Hello! I am Lars E. Schonander, a writer for MediaFile and a blogger on international affairs, tech, and general wonkery. Happy Monday! Here is my weekly newsletter with a weekly analysis with interesting data, along with links related to things I found particularly interesting that week. Any Questions? Send me a message or just respond to this email!
The Weekly Data:
This week, I found a dataset on Anthony Bourdain and where he traveled for his various travel slash food shows.
To start, I wanted to plot out a season of his travels, but not by using a map. Via the usage of geom_path
, it was very simple to plot out the x and y coordinates of where Anthony Bourdain traveled for the first season. In this case, he started in Paris, but ended for the final episode all the way in the DRC. Important to note, that this was not the season where the Hanoi trip lead to Anthony eating with former President Obama.
To change things up, I realized the (country | city) model creates a hub and spoke method of visualizing where Anthony Bourdain traveled to. I then converted the data into pairs of (country | city), with weights given for how many times Anthony Bourdain traveled to a particular country, and then the associate city. As seen below, while unlabeled, several patterns show up. For starters, he doesn’t spend to much time in a single country, with the exception of the massive blob on the left, which represents the United States.
Unfortunately, this graph does not have weights between the links, so it only counts how many distinct cities did Anthony travel to per country.
Finally, because of the size of the United States blob, I decided to drill down into the specifics of where exactly in the United States did he travel he travel too. In practice, it’s areas with major or interesting culinary scenes, such as Los Angeles or The Bronx. However, there is still quite a bit of geographic diversity in general. It’s a nice mix of big cities but also not as famous places such as Livonia in Michigan, or parts of the American Southwest.
Now, some links…
Micah Meadowcroft (The New Atlantics): The Distance Between Us
In a studio somewhere, amid the smell of roses and cigarettes, bright air spills in with the breeze from a high and open window — the light is good for skin — and a beautiful young man sits for his picture. Outside, bees talk amongst themselves as they flit between the yellow blossom chains of a laburnum. Inside, the dull throb of London electronic music drowns their voices. And the model, who is not a model exactly, but an “influencer,” and in charge here as artist and subject both, has to shout for the camera so he can see the photographs.
Adam Serwer (The Atlantic): The Illiberal Right Throws a Tantrum
By the tail end of the Obama administration, the culture war seemed lost. The religious right sued for détente, having been swept up in one of the most rapid cultural shifts in generations. Gone were the decades of being able to count on attacking its traditional targets for political advantage. In 2013, Chuck Cooper, the attorney defending California’s ban on same-sex marriage, begged the justices to allow same-sex-marriage opponents to lose at the ballot box rather than in court. Conservatives such as George Will and Rod Dreher griped that LGBTQ activists were “sore winners,” intent on imposing their beliefs on prostrate Christians, who, after all, had already been defeated.
Chas Freeman: The Sino-American Split and its Consequences
But, finally, in China, we Americans have a cure for enemy deprivation syndrome – the sick feeling that affects military-industrial complexes when their adversaries unexpectedly throw in the towel, leaving them without a diabolical enemy to keep them in shape and in the money. The Soviet Union is dead, but China is having a comeback! Praise the Lord and pass the ammunition — and the cash to buy more of it!
Kim Larsen (Stitch-Fix): GAM: The Predictive Modeling Silver Bullet
Imagine that you step into a room of data scientists; the dress code is casual and the scent of strong coffee is hanging in the air. You ask the data scientists if they regularly use generalized additive models (GAM) to do their work. Very few will say yes, if any at all.
Now let’s replay the scenario, only this time we replace GAM with, say, random forest or support vector machines (SVM). Everyone will say yes, and you might even spark a passionate debate.
Despite its lack of popularity in the data science community, GAM is a powerful and yet simple technique. Hence, the purpose of this post is to convince more data scientists to use GAM. Of course, GAM is no silver bullet, but it is a technique you should add to your arsenal.
Reading Design
Reading Design is an online archive of critical writing about design. The idea is to embrace the whole of design, from architecture and urbanism to product, fashion, graphics and beyond. The texts featured here date from the nineteenth century right up to the present moment but each one contains something which remains relevant, surprising or interesting to us today.
What I’m Reading
I bought Leo Strauss’s On Political Philosophy. It’s a transcript of many of his lectures, starting with the lectures he did on Positivism explaining the history of the idea, such as it’s founding with Auguste de Comte, which the end of the lectures is where I am currently at in the book. It’s interesting to note that he speaks that metaphysics declined in importance as actual science became more important.
What I’m Working On
Creating more dashboards for my internship. It’s quite nice to turn what was once a tangled mess of an Excel sheet into a R shiny dashboard that one can just move sliders around versus deal with hidden formulas.
Thanks!
Thanks for taking the time to read this, I will be back next Monday. In the meantime, you can follow me on Twitter or reach out via email.