasilva. Not only does it have my Coursera work but I have created a repo for things I have developed for my current job. I also plan on uploading research files in the future.