Analyzing MP data

I made some charts that I think are interesting ways to visualize mp tick data:

https://markdaily.github.io/

I'd love feedback on these, or suggestions for other things to analyze. 

Note: I obtained this information for my personal interest by scraping the site. I did what I could not to make excessive requests, have no interest in using it as my own. I'd love to hear if anyone thinks this is inappropriate. My goal was only to add value to information that's already available. :)

If you like analyzing data, how about the number of climbers by age? 

Cool idea. Rather than just "average tick by x", how about 3D data to show the actual histograms?

Very cool. Does the heat map have a scale associated with it? It looks saturated at major climbing areas, i.e. the same shade of red in the southeast as the Colorado front range - is the amount of ticks per area actually equal both places?

I love stuff like this! very cool! What's next? I really like the heat map!

Thx. Heat map is too cool

Thanks for the input. Added numbers of users by age, gender by state. (Hint: move to Iowa or Louisiana if you want good odds on a climbing girlfriend...)

Very cool. Thanks for putting in the time to do this. How about graphs showing the following?

1. total lifetime ticks

2. average ticks per month or per year

3. type of ticks (trad/sport/TR) 

4. type of route (rock/boulder/ice/alpine/snow/mixed)

For each of the above, could try using age, gender, state, etc., on horizontal axis.

Thanks!

You have to question to the statistical significance of the data.  Is the sampling pool statistically valid?  For example, does North Dakota really have an average of the hardest climbers in the country?  Lots (most?) of climbers on MP don't put in tick lists.  So while this is fun to look at I don't think it is necessarily accurate.  

I would also be interested in seeing a survey to determine likelihood to record a tick after completing a climb across different statistical groups; that seems like an important control before interpreting data.

Can you make the data you scraped available?

amarius wrote:

Fair point, but... I actually track RRG ticks in both places. I like having a "master" tick list for all my climbs, so I put them on MP as well.

Since ticks are self-reported there's absolutely massive selection bias inherent in the data. I would treat it as just for fun and not try to draw any conclusions from it.

Super cool charts and map!

I think the MP blog did something like this previously, but only showed things like top 10.  Cool to see the whole picture.