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Daniel
@profoundhub
@bradd123 it really depends on what you want to do after you get that degree
evaristoc
@evaristoc
@krisgesling excellent point about the Others label. I would keep the map you have done but what about other representation? It can be a bit polemic one, but could you try another in which instead of representing the number of respondents, the colour would represent the proportion of minorities against total respondents? It is a pity we didn't happen to ask about race for example...
Brahma Reddy Chilakala
@bradd123
@profoundhub Yeah, I want to get a job in a data science startup. What is your opinion of that nanodegree?
evaristoc
@evaristoc

@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 additionally: the pie in the tooltip is not saying anything, I am afraid. Better to get rid of it, if you cannot work a better way to represent it... IMO
Kris Gesling
@krisgesling
@evaristoc @SamAI-Software have updated the map with suggestions made, and added a % bar for those who identify as an ethnic minority in their country - not sure it really works that well but figured it was worth a try.
As you say I previously had the map coloured as a ratio non-men: men however I think it misrepresents the data as countries who only have 2 campers can look like they're leading a progressive revolution. I don't think there's enough data for most countries to make the claims it would be trying to make, even if it looks like a more interesting story.
Ultimately I was working to address the question of gender breakdown per country for integration into a broader set of visualisations. I haven't thought of a nice way to do that using country fill so for me the pie graph or a stacked bar graph is the best solution.
Sam Aiken
@SamAI-Software
@krisgesling well done! Looks great! :+1:
However, there is still too much text in tooltip, so it's hard to digest
  • How about putting non-male&non-female into one word? May be abbreviation?
  • Also there is no need for "no response"
  • And just "ethnic minority" will look easier
Kris Gesling
@krisgesling
I hid the 'no response' where it was 0 but I find those stats interesting still. I could do the same for Trans*, genderqueer and agender but the lack of people choosing any of those options is also interesting. Maybe both will get cut if FCC use it but for me, I like them. Good point on the ethnic minority label. I still need to optimise the whole thing for mobile devices too...
evaristoc
@evaristoc

@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:

  1. The usual proportion is 80-85% males over the rest, particularly Asian-European countries
  2. That proportion seemed higher in South-America, Africa and some Asian countries; but lower in North American countries, China and some Oceanic countries (Australia, Philippines,...).
  3. Ethiopie is an interesting case...
  4. There were about xxx amount of countries where there was at least 1 person affirming to belong to non-male/female gender categories.
  5. If we exclude countries when no-one reported to belong to non-male/female gender categories, you can notice that that segment reached 1-2% of the total respondents, with some exceptional cases reaching 4-5%.
  6. The more respondents, the more likely that the data was better.

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...

evaristoc
@evaristoc
@Evaderei: How did you solve the issue with the twitter posts?
Daniel
@profoundhub
@bradd123 go for it, it should give you a good foundation and community of students and educators to lean on!
Victor
@Evaderei
@evaristoc I haven't
evaristoc
@evaristoc
Send me DM later with the code? I will try to find time to check it and discuss it with you... @Evaderei
Victor
@Evaderei
thanks @evaristoc it gets really frustrating and honestly makes me wanna call quits on the whole thing xD
CamperBot
@camperbot
evaderei sends brownie points to @evaristoc :sparkles: :thumbsup: :sparkles:
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Victor
@Evaderei
especially when i've spent hours upon hours alone on it
Daniel
@profoundhub
anyone here know how many students there are here, and where i can go to find out,... are the stats somewhere? I like to see how many new students are added to FCC in the last 30 days, for example.
evaristoc
@evaristoc

People

THE DSR WEEKLY DIGEST:

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.
Previous Digest
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


List of Week Contributors:

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


4 Popular Messages:


Some Links from Last Week (random selection):

(For a longer list check:
http://evaristoc.github.io/FreeCodeCamp_DSR/update
)


10 HOT KEYWORDS to find what it is going on recently in this channel:

'ethnic', 'excel', 'graph', 'minority', 'jscript', 'pies', 'viz', 'dissertation', 'podcast', 'survey'

(For a word cloud check:
http://evaristoc.github.io/FreeCodeCamp_DSR/update
)


evaristoc
@evaristoc
Above the fork by @SamAI-Software from @krisgesling work was reported. Here the link that @krisgesling is currently working on:
http://codepen.io/krisgesling/pen/GZwYKV?editors=0010
Sam Aiken
@SamAI-Software
We are inviting EVERYONE to participate. Check advances here: FreeCodeCamp/2016-new-coder-survey#26 :+1:
Ayan Ghatak
@AyanGhatak
@SamAI-Software Can I use FusionCharts(http://www.fusioncharts.com/) to make some interactive visualisation for the data. Or are we sticking to d3 only here?
Daniel
@profoundhub
@AyanGhatak fusioncharts looks really slick!
evaristoc
@evaristoc

@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!


