Like it or not, I spend a lot of time in front of a screen and a keyboard. I did not pay much attention to it until recently…
My setup at home is nothing extravagant, a plain table, a laptop stand to have the screen up to my eyes, my logitech trackball (not my original one, but a newer one), a trusty calculator, and my keyboard, a Drevo Gramr.
Filed under curious
This has been a small nightmare 🙂
So, I own an SN30pro gamepad mostly used to play Nintendo Switch. It works wonders, EXCEPT when running in multiplayer mode alongside other controllers, where I get a totally noticeable input lag
I stumbled upon a lego map in twitter and I thought it was quite fun and I should do something similar:
And here’s the result. One with NaturalEarth data colours for height, and another one with a set of official lego colours 😀
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NOTE from the future:
Since everybody in twitter was to keen to remind me, First the map in EPSG:25831, then in 4236 😀
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Let’s get out of your way, here’s the full-resolution map:
Barcelona Equidistant Azimuthal.
Available in my zazzle.es shop.
Now that you’ve seen it and ordered a print :-P, I can start going on on the full process 🙂
Coming back with another bcn map. this time I’m not representing anything from open data, but I’m playing around the network analysis tool available with Qgis. The following distances map has been generated using those tools:
Keeping with the row of Barcelona data, I present here a map of the unemployment rate per neighbourhood since 2012 up to 2019.
The data comes from Barcelona open data estat-atur-pes dataset. This dataset contains the column pes_atur for each month of each year. In the presented visualizations I simply used the value of January for each year.
pes_atur is the percentage of the unemployed registered citizens in each neighbourhood over the number of registered citizens for that neighbourhood with ages comprised between 16 and 64 years old.
Long definition, but clear idea.
Again, using a choropleth map similar to the one from the mean rent prices map. I just used a different colour scheme from white (almost no unemployment) to red (heavy unemployment).
First an animated gif of all the maps:
And now, all the individual maps per year.
There was no data prior to 2012, so what we can mostly see from here is a kind of recovery from the 2009 financial crisis. We come from 2012 when most neighbourhoods had over 11% of registered unemployment, to 2019 when we can see lighter tones, showing unemployment rates under 9% in most areas.
This is clearly not an in-depth review, just a quick take on the presented data. More information can be seen in the official Barcelona website, or the small publications from newspapers.
Castells 