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My First Shiny App

The developers of RStudio have created this wonderful package called shiny. It allows you to create little apps using R. You can deploy your app on a server or used their cloud based service.  I played around with it and have created my first app and have chosen to use the cloud based solution.  My first app is the BEA Data Explorer.

Since shiny allows for visualization of the data I think it is a great tool when you are exploring a data set for the first time.  It helps you to get a feel for the data.  This app allows me to look at the BEA data for metros.  I can easily filter the data, view the relationships between two variables, and even cluster them using k-means.  I would love to hear what you think of my app!

bea-app

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FRED API for R

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')

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Bureau of Economic Analysis API

Following in the footstep of my previous posts on the FRED API and the BLS and Census Bureau API, I want to pass on another data source.

The Bureau of Economic Analysis (or BEA) has an API.  They are the people who come up with the GDP estimates (among other things).  You can register for an API key, and read the documentation (their user guide is quite good).  The URI is http://www.bea.gov/api/data.  You can get data in JSON and XML formats.

Once I become more proficient with Python, I plan on programming a wrapper for this API.  I will announce when that project is complete here.

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A Couple of Great Blog Posts on Panda

While working with Pandas today I came across two great blog posts.  The first is Greg Reda’s Intro to Pandas Data Structures.  He give a great tutorial complete with some examples.  His writing is clear and concise.

The second is Mikhail Semeniuk’s Python Pandas Tutorial.  This post was interesting to me because of examples of how to run regressions.  This is something I will put to use.

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More Economic Data APIs

I previously posted about the FRED API which got me thinking that there are other APIs that others might not be aware of.  I would like to pass them on.

The U.S. Census Bureau has an API that give you access to economic indicators, as well as demographic data (decennial census and American Community Survey data).  I just requested my API key.  Sunlight Labs has programmed a Python wrapper but it looks to be a bit outdated.

The U.S. Bureau of Labor Statistics also has an API.  I have used the API to get unemployment rates for some widgets I’ve programmed (example).  I’m not sure if there are series that are available through the BLS that are not available through FRED.  There is also a 3rd party Python wrapper.

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St. Louis Fed FRED API

I just wanted to pass on a link that I intend to use. I read an article that stated there is a lack of data sets for people interested in becoming a data scientist to use. I found that strange given the large amounts of data available in the Economics field.

The St. Louis Federal Reserve Bank, has the Federal Reserve Economic Data system or FRED. There are 212,000 time series from 62 sources. They also have an API, and a 3rd party Python wrapper.