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Write a Python script to parse, clean, and store the census collection data from 2010 into the database.

Cleaning steps we need to take include:

• percentages that are not in the range [0, 1]

• data points that are not tracts (such as counties, etc)

We want to be able to store each data point as an object under a Mongo collection so that we can access it later. Create a Model for the Collection, and then do .save() to save btw.

Each data pt should have: Date (as mongo datetime obj), tractId, 2000 response rate, 2010 response rate

Sample data

Expand the maps component to have a layer of color depending on census response rates (or just mock data for now)

Part of #1

Before the designs are completed, we need to create a basic map that has tracts.

Still something we have to figure out is how much the MapBox API will provide for us (we can upload data into their platform and they will render it for us) and how much data we must provide ourselfs (mostly predictive data, especially during the census collection period).

Assume that within the db, each data point has: Date (as mongo datetime obj), tractId, 2000 response rate, 2010 response rate