Original goal : Plot predicted MTA delays based off GTFS live-feed data using a neighborhood layer choropleth.
Adjusted goal : Prototype a system to show live and static MTA data by neighborhood.
Important data created : For every canon neighborhood in NYC, I’ve attached the # of train lines that run through!
Whats here :
Where MTA trains currently are, live! | (Using a sample of live-data)
Neighorhood MTA Route Density | Map showing how many trains are available per neighborhood
Tables | The information I wanted to bring to the world (For real estate or urban development purposes)
Complications :
Scheduled service changes, and line changes make monitoring live-data an incredibly difficult task to automate
Choropleth mapping is not at a sufficient technological state to easily support data streaming
Zillow GEOjson for neighborhoods
MTA line GEOjson for MTA lines
MTA Static-GTFS feed for train station information
MTA Live-GTFS fed for current train whereabouts
Can be found within each .py script on the github. (Data handling for the Live-Choropleth can be found in plotLiveChoro.py)
There are no errors in the making of my data, to my knowledge.
Copius use of pandas / JSON / GEOjson
Interested in how many MTA lines pass through each neighborhood? Well here it is, in convenient, easy to read CSV.
(https://github.com/parastyle/DATA608/blob/master/DATA608/Final/MTA_lines_pass_through.csv)