In this article I would like share a very simple analysis about developers and their relevance in 6 of the most important capitals of #LatAm. Based on data proposed by [http://data.stackexchange.com/] we will study the behavior of developers [all disciplines] in [Buenos Aires, Sao Paulo, Santiago de Chile, Lima, Bogota and Mexico City]
I used the #Users table, the complexity begins when the analysis of the #Location attribute shows a quite variable string. Anyway it's possible identify the data of cities without problems. For this sample/snapshot I identified over 5K developers.
I used the #Users table, the complexity begins when the analysis of the #Location attribute shows a quite variable string. Anyway it's possible identify the data of cities without problems. For this sample/snapshot I identified over 5K developers.
Bogotá, Colombia | 650 |
Lima, Perú | 515 |
Santiago, Chile | 750 |
Sao Paulo, Brazil | 1845 |
Mexico City, Mexico | 582 |
Buenos Aires, Argentina | 1395 |
Total | 5737 |
I used a very simple model query like this:
Select count(*), Sum(reputation),Location from
Users
Where Location LIKE 'key%'
Group by Location
Order by Sum(reputation)
Then using some filters... if you want avoid this step you can use better regular expressions [more accurately]. Later we added the relevance of the developers of each country and here the result chart
#BuenosAires birthplace of great developers? Analysis according #stackexchange por Nicolas Bortolotti se distribuye bajo una Licencia Creative Commons Atribución-CompartirIgual 4.0 Internacional.
Users
Where Location LIKE 'key%'
Group by Location
Order by Sum(reputation)
Then using some filters... if you want avoid this step you can use better regular expressions [more accurately]. Later we added the relevance of the developers of each country and here the result chart
#BuenosAires birthplace of great developers? Analysis according #stackexchange por Nicolas Bortolotti se distribuye bajo una Licencia Creative Commons Atribución-CompartirIgual 4.0 Internacional.
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