Back to train(ing)s!

I have found a bit more inspiration to work with MongoDB and I also returned to the train data. But, instead of continuing with the train schedules I looked at the historical data as I had one question on my mind: Is the S9 train always late?

Well, it seems that it has been late and when tweaking the queries long enough and plotting the data just right you can see a “message” from the train operator ๐Ÿ˜€

s9

The above graph shows the differences between the scheduled and actual running times (when the train was more than 15 mins late) for the S9 arriving at my home city. The data is from June 2016 to mid-March 2017 and unless I’m mistaken it looks like that the data is giving me the finger ๐Ÿ™‚ The graph was done in Excel based on the JSON data residing in MongoDB.

I also took my first stab at the matplotlib and plotted the difference for the whole data. And at the first glance it does support my hypothesis that the S9 was late fairly often. I’ll try to work with matplotlib more and produce more graphs and also work with pandas in order to analyse the data a bit more. But it’s good to have some validation for my gut feeling.

s9_matplot

Trainings

As the title hinted, I have continued my learning path and I’m subscribing two MongoDB courses at the MongoDB University: M101P and M102 which are Mongo for Developers (Python) and MongoDB for DBAs. I already completed the M201 (MongoDB Performance) and I must say that the contents and the facilities (videos and the trainers) are spot on.

The main goal is to sit through the certifications for M101 and M102 in the summer and these little side-projects help a lot. So, good times at the moment!

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