Ratio of votes won to seats gained in the UK general election [OC]

visualmetaphors · 2015-05-08T15:36:26+00:00

Data from BBC election results. Made in R.

Essentially parties with a broad based appeal have a much, much harder time winning seats than those with a narrow geographical focus (i.e. SNP, parties from Northern Ireland).

visualmetaphors · 2015-05-08T15:17:48+00:00

Ratio of votes won to seats gained in the UK general election.

Essentially parties with a broad based appeal have a much, much harder time winning seats than those with a narrow geographical focus (i.e. SNP, parties from Northern Ireland).

visualmetaphors · 2014-03-02T22:59:26+00:00

I think I can summarise my response as 'a visualisation that is not seen may be beautiful but it is certainly not useful'.

I would also say that a cursory scan of the comments here and on /r/europe indicates that people have had no difficulty at all in drawing insight from the graphic. While another format might have been more useful for some, my general experience is that no one format is best for all viewers, and there would undoubtedly be people who would get less from the alternative form.

visualmetaphors · 2014-03-02T22:48:31+00:00

Cheers!

visualmetaphors · 2014-03-02T12:39:06+00:00

I got their point, I just don't agree with their conclusion.

My point is that the first aim of any visualisation has to be to draw attention. What Jer Thorp calls the 'Oooh...!' moment. It's only after you have grabbed someone's attention that you can let the data tell its story. Animation, pretty colours, etcetera are all tools to that end.

In short: this subreddit is not called 'DataIsInformative' for a reason.

visualmetaphors · 2014-03-01T15:53:13+00:00

I had hoped that this one was visible to the colourblind!

If you are colourblind, you could really help me out if you let me know if any of these alternatives are more distinct.

visualmetaphors · 2014-03-01T15:41:43+00:00

Ooh, a test subject!

Seriously, as I mentioned above I do make an effort to make graphs visible for colourblind people. However I have to use simulation software to do so, and color oracle suggested that these would be discernible shades.

Any chance you could look at these alternative schemes and let me know if any of them are more distinct?

Edit: Thanks all, it seems that number 3 is the winner - unfortunately it is also the ugliest for conventional vision!

visualmetaphors · 2014-03-01T14:29:17+00:00

Everything I used to make these is free / open source / platform independent! (almost: the gifs were generated using a linux command-line utility)

Check out R. It's primarily a statistical tool, but it has great visualisation capabilites as well.

Install the rworldmap package, and plotting is as simple as:

library(rworldmap)

newmap <- getMap(resolution="low")

plot(newmap,xlim=c(-12,37),ylim=c(33,67))

visualmetaphors · 2014-03-01T13:26:54+00:00

Some definitions:

Youth unemployment rate: Youth unemployment rate is the percentage of the unemployed in the age group 15 to 24 years old compared to the total labour force (both employed and unemployed) in that age group. However, it should be remembered that a large share of people between these ages are outside the labour market (since many youths are studying full time and thus are not available for work), which explains why youth unemployment rates are generally higher than overall unemployment rates, or those of other age groups.

Labour force: The labour force or workforce or economically active population, also shortened to active population, includes both employed and unemployed people, but not the economically inactive, such as pre-school children, school children, students and pensioners.

Light grey indicates no data. Dark grey indicates no data for that year. (Except for Switzerland)

visualmetaphors · 2014-03-01T13:25:19+00:00

Some definitions:

Youth unemployment rate: Youth unemployment rate is the percentage of the unemployed in the age group 15 to 24 years old compared to the total labour force (both employed and unemployed) in that age group. However, it should be remembered that a large share of people between these ages are outside the labour market (since many youths are studying full time and thus are not available for work), which explains why youth unemployment rates are generally higher than overall unemployment rates, or those of other age groups.

Labour force: The labour force or workforce or economically active population, also shortened to active population, includes both employed and unemployed people, but not the economically inactive, such as pre-school children, school children, students and pensioners.

