Edit 20191018: Following some comments (thank you!) I added a few more graphs, such as a few top10. I also cleaned the R code a bit and made the graphs a tad easier to read.
Two weeks ago, I took the Montreal subway with my SO and casually mentioned it would be nice to understand why the Joliette subway station has more foot traffic than the next one, PieIX. Is the part of the neighborhood served by the Joliette station denser? Would there be a correlation between the mean household income and foot traffic? Has the more aggressive gentrification around the Joliette station affected its achalandage?
Much to my surprise, instead of sharing my urbanistical enthusiasm, my SO readily disputed what I thought was an irrefutable fact: "PieIX has more foot traffic than Joliette, mainly because of the superior amount of bus lines departing from it" she told me.
Shaken to the core, I decided to prove to the world I was right and asked Société de Transport de Montréal (STM) for the foot traffic data of the Montreal subway.
Turns out I was wrong (PieIX is about twice as big as Joliette...) and individual observations are often untrue. Shocking right?!
Visualisations
STM kindly sent me daily values for each subway stations from 2001 to 2018. Armed with all this data, I decided to play a little with R and came up with some interesting graphs.
Behold this semiinteractive map of Montreal's subway! By clicking on a subway station, you'll be redirected to a graph of the station's foot traffic.
I also made a few graphs that include data from multiple stations. Some of them (like the Orange line) are quite crowded though:
Licences

The subway map displayed on this page, the original dataset and my modified dataset are licenced under CCO 1.0: they are in the public domain.

The R code I wrote is licensed under the GPLv3+. Feel free to reuse it if you get a more up to date dataset from the STM.