@krisgesling just a quick add to my comment just above. You might think it contradicts what I advised at May 03 12:04 :point_up:. For your first project I had the impression that you wanted to use colours to represent the differences between several different variables at the same time. Blue for countries with the largest amount of males, yellow for intermediate, etc. I might have it wrong.
Still, the fact is that the colour variation make more sense specially if what you want to represent is a gradient. A nice example is your most recent map: a colour gradient representing ranges of number of participants.
What your map is probably not showing is your story. If what you want to represent is the amount of minorities that participated in the survey, I would suggest that as the main colouring aspect of your map. The rest of the information (example how many respondents per country) is possibly marginal.
In my opinion, your story would be more interesting if you not only tell about the proportion of minorities claiming to filling in the questionnaire: it would be great if you can add information about their coding aspirations, resources they use, or perhaps salary expectations.
My personal opinion is that highlighting minorities by excluding majorities is as unfair as the opposite: I would suggest to prepare maps for female, male, or non-(fe)-male alike. An impartial view allows for discussion and observations.
Hope this helps!
@krisgesling if you don't want to use the "Others" label then try an acronym and in some corner of the map try a legend explaining what means?
Your final work looks nicer! I don't still feel that the pie is adding info though...
I can tell you what I see:
Thinking... suppose that you have some data pre-digested as above. Could that work to guide user's information discovery even though it is a bit prescriptive? Let's say as a user I select to check the Affirmation 2: the map could highlight all countries that show over 80% and those which don't. Those countries that are exceptional should be highlighted apart...
The Affirmation 4 or 5 can also allows for highlighting (or opacity...). Etc.
@krisgesling I am just giving you ideas, please be free to select your way according to your interests and possibilities. No pressure! :)
Obs: a legend should be introduced at some point for sure...
And the borders between countries... I hope you can find a solution...
DSR (DataScience Room) is an effort to gather campers of all levels and specializations willing to engage in discussion, collaboration and practice of data-related projects, with preference for using FCC data.
Tentative DSR site: http://evaristoc.github.io/FreeCodeCamp_DSR/
This week we have been working on the FCC Survey. See some work at the room or visit the issue page of the FCC Survey Repo. We are working on providing a clean Dataset for further analyses and visualizations. We are inviting EVERYONE to participate. Check advances here: FreeCodeCamp/2016-new-coder-survey#26
erictleung, bradd123, tufonas, Dawny33, psuedoCode, zcassini, Mashadim, QuincyLarson, sudeepnarkar, shian48263, theflametrooper, codengraphix, emilaasa, Evaderei, nitisha8086, jboxman, krisgesling, CaseyJunio, zydecat, abhisekp, evaristoc, profoundhub, joeybuczek, kymanikd, twolfe2, ozkoc, SamAI-Software, AdventureBear
(For a longer list check:
'ethnic', 'excel', 'graph', 'minority', 'jscript', 'pies', 'viz', 'dissertation', 'podcast', 'survey'
(For a word cloud check:
@AyanGhatak I can answer that question: no sticking. Why? It is also very important for the project that campers show their abilities in manipulating and presenting data as much as using specific tools.
Better d3 as it is part of the FCC program as well as the possibilities that d3.js offers for customisation but I would suggest not prescription as d3 is not easy.
The only issue is project consolidation: if we all start working different technologies that will affect the ways we consolidate the final work which should consist in a small website of visualizations (@QuincyLarson idea). However we could try to deal with that later...
@AyanGhatak let us know about your project!
I think we need to prepare something that support this interesting article:
I think the author did a pretty good job in terms of showcasing some common dev related podcasts and some basic tool comparisons. In terms of data viz though, what were you thinking in terms of a project? -
maybe analyzing other data-points to infer lack of adoption of podcasts?
Less of a visualization but more of a keyword aggregator of podcasts (which I suppose one could create linkage and visualization)?
Maybe consume/use some API for podcasts (though it seems it's pretty limited based on cursory google search something like what this person-was looking to do) -
But maybe something like top (n) code related podcasts with matching keyword within episodes to maybe teaching concepts or frameworks/technologies within
fcc 'stable (e.g., 'react','node', 'mongo', 'callback(s)'? - So, chart plus access ability to go to site and grab podcast?
Don't know if any of this is close to the initial/spark idea - but what are your thoughts?
@profoundhub I can tell you anecdotally that we average around 2,000 new registered campers every day.
@qmikew1 I don't think there's a moral problem with promoting ad-supported podcasts. Ads (sponsors) are one of the only avenues available to podcasters.
@Areef1991 welcome to the data science room.
profoundhub sends brownie points to @quincylarson :sparkles: :thumbsup: :sparkles: