One of the things I wish I had known more about when I first started working with Python (and, really, any time before I finally learned about it a couple years ago) is the power of virtual environments for Python using the
Yes, you read that right... riding your bike without a helmet may be safer than riding with one.
Statistics are an interesting thing. They can very quickly relate large amounts of information. The problem is that without careful analysis they can create the wrong impression or give an altogether false understanding of the world.
Why It Makes Sense to Bike Without a Helmet is a simple example of this very concept:
Recently I decided I wanted to perform a statistical analysis of all the music I've ever played in iTunes. This is non-trivial, as iTunes only stores the date and time each song was played last and does not keep any log showing previous plays.
With several copies of my iTunes library file, I can reconstruct the overall history. Luckily, I am using Time Machine and can therefore retrieve snapshots of the library. This is enough to reconstruct the history going back over a year.
Hilarious commentary by, of all people, David Attenborough:
The environment is complex. I love studying complexity, and observing ecosystems fascinates me because they are made up of many moving parts that each interact with the others in ways that are simple but in an overall way that is too complicated to predict reliably.
Several years ago, wolves were reintroduced to Yellowstone National Park. The expectation was that this would help manage the populations of deer and other large game. It did. But it also impacted the environment in a slew of unexpected ways in what's called a trophic cascade. This video explains it well: