Shoutout to Philippe Vibien for creating “NYC Subway Stringlines”, one of my favorite (and certainly most used) data visualizations ever. Made possible by the M

Shoutout to Philippe Vibien for creating “NYC Subway Stringlines”, one of my favorite (and certainly most used) data visualizations ever. Made possible by the MTA’s GTFS RT feed. https://pvibien.com/stringline.htm https://pvibien.com/stringline.htm Note: If you’re checking this out around 6 PM EST, look at the E train to get an idea of what a bad night on the subway looks like. Each line on the graph represents a train with the Y axis as stations and the X axis representing time. You can follow the trip of the train and get an idea for how well the line is running based on the straightness of the line. If you see areas where the line is flat in the Y axis, you know that a train is being held at a station. Here’s an example where “stringlines” provide information that a countdown clock couldn’t convey: https://i.imgur.com/u5VGqH4.jpeg https://i.imgur.com/u5VGqH4.jpeg Because the “line” is not progressing past 5th Ave/53rd st, we know that that is where the issue is occurring. A countdown timer would simply either say static or start adding time, but you wouldn’t know how far the next train is from you. Here’s another example: https://i.imgur.com/mrvrbUt.jpeg https://i.imgur.com/mrvrbUt.jpeg What I can glean from this is that the E train is running with much lower frequency than it was an hour ago, so I should expect longer wait times. It’s truly a marvelous invention.