Retrospective for NumPy Weather 1 to 10

Welcome to the first Retrospective of NumPy Weather 1 to 10 in which we will try to answer the following questions:

  • What did we do wrong?
  • What did we do right?
  • Profit? Just kidding. The correct question is – do we need retrospectives?

Let’s discuss NumPy Weather 1 to 10 in order of appearance:

  1. Cold Easter. It was supposed to be the coldest Easter since 1964 in the Netherlands. We went searching for weather data and quickly found the KNMI website. We explored the data a bit.
  2. Daily Temperature Range. We continued by checking out the daily temperature ranges.
  3. Global Warming. In which, we checked for any indications of Global Warming.
  4. Sun Radiation versus Temperature. We all know that solar radiation and temperature are related. Surprisingly, we found out that the correlation is not that strong.
  5. Wind Direction. Southwestern winds are predominant in the Netherlands having to do with the proximity of the North Sea. We proved as much in this post.
  6. Wind speed. We discovered a weak negative correlation between wind speed and temperature.
  7. Precipitation and sunshine duration. We had a look at precipitation and sunshine duration. It seems that sunshine and precipitation duration are inversely correlated. Obviously the rain duration is limited between 0 and 24 hours, with lower values being much more likely. We can see clearly that in the summer months, the sun shines longer and it rains less (duration-wise).
  8. Monthly Precipitation in De Bilt. Yes, it rains in De Bilt, but the amount of rain is not shocking.
  9. Atmospheric pressure in De Bilt. The Gauss curve fits the distribution of average daily pressures almost perfectly. The monthly average pressure seems to be constant.
  10. Atmospheric Humidity in De Bilt. Actually this post was about relative atmospheric humidity.

What did we do wrong?

Lots I would think. I already discovered a bug, but since nobody else noticed, I will keep silent about it. Unfortunately we didn’t get to predict the weather. So that’s something to keep in mind in the future.

What did we do right?

Everything that we didn’t do wrong, I guess. We did a lot of work with masked arrays and Matplotlib.

Was this retrospective meaningful?

I don’t know, but it sure was a good break from actual work.

The Next Sprint

In the next sprint I will try to focus more on predicting the weather. Although it might turn out to be too hard.

Update for April 14, 2013

People seem to have finally figured out that the WordPress botnet is a serious threat. I installed the Simple Login Lockdown plugin myself. The plugin keeps track of frequent login attempts and takes measures against them. Apparently the botnet is intelligent enough to not login from the same IP address too often. So this might not help. However, if you are using Apache and only access the admin dashboard from a fixed set of IP addresses, you might consider locking down access to the wp-admin directory with a .htaccess file in the same directory. If you are using a Content Delivery Network, you need to do a bit more work, but it’s doable.

By the author of NumPy Beginner's Guide, NumPy Cookbook and Instant Pygame. If you enjoyed this post, please consider leaving a comment or subscribing to the RSS feed to have future articles delivered to your feed reader.
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