Uses the Quandl API to get housing data for all of New York City. Creates a Redis store full of NYC Housing Data. Uses a Flask app to creates a RESTful API that can be used to get relevant statistics on dataset and make visualisations.
Note: First make sure you have the following Python libraries installed.
Run:
pip install Quandl requests pandas pymongo
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Create file config which holds Quandl API key
config.py
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Put the API key from Quandl into config.py
echo apiKey = "YOUR_API_KEY" > config.py
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Populate a local Mongo store
python get_data_from_quandl.py
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Query the store, to get gentrification data for a particular interval:
(3,6,12,24)
python query_mongo.py <interval>
- Use a visualization lib [vega, Seaborn, folium]
- Write query python scripts and tie together w/ a shell script.