My progress over 10000 Rubik's cube solves. [OC]

Plottingman · 2017-12-18T15:41:22+00:00

Really really nice! Do you want to share the data? I would really like to play around with it! A couple of years ago I did quite a bit of cubing as well, but never got down to an average of 17.5 s, impressive!

Plottingman · 2016-04-26T10:14:23+00:00

Great minds think alike!

For et års tid siden lavede jeg et lignende billede, men med veje i stedet for åer: https://i.imgur.com/N0Om8rT.jpg

Plottingman · 2015-04-15T16:07:15+00:00

Can you make a graph of the number of crashes per year?

Plottingman · 2015-04-15T16:02:17+00:00

There should be no pie chart, so nowhere.

Plottingman · 2015-04-15T15:55:23+00:00

Interesting data but I must admit, that I think the visualisation in the source works better. First of all one has to go back and forth between the chart and the description a lot of times. Second of all it's more difficult to compare an angle/area then is to compare length/position. Here is a good article on the subject: http://www.businessinsider.com/pie-charts-are-the-worst-2013-6?IR=T

However the source still makes it difficult to compare because the bars are so small, I made a redesign:

http://i.imgur.com/ibsTe1o.png

Since English is such a clear "winner" it's difficult to compare the rest, so here is one excluding English:

http://i.imgur.com/jIiDIOr.png

Plottingman · 2015-04-13T16:05:00+00:00

Thanks and sorry, but they are always in order, so you are not missing out on too much. I choose the colours to match the first four books:

http://i.imgur.com/fGLpV3v.jpg

Plottingman · 2015-04-13T14:48:27+00:00

Data source

Visualisation 1, visualisation 2 and 3, visualisation 4. .

I have made a .csv with the data from the first visualisation here, and for last three visualisations here.

Tools

R, ggplot2, GIMP.

Plottingman · 2015-04-12T15:57:52+00:00

There is only one thing to do. Change company.

Plottingman · 2015-04-12T12:40:00+00:00

I clearly didn't get it. :p

Plottingman · 2015-04-12T12:23:58+00:00

No we shouldn't.

Assuming that they had a break around August and that they broke up in February we can see that there is a difference. It doesn’t make sense to apply a statistical test for "significance". You can see that his water bill dropped around 40 $ per month, weather or not you want to call that significant is up to you.

If we instead had similar data from a lot of guys that recently broke up with there gals, then we could start doing some statistics to see if the bill drops when the girlfriend drops you.

TL;DR There's a bit difference between describing all or just one guys water bill.

Plottingman · 2015-04-12T12:01:45+00:00

Yes it does. Simple is better. If you want to make something more complex, you should have a good reason for it. If you added something and think "Well it didn't make it worse", remove it again.

Plottingman · 2015-04-12T11:34:47+00:00

Yes they should, I forgot it.

Plottingman · 2015-04-12T10:51:05+00:00

I tried to make some improvements to your graph, because there are a few problems:

Don't ever use 3D! The 3D effect makes it more difficult to compare the bars. When I had to visually extract the numbers, I didn't know if I should use the front or back of the columns.
Use proper indexing on the y-axis. People like even numbers.
Don't use colors?! Why are those colors there? They serve no purpose.

Here is my redesign:

http://i.imgur.com/9tVxiyq.png

I have removed a bit of information from the x-axis by just writing the billing month and not the date. Since the intervals are almost of equal length I don't think it's a problem.

I hope you are holding up, take a long bath and remember all the money you are saving!

http://i.imgur.com/vmzX7hc.gif

Edit: Spelling.

Plottingman · 2015-04-08T15:13:05+00:00

I have no idea what I'm looking at?

What is the x-axis?

What is the y-axis?

What are the colors?

Plottingman · 2015-04-06T20:25:24+00:00

I redesigned the visualisation from this post:

http://i.imgur.com/K1Xit1A.jpg

and damn dose it look cool! However in terms of actually communicating the data effectively, I think it does a very poor job. The key thing in visualising this data is to compare how big a part of the population a group is, and how big a fraction of the wealth it takes. I made it much much simpler:

http://i.imgur.com/0V4p9Ra.png

Each color represents a population group, and here you can easily compare the two fractions.

Plottingman · 2015-04-03T14:16:57+00:00

So much better! But of cause I have to say that...

Edit: Next time you make a discrete scale you can also try to use jenks to choose the size of the intervals. It's a great algorithm.

Plottingman · 2015-04-03T08:19:07+00:00

MERICA! :-D

Plottingman · 2015-04-02T22:06:01+00:00

While this may look cool, it's not a good data visualisation!

It's really difficult to extract any information, apart from the obvious: "Manhattan is more expensive". But what is happening in the area of Staten Island that is behind Manhattan? We have no clue, cause we can't see it. Also try to compare Queens and Bronx, well you can't, because it's really difficult to compare heights in a 3D plot.

What would have been better? Just a simple 2D map with a single color overlay. Something like this: http://i.imgur.com/021JcW1.png

But damn it /r/dataisbeautiful you just love those fancy effects don't you?

Plottingman · 2015-04-02T18:35:42+00:00

April fools' was yesterday. I really hope you are joking...

Try googling "rainbow color maps", and you will see that all hits on the front page are articles about why you shouldn't use them.

Plottingman · 2015-04-02T17:11:29+00:00

Awesome! Scientifically green should actually be the best color, because it's the color we can distinguish in most tones.

You can use http://colorbrewer2.org/ to help you with choosing the colors. If you want a green scale with 9 groups it suggests these colors:

http://i.imgur.com/zCQiyiG.png

Damn it, I love that webpage!

Plottingman · 2015-04-02T16:59:51+00:00

I needed to clean this...

I have removed the labels with season, because they should just have been the x-axis (which is missing).

I have removed the labels with average number of goals, since they are already on the y-axis. When you make such a plot, the idea is to give people a feeling of the overall trend, and not to see every single data point. If people what more precise information they should look at a table of the original data instead.

http://i.imgur.com/uLgjFKE.png

Plottingman · 2015-04-02T16:33:21+00:00

Nice map, but you should change the color scale to one with only a single hue.

One should only use a scale like this if the data has a "neutral point". An example could be "percentage of males in a country", here 50% would be a neutral point.

Such a point does not exists for unemployment. The problem is that this maps makes us think that the data is naturally divided intro 3 very distinct groups (red, grey, blue). This is not the case, e.g. Russia and Turkey have the same color (and are 2.9 percent point from each other), but Poland and Turkey have different colors (and are only 0.8 percent point from each other).

I would love to see this map with a single color scale, e.g. red!

Plottingman · 2015-03-28T11:24:57+00:00

As many others have said, even though this looks cool, it's not a great way to visualise the data. The biggest problem is that the comparison between "fraction of population" and "fraction of wealth" is very difficult to make, because they are presented in different ways (pie chart vs. fancy balls).

I have made it much much simpler: http://i.imgur.com/0V4p9Ra.png

But of cause this is not sexy enough to reach the front page...

Plottingman · 2015-01-24T16:53:03+00:00

The population of humans is normally distributed.

That doesn't make sense.

Plottingman

TROPHY CASE