How people run a 7,323 km marathon

[palrogg]

Top marathon runners run at the amazing speed of 21 km/h. But how are the other runners doing and what has their age to do with their performance? I wanted to plot their age and speed to figure out. Ages range from 19 to 61 years old.

Story issue checklist

My pitch was (use the number): NaN

• My pitch has been approved (see PITCHING.md)
• My story issue links to my pitch issue
• I have included an update of my visualization/story in a comment
• I have received two comments of peer feedback
• I have received editorial feedback

[palrogg]

Summary of the critiques:

• There is many overlapping points => add opacity
• For small multiples, keep the same axis limits
• This is speed, not time. Make more obvious that the bigger is the better

[palrogg]

Reworked visual:

[palrogg]

Checklist moved to original post

[jsoma]

I'm only in here to tag things at the moment, but I have to say that NaN made me laugh out loud. I also went ahead and checked some boxes for you.

[snajmabadi]

@palrogg -- These graphics are great! I particularly like the first two small multiple graphs ("escaladelite hommes" and "escaladelite femmes") as there seems to be more of a trend (older runners are slightly slower). I might consider adding small annotations on a few of the graphs, to point out the oldest/youngest/fastest runners, and maybe might change some of the headlines from "Hommes I"/"Femmes II"/etc. to say something like "Femmes, age 41-50," just to make it a little more clear to the viewer.

[jsoma]

I would probably add more opacity, those bars are still looking pretty solid :)

Labeling: In the spirit of Don't Repeat Yourself, I would label "Hommes" large up top on the left and "Femmes" up top on the right - then maybe even pull I, II and III out to the left-hand side? That way you can improve your data-ink ratio a bit!

Axes: Looking at Femmes II, the bottom is just.. so solid. I'd imagine it would be spread out a little more - how about trying from an axis of 0? I worry some data is getting cut off, but it also might be a little more fun to look at.

Annotations: It wasn't until I read @snajmabadi's comment that I realized that I II and III were ages! Since you're already displaying age based on position on the X axis, you could just put them all into one chart. That + opacity change and we'll probably be able to see some patterns. I agree about marking some outliers or the like, too.

Story: I'd push for there to be a message coming out of this chart - I look at it, spend some time with it and understand it, but you need some sort of hook in order to get people interested. A lot of times it's finding one person who is interesting (like the scrabble guy or the basketball guy) but in this case I think a general "men run like this, women run like this" and "young people run like this, old people run like this" should be good enough.

[oargueso]

I agree with @snajmabadi and Soma: a short explanation of the categories would be helpful for people who are not familiar with marathon running. Since I am not, I would also be grateful to have some context: is a 10 km/h a good pace for a 40-50 year old woman? Also, do you have information about the Course de l'Escalade? From its name it seems to me that it is somehow a hiking marathon? How does it compare to any other marathons? As said, a little bit of context. The graph is great and I do not know much about running, but I now want to read more about it!

[palrogg]

Thank you so much for your feedback!
@snajmabadi: very good point, I started to add annotations and it gets much more interesting! I also changed the "Femmes I, II, III" labels in a new graph which I'll have to do again, because I realized the file named "2015" contained the data of the previous year...

@jsoma:

• Labels: Right, it'll look much better (and more logical) with only big “men” and “women” labels on top. I always feel uncomfortable with men/women comparison in sports...
• Axes: I feel bad about this data I cut out. The worst is maybe, actually, that there's a “Femmes IV” and a “Hommes IV” category.
• Ages: True, I'll group them in one graph, this makes more sense.
• Story: Very good point, I'm still working on that. To be honest, I spent much too little time studying the data. It was a loss of time not to spend more time on it.

@oargueso: True, I have to provide this explanation. The truth is I didn't understand anything about these categories and the graph was an attempt to catch it. In fact, the “Escalade” is a historic battle which occurred in 1602: french troops climbed the walls of Geneva to take it! Now, many runners of the marathon are top-level professionals, I think most of them are Kenyan distance runners, I promise I'll write something about it. (Public domain image, description here)

[jsoma]

Saw this, thought of your graphic: https://www.reddit.com/r/dataisbeautiful/comments/4vcxd0/almost_all_men_are_stronger_than_almost_all_women/ (originally posted in the pitch)

[palrogg]

Very interesting! I should visit r/dataisbeautiful everyday.
Now that I use the right data, the winner of last year's race is 33 years old! Here's the new, annotated graph (I'm still working on the small multiples):

[palrogg]

The second graph is still in progress (Illustrator just crashed, I think it needs to rest):

[M0nica]

@palrogg How are runners classified as elite versus regular? Is this something that you computer or is this dictated by an orgnanization? Also, I was wondering what do the 4 colors in the bottom two graphs signify?

[jsoma]

Pull request #56 merged