Juan Convers

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When I was a kid, I used to play tennis on the rusty concrete court around the corner from our place. My friends and I spent countless hours there, which is why the sport has always stayed close to my heart—and remains the only one I truly enjoy watching.

This week, I’ve been following the Australian Open, which is still ongoing, and there have already been some great matches. That got me thinking about how dominance in tennis is measured over time. Many people agree that Djokovic sits at the top when it comes to total Grand Slam titles, but it made me curious about how those wins are distributed across each major. The table below summarizes that breakdown.

What stands out from the table is the contrast in geographic dominance between the two ATP and WTA tours. The women’s records are overwhelmingly held by American players across all four Grand Slams, while the men’s side is largely defined by European dominance.

After a couple of days of competition in the 2016 Rio Summer Olympics, the medals table starts to look similar to London 2012. This is the current table

And this is how the table looked at the end of the London competition.

Clearly the US and China are dominating on this sport event.

When I was at school I learned the blood type 0+ was the most common one and AB- the rarest one. Wikipedia has a good article about this information with a breakdown by country.

O+ and A+ are the most common ones and AB- is the least common:.

Last Thursday the Eurostats Office published the inflation data for January 2016. Even if those numbers are definitively better than the hyperinflation happening in other regions of the world (cough ... Venezuela), there is always the risk on deflation:

Now it's remarkable how the highest rate in Europe was Norway, a pretty expensive country already. I'm sorry for my Norwegian friends.

It is hard to assess what are the most popular programming languages because there are multiple ways to measure them but none of the are perfect (ie. Repositories, lines of code, occurrences in job offers, etc). For example if work with embedded systems C is very popular, but if you work on the web the history is very different.

One interesting measurement of popularity of a language are the questions related to the language. Stack Overflow features questions and answers on a wide range of programming languages and compiles a list of the most popular tags with total, today and this week breakdown.

This data is a nice proxy on how popular are the different programming languages.

The US Bureau of Labor Statistics published the unemployment figures for January, and the rate is low: 4.9%. It’s one of the lowest unemployment rates since the financial crisis of 2008. The rate is half of what it was at the peak in October 2009:

Even though this is very good news for the American people, the increase in wages is still sluggish. In the last quarter of 2015, the rate was 1.9%. It was around 3% before the crisis hit hard.

If I were American, I would ask these questions to the presidential candidates.

I wanted to wrap up this series of posts I have been writing about the people living in Berlin, using data provided by the Statistical Office of Berlin-Brandenburg, with a final post about EU foreign citizens living in the city.

A couple of days ago I was discussing how Poland, Italy and Bulgaria were the EU countries with the highest number of expats living in Berlin, but the data also contains a very interesting breakdown per district (Bezirk).

I put the totals in a density map:

I also used the specific countries data to create a matrix heatmap using the tutorial on how to create a heatmap with jQuery and Tables. See the resulting table below:

There are a couple of interesting conclusions from the data: Polish are definitely the highest minority from the EU countries and this can be observed in every district. Mitte is definitely the most popular district for most of the EU citizens and finally Marzahn-Hellersdorf is the least popular overall.