Finding Weirdness in Temperature Data

Posted to Mistaken Data  |  Nathan Yau

After parsing Weather Underground pages to grab temperature data, it’s time to look at the data. Can’t download all that data and not do anything with it!

First off, in my initial pass of my parsing script, I accidentally cut the month range short, so I didn’t get any data for December from 1980 to 2005. It should be noted that these plots don’t show this missing data. Um, there’s no axes or labels either. Sorry, I got a little lazy, but that’s not the point now anyways.

Notice anything weird about the above plot? There’s some unusually smooth data in the middle. Here’s a zoom in:

Wunder: Inconsistency Highlighted

If we look at the data between 1994 and 1997, there’s oddly a lot of smoothness… hmm… HMMM.

It looks like between that time, there was some interpolation going on. I mean, if that’s all you got, that’s all you got, but I wish WU would at least make note of it or provide some annotation.

Anyways, just another example of data posing to be something else. In my opinion, all data sucks until proven worthwhile.

Favorites

How We Spend Our Money, a Breakdown

We know spending changes when you have more money. Here’s by how much.

Top Brewery Road Trip, Routed Algorithmically

There are a lot of great craft breweries in the United States, but there is only so much time. This is the computed best way to get to the top rated breweries and how to maximize the beer tasting experience. Every journey begins with a single sip.

How You Will Die

So far we’ve seen when you will die and how other people tend to die. Now let’s put the two together to see how and when you will die, given your sex, race, and age.

Watching the growth of Walmart – now with 100% more Sam’s Club

The ever so popular Walmart growth map gets an update, and yes, it still looks like a wildfire. Sam’s Club follows soon after, although not nearly as vigorously.