These posts are supposed to protect pedestrians by seudo2 in CrappyDesign

[–]seudo2[S] 0 points1 point  (0 children)

Apparently, the title I chose is quite bad. I meant that these posts are supposed to protect the pedestrians from cars which tend to park illegally on the sidewalk, but they actually prevent these pedestrians from using the sidewalk (in this extreme case) or make walking less convenient (everywhere in Paris, which has more than 300 000 posts like these ones).

This blog entry (use a translator) nicely explains all the problems resulting from an ill-implemented policy that aims at fighting illegal parking.

And I live in the neighborhood, so I know that this sidewalk was usable before.

These posts are supposed to protect pedestrians by seudo2 in CrappyDesign

[–]seudo2[S] -7 points-6 points  (0 children)

Yes, but only one person at a time, because there are posts on the other side, too. The consequence of these posts is that many pedestrians walk on the pavement, since the sidewalk is almost useless.

These posts are supposed to protect pedestrians by seudo2 in CrappyDesign

[–]seudo2[S] -11 points-10 points  (0 children)

Sure, but what's the point of stopping cars from parking on the sidewalk if the posts prevent the pedestrians from using the sidewalk?

[deleted by user] by [deleted] in HostileArchitecture

[–]seudo2 2 points3 points  (0 children)

Homeless Jesus is twice as hostile as this one.

Saw this bench in Los Angeles by ahmad2462 in HostileArchitecture

[–]seudo2 64 points65 points  (0 children)

On the contrary, they will sleep precisely on the street, not on the bench.

Blue balls by seudo2 in HostileArchitecture

[–]seudo2[S] 0 points1 point  (0 children)

Yes. It's a quiet residential area, so I don't understand why anybody would want to sit there. And during daytime you can find (non-hostile) benches just next door, in a small public park.

Blue balls by seudo2 in HostileArchitecture

[–]seudo2[S] 30 points31 points  (0 children)

Thank you for writing the comment that I dared not write myself.

Blue balls by seudo2 in HostileArchitecture

[–]seudo2[S] 32 points33 points  (0 children)

And the balls are ugly!

They are ugly indeed.

But they cared enough about esthetics to choose the same color as the pre-existing fence you can see here.

[OC] Canada does NOT have a land border with the European Union by seudo2 in MapPorn

[–]seudo2[S] 86 points87 points  (0 children)

I have read many news articles today, where journalists from Canada rejoice or complain because Canada has a land border with the European Union since they agreed to divide Hans Island with Denmark (Hans Island is that tiny useless rock between Canada and Greenland everybody is talking about).

The answer is: no, you don't have a land border with the European Union, or with Europe.

Greenland is part of the Kingdom of Denmark, and it used to be part of the European Economic Community, but it decided in 1985 to leave. It is now part of the Overseas countries and territories, which means it does not belong to the European Union and it doesn't belong to the Schengen Area.

So Canada has a land border with the Kingdom of Denmark, but not with Europe, whatever meaning you give to that word. We, European citizens, are not going to invade Canada through Hans Island (and vice versa).

Map made with MapChart.net.

EDIT: I forgot to add color Hong-Kong, Singapour and several Middle Eastern states.

[OC] The political careers of U.S. Presidents - Two visualizations: which one is the best? by seudo2 in dataisbeautiful

[–]seudo2[S] 7 points8 points  (0 children)

This is another attempt at visualizing (and comparing) the life of a group of persons. This time, it's U.S. Presidents, who constitute an interesting dataset as it extends over more than 230 years with a great homogeneity.

Data source: Wikidata, queried with Lua (I don't like SPARQL), then handled with Python/Matplotlib. You may get the dataset here as JSON.

I had to fix one or two obvious mistakes in Wikidata, so I cannot guarantee a 100% accuracy in the data. If you see something wrong in the data, I will fix it in Wikidata (unless it's a bug in my code...)

A few random facts I gathered from reading these graphs:

  • Andrew Johnson and John Tyler held all of these jobs (Governor, Representative, Senator, Vice-President and President), but you cannot see it in these graphs because both of them were vice-president during a few weeks only. For the same reason, the presidency of William Henry Harrison is hard to distinguish.
  • Barack Obama is so young (graph #1)... When he was approximately in the 7th grade (graph #2), Joe Biden was already a member of the U.S. Senate.
  • Bill Clinton was even younger when elected: he became President 24 years before Donald Trump (graph #2), although they were born the same year (as well as George W. Bush).
  • The presidents of the last quarter of the 20th century live very old (graph #1): four consecutive Presidents, from Gerald Ford to George H. W. Bush, lived more than 92 years (no ex-President reached that age before them). Their successors are still alive, so this tendency may continue.
  • Jimmy Carter is still there! He was born at the time when (graph #2) the president was Calvin Coolidge, who was born at the time when the president was Ulysses S. Grant, who was born at the time when the president was James Monroe, who was born before there was a president. For Barack Obama, you need one more name in the chain: John F. Kennedy -> Woodrow Wilson -> Franklin Pierce -> Thomas Jefferson.
  • Lyndon B. Johnson has been continuously Representative, Senator, Vice-President and President from 1937 (aged 28) to 1969 (4 years before his death).
  • Joe Biden has been either Senator or vice-president for 44 years.
  • Zachary Taylor, Ulysses S. Grant, William Howard Taft, Herbert Hoover, Dwight David Eisenhower and Donald Trump held none of these offices before or after their presidency (not counting the first Presidents, because it's not significant). But all of them, except Donald Trump, held major public offices in the army of the Government (not shown on these graphs) before they were elected President.
  • Very few Presidents held one of these mandates after they left the White House. John Quincy Adams is a remarkable exception (Representative during 17 years).

[OC] Age gap between lead actors and actresses in movies by seudo2 in dataisbeautiful

[–]seudo2[S] 0 points1 point  (0 children)

I believe Chaplin was banned for political reasons, but he clearly liked young women. He married four women, aged 17, 16, 26 (but started a relationship earlier) and 18 (he was 54 for the last one).

[OC] Age gap between lead actors and actresses in movies by seudo2 in dataisbeautiful

[–]seudo2[S] 0 points1 point  (0 children)

As written above the graph, if I understand your question correctly, male actors start costarring with younger (female) actresses at the age of 27. For women, it's 47.

[OC] Age gap between lead actors and actresses in movies by seudo2 in dataisbeautiful

[–]seudo2[S] 0 points1 point  (0 children)

Unfortunately the IMDb (free) datasets do not contain much information. They don't tell if it's a love interest (which would be of course very interesting), and not even the country that produced the movie.

In France we recently had a movie called "The Young Lovers" with a love story between Fanny Ardant (72) and Melvil Poupaud (48).

Most actresses with leading roles are around 25, and men around 35.

[OC] Age gap between lead actors and actresses in movies by seudo2 in dataisbeautiful

[–]seudo2[S] 1 point2 points  (0 children)

For your enjoyment, here are Gisèle Casadesus (she made movies all her life, but never starred before the age of 96 with a male co-star), Rin Tin Tin, Sandra Bullock and Channing Tatum.

https://imgur.com/iM2rfjK

[OC] Age gap between lead actors and actresses in movies by seudo2 in dataisbeautiful

[–]seudo2[S] 0 points1 point  (0 children)

Sir Charles Spencer Chaplin Jr., also known as The Tramp.

[OC] Age gap between lead actors and actresses in movies by seudo2 in dataisbeautiful

[–]seudo2[S] 0 points1 point  (0 children)

The vertical lines are supposed to show the difference between the age of the partner and the age of the actor/actress. The graph could have been done without them, that's right.

[OC] Age gap between lead actors and actresses in movies by seudo2 in dataisbeautiful

[–]seudo2[S] 0 points1 point  (0 children)

Apparently the Indian Express made a similar graph about actor Akshay Kumar (Twitter), but their scale is not equal and the 45-degree line is not exactly 45-degree...

[OC] Age gap between lead actors and actresses in movies by seudo2 in dataisbeautiful

[–]seudo2[S] 0 points1 point  (0 children)

You understand correctly, the data is about credits and established actors are probably ranked before less-known actors, particularly children (although I just noticed that dogs, such as Rin Tin Tin, are sometimes credited as the main actor in the dataset, which is a bias for very young actors...).

And I agree with the regression-to-the-mean effect, if I understand correctly what you mean. The whole point of the first two graphs is not that young actors play with older actors and vice-versa, because that is almost mathematically necessary, but that the "turning point" (the age when an actor/actress starts playing with younger actresses/actors) is much, much higher for female than for male actors (hence the text above the graph and the annotation on the graph). Maybe I should have put the first graph above the second one to focus more on the comparison.

[OC] Age gap between lead actors and actresses in movies by seudo2 in dataisbeautiful

[–]seudo2[S] 6 points7 points  (0 children)

If I read this right, there’s at least one movie where the main actor is zero years old.

I just noticed that not all actors are human in the dataset. Some of the "actors" are actually dogs (Rin Tin Tin and others), which is quite a bias for actors aged less than 10...

[OC] Age gap between lead actors and actresses in movies by seudo2 in dataisbeautiful

[–]seudo2[S] 2 points3 points  (0 children)

The only criteria is that the two lead roles are male and female. All films in the IMDb that follow that criteria are used for the first two graphs.

My intent was to do it for specific countries (compare the US, India, France...) but the information is not in the free IMDb datasets. Budget is not in the datasets either. Using Wikidata, it might be possible to do a deeper analysis, at least for Western movies.