Datapoints: The best datascience webcomic
And we’re back in action with Bokeh, this time with some poke data. Enjoy!
Here we’ll walk through creating two different stacked column charts in Bokeh using TSA claims from 2002 – 2015. Occasionally you’ll encounter datasets that lend themselves to aggregation by column chart. If that data is split out by categories (say…fruit imports) over various years then it may make sense to use this kind of chart. […]
A vision of the near future The year is 2022 and you just finished a workout your personal (digital) trainer from Total Lyfe Transformations. The workout was designed just for you. This service especially suits your needs. Signup was quick and easy and they even sent a watch (free!) for you to wear. You allowed […]
This episode we explore the built-in functions beginning with “C.” These include callable, chr, classmethod, compile, and complex.
There’s some kind of correlation in here somewhere…
Welcome to the first episode of let’s read the docs. We’re starting with the Python Standard Library documentation for 3.7.1. The following are code snippets (run via jupyter) for this episode.
Data pipelines across industries service an untold number of records each and every day. They deserve some TLC too.
Sometimes you’re looking where the light is…and not where you left your keys.
There are many different levels of data storage. Who knows the kind of magnitude we aspire to in the far future…
There’s a lot of them floating around these days.
To meet the definition of big data. One person’s tiny dataset is another person’s datalake…maybe?
We’ve all been under the dreaded time crunch. Training never happens quickly.
I think many of us have had this experience. We start a new job, move to a new team, join an existing group as a hobby and when we go to read their documentation we find…it doesn’t exist. Maybe the code itself is self-documenting?
Washington DC is one of the recipients of Amazon’s new HQ2s. With this decision comes mixed feelings for me and other locals. I believe in growth. Growth will get us the to the cities of the future dreamed up in those cheap comic books I read as a child. Growth will lift people out of […]
Humor will probably be the last to fall.
Once we start understanding the power of what’s possible this should change.
No matter what kind of data you have you probably could use more of it.
I don’t really see how we could change either. Seems easier to me to read right to left than think differently about coordinates, you?
There are already many uses for commercial drones…and I want a burger now.
Sure there are very many important things that neural networks are trained to do. But there are also silly things too, and they should be recognized and appreciated. 🙂
Technological change always causes disruption, but AI is likely to have a bigger impact than anything since the advent of computers, and its consequences could be far more disruptive. Being both powerful and relatively cheap, it will spread faster than computers did and touch every industry. ~The Economist
The government is extremely fond of amassing great quantities of statistics. These are raised to the nth degree, the cube roots are extracted, and the results are arranged into elaborate and impressive displays. What must be kept ever in mind, however, is that in every case, the figures are first put down by a village watchman, and he puts down anything he damn well pleases. ~Josiah Stamp