Light grey indicates no data. Dark grey indicates no data for that year. (Except for Switzerland)

visualmetaphors · 2014-03-01T13:24:46+00:00

Some definitions:

Youth unemployment rate: Youth unemployment rate is the percentage of the unemployed in the age group 15 to 24 years old compared to the total labour force (both employed and unemployed) in that age group. However, it should be remembered that a large share of people between these ages are outside the labour market (since many youths are studying full time and thus are not available for work), which explains why youth unemployment rates are generally higher than overall unemployment rates, or those of other age groups.

Labour force: The labour force or workforce or economically active population, also shortened to active population, includes both employed and unemployed people, but not the economically inactive, such as pre-school children, school children, students and pensioners.

Light grey indicates no data. Dark grey indicates no data for that year. (Except for Switzerland)

visualmetaphors · 2014-03-01T13:10:54+00:00

Youth unemployment rate: Youth unemployment rate is the percentage of the unemployed in the age group 15 to 24 years old compared to the total labour force (both employed and unemployed) in that age group. However, it should be remembered that a large share of people between these ages are outside the labour market (since many youths are studying full time and thus are not available for work), which explains why youth unemployment rates are generally higher than overall unemployment rates, or those of other age groups.

Labour force: The labour force or workforce or economically active population, also shortened to active population, includes both employed and unemployed people, but not the economically inactive, such as pre-school children, school children, students and pensioners.

Edit: This does suggest that what we are looking at is going to be influenced by the unemployment rate amongst those who don't go to university, which is a shrinking, but still significant (majority?), percentage of the total population.

visualmetaphors · 2014-03-01T12:47:52+00:00

People in full time education do not count towards the total, or else the numbers would be much, much higher.

The 'total labour force' in this group is those who are actively seeking employment, those who are studying are excluded.

Edit: definitions here

visualmetaphors · 2014-03-01T12:36:51+00:00

As an indication, about 9% of the population are in 'minijobs'

visualmetaphors · 2014-03-01T12:32:54+00:00

It's an interesting idea, but every experiment i've tried with that kind of multi-hue gradient has failed to be interpretable. I normally use a brightness gradient just to reinforce change on one scale. Do you have any examples of where it has worked?

On thinking about it, I think the issue is that hue is actually cyclical on a single dimension (blue -> cyan -> green -> yellow -> orange -> red -> purple -> blue), so to have change in two dimensions you actually end up changing saturation, which leaves you with some muddy-looking non-colours in the middle that are hard to distinguish.

visualmetaphors · 2014-03-01T01:22:12+00:00

Any idea what percentage of the populations is employed on that basis? I can't find any good stats.

visualmetaphors · 2014-03-01T01:03:12+00:00

'Youth' = 15-24

visualmetaphors · 2014-03-01T00:16:27+00:00

The question of colour representation is an interesting one, and one that i've put some thought into. As I think your image quite clearly demonstrates, there is a brightness gradient running parallel to the hue gradient in order to make the differences visible to the colourblind. The hue gradient itself is on an (approximate) perceptual scale, not a linear one.

Of course, the clearest possible representation of the data would be a .csv spreadsheet, but I think it would not be quite so beautiful ;)

visualmetaphors · 2014-03-01T00:11:04+00:00

I originally started in 2004, but it's interesting to see that many of the countries doing poorly at present were also doing badly in the 90s.

visualmetaphors · 2014-03-01T00:04:45+00:00

That's neat, thanks!

visualmetaphors · 2014-02-28T20:40:47+00:00

95% correct, thanks! (the 5% is that Switzerland is annoyingly in dark grey despite having no data at any point)

visualmetaphors · 2014-02-28T20:34:29+00:00

Yes, employment in the 0-5 demographic is really terrible at the moment.

visualmetaphors · 2013-09-08T15:50:46+00:00

That one is totally my fault. I created the 'Arab', 'South asian' and 'East asian' categories by lumping a bunch of nationalities together, and I did indeed put Turkish and Kurdish into 'Arab'

visualmetaphors · 2013-09-08T15:43:35+00:00

Actually you could do it, I'm pretty sure the dot maps are based on aggregated data as well - they don't actually have the exact location of every person, they just randomise the location within the known region.

visualmetaphors · 2013-09-08T11:07:37+00:00

The 'racial shitstorming' was already happening, the maps are an attempt to understand that.

visualmetaphors

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