What this software does?

     This software create a Electrical Installation of buildings project with a minimum interference by the user. You just need to input the room's dimension and the specifc power plugs, such as washing machines, motors. The software will make all the calculations such as the number and power of general power plugs for each room and each type of rooms, light power, cable and conduit sizing following the IEC rules for Electrical Installations of Buildings, which is, in Brazil, is ruled by NRB5410 from ABNT (Brazilian Technical Standart Association). Furthermore, a list of materials needed is generated based on a list of products already available in the Database, follwed by the budget.

A brief process history

     I started this project, after finishing my third Nanodegree in Data Science, looking for some application for the knowledge and skills I have learned, using my background in Electrical enginner and programming skills. In that time I was studing Electrical Installation of buildings and I had many difficulties to use the softwares available for that purpose. So, I thought, why not make my own software? And the result is here.


  • Electrical Engineer Bachelor degree from Sao Carlos Engineer School, Sao Carlos, Brazil EESC-USP.
  • Bioinformatic Specialist from Computational Science Lab, Petrópolis, Brazil, LNCC.
  • ABNT certified for Low voltage Electrical Installation of buildings (Safety and Protection).
  • Data Scientist
    • Data Sience Fundamentals I - Udacity
    • Data Sience Fundamentals II - Udacity
    • Data Sientist Nanodegree - Udacity

Software workflow

In the picture bellow we can see a simplified software animation workflow.

A few numbers and graphics about the time spent

Stats only for this project

Total of commits in this project


Number of days with at least one commit


Number of Deploys to Heroku


Number of lines in the main function


Number of lines in scripts to help


Commit graphic history

From left to right, those graphics are showing my work from 2018 october 1st to 2019 september 30th where each frame corresponding to 7 days.

  • Total number of commits for each month.
  • Total number of commits by weekday.
  • Total number of commits by the hour of the day.

Rolling mean from time between commits

     Once I became more confident using git to version control I started making commits more frequently, and doing so I was wondering how much time I was spending between commits. To check this information I made a Rolling mean graphic with a 50 commits window as you can see in the picture bellow. As I expected, the time between commits can be a good way to check your productivity once your routine and your commit behaviour are stable.

Stripplot graphic

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