Inspiration
Visuals
Proposal
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param_config_file
- Capture the mongodb db name
- endpoints
- flask site port
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Geo coding data for (State,county)
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INSU_DATA / API Call 1 ("Insured","Un-insured","State","County" "Year", "lat","lon")
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POP_DATA / API Call 2 ("Population_Count","State","County","Year","lat","lon")
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INCO_DATA / API Call 3 ("Income","State","County","Year","lat","lon")
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DEATH_DATA / API Call 4 ("Death_count","State","County","Year","lat","lon")
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Database (MongoDB) (for each dataset) (refer to module 12-1)
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ETL routines to clean up and merge data for rendering into starter database
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Initialize database with api calls to feed the starter database
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Build a Python flask service layer to initialize the map rendering with dataset from mongoDB (refer to module 10-3 flask)
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Incorporate leaflets / plotly to enable user interaction with the data visualization
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Read data via api using python and imported it into MongoDB
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Imported data from flat files into json
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created indexes on mongo db for quicker access by state and county fips
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used python scripts to merge datasets about counties
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mongodb cannot accept numbers as key
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if you are using plotly the scripts go at the end so the javascript engine can see the DOM elements
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Just when you thought there is not enough charting engines.. there is MongoDB charts - https://www.mongodb.com/products/charts