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  • Writer's pictureTim Burns

Create Actionable Datasets by Combining Sources

Updated: Dec 3, 2023


Brittney Howard performing Stay High on KEXP


Good Data drives actions. A stunning dashboard is good for impressing others, but the real value comes from the data we use to guide our actions. One data set alone may be interesting, but the real litmus test of good data is that it causes us to do things. Spend money, fix a problem, save money.


I like to use my data sets to fill my life with music, and that is why I spent Thanksgiving working on a Python Client to query Seat Geek's API about upcoming local events.


I wanted to have a way to match my top artist dashboards with buying tickets to shows of new artists near where I live. To do this, I wrote a simple Python client to pull data based on output data from the dashboard.

It will determine your location using your public IP address and give back a JSON object.


Why is it interesting? Data value is based on multipliers. If we combine two data sources and cross-reference the two, the value also multiplies.


For example, I gather data on the top new bands from the KEXP radio playlist dashboard. The top artist on my Tableau Dashboard today is Brittney Howard (she's AMAZING!).



Using that as input to the API, I can run the query to check where Brittney Howard is playing near me:


./seatgeek/seatgeek_client.py --get events --geoip --range 50mi --type concert --performers brittany-howard > brittney.json


I now have tickets to see Brittney Howard at the Wilbur on February 12th. That's what I call "Actionable Data Analysis"!




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