People

I think we need to prepare something that support this interesting article:

https://medium.freecodecamp.com/the-best-podcasts-for-new-coders-and-the-best-tools-for-listening-to-them-df393b1c8dc#.2q4bgnx79

Serenity
@qmikew1
definitely agree with podcasts as being a nice tool (one of those in that article is my current fav) but it also seems sort of dicey to maybe indirectly promote podcasts that are, in fact, supported by advertising. It would have to be pretty generic in terms of info though... (but that's just my opinion)
evaristoc
@evaristoc
Good point... Let us know if you want to work on some viz for that... @qmikew1
Serenity
@qmikew1
will do -
Syed
@Areef1991
Hello world
CamperBot
@camperbot

welcome to FreeCodeCamp @Areef1991!

evaristoc
@evaristoc
@Areef1991 Welcome! Hope you will enjoy this room
evaristoc
@evaristoc
Sorry people for a note:
https://gitter.im/FreeCodeCamp/DataScience?at=572742d060e2f3e87366c1e8
d:481; p:365; r:186; l:263
Serenity
@qmikew1

@evaristoc Follow-Up on the podcast thing- I guess that would be under terms of use and maybe a non-endorsement blurb would probably be sufficient.

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? -

First thoughts

  1. maybe analyzing other data-points to infer lack of adoption of podcasts?

  2. Less of a visualization but more of a keyword aggregator of podcasts (which I suppose one could create linkage and visualization)?
    Ex:
    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?

Daniel
@profoundhub
Welcome @Areef1991
Quincy Larson
@QuincyLarson
@krisgesling The most interesting thing about the gender question imho is the proportion of females. This is the main focus of the larger discussion on diversity in technology fields - representation of women. So you might consider making a graphic that just shows the percentage of respondents that were female in each country. This means you only have to visualize one thing, and could use intensity of color.
Quincy Larson
@QuincyLarson

@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.

Serenity
@qmikew1
@QuincyLarson yeah, they do need to keep the podcasts going.... point taken
but meant it as an indirect support thing
(am just super cautious and slightly neurotic)
Quincy Larson
@QuincyLarson
@qmikew1 no worries. No harm in being cautious ;)
Daniel
@profoundhub
Thanks @QuincyLarson that's awesome, I check in every 4 - 5 hours, i love the community here!
CamperBot
@camperbot
:star2: 1131 | @quincylarson |http://www.freecodecamp.com/quincylarson
profoundhub sends brownie points to @quincylarson :sparkles: :thumbsup: :sparkles:
ITme2015
@ITme2015
Hi All!
evaristoc
@evaristoc
@qmikew1 are you going to take the project? It would be great!
Kris Gesling
@krisgesling
Alright I've changed it back to being colouring in by gender. I was concerned about countries with a small response rate being misrepresented but really for the one female respondent in Libya it would be pretty cool to have your country highlighted thanks to your work and they deserve to be represented too. Also added a global statistics bar so you can see the global proportion of genders.
http://codepen.io/krisgesling/full/GZwYKV/
Has anyone else started a visualisation or waiting on the data to get cleaned up?
evaristoc
@evaristoc

@krisgesling VERY good... I still have some doubts about the need of the pie in the tooltip, but it is becoming such a good presentation that I could easily ignore that aspect... :)

Well done!!!

@krisgesling to keep consistency: could you add some global data about percentage of the minorities?
evaristoc
@evaristoc

And what means "No response" in the global data? You are not adding tool tip information about those... I understand what you are at to but it is not intuitive... it should probably included but as a different statistics. For example:
total interviews: 14k something
complete responses: 13k something (less the no responses)

And then legend about global info.

I think the global info would be much better if you try pie? Could you try a test?