The following map uses data from the IMF Direction of Trade. IMF Trade Map body { font-family: sans-serif; margin: 20px; } #container { max-width: 800px; margin: auto; } #map { height: 700px; width: 100%; } #slider-container { margin-top: 20px; width: 159%; } input[type="range"] { width: 100%; } #slider-label { text-align: center; margin-top: 5px; font-size: 1.1em; } let allData = []; let periods = []; fetch('/data.

Use IMF API to automatically collect relevant data soures Process data as needed Create metrics to define majority import (in this case which ever of the three countries the share of the imports are from) Combine geojson file with data so that there is a proper geospatial file with the neceesary information Creating visuals of the dataset Start to finish process in one Jupyter Notebook GitHub Repository

Define metrics: Availability = Bike Paths (km)/ Roads (km) Quality = ( Seperated Bikepaths / All Bike Paths )*100 Utilize API to collect data from OpenStreetMap Acquire appropriate shapefiles from the city authorities Clean and process data Create data visualizations and report findings GitHub Repository