Virtual Peoples…

This is my last day of work before Christmas and New Year festivities. Time for one last update on the crazy stuff I am currently doing and also time to wish you and you families all the best for the new year!

My group is currently working on a data science project and as peoples in that field might have experienced, it is sometime hard to get by the data… As probably others have done in the past we decided in a first phase to generate our own data from simulation.

We have to simulate peoples, more precisely in this case, peoples from the Montreal area. We want the simulation to be representative of the reality, thus we start from Canadian census data and generate virtual denizens which are statistically correct for their home location. I’m also generating names from various sources (including tombstones registry). I’m still in the first stages of that simulation, but here is a subset of virtual denizens I have generated for my neighborhood region (Any resemblance between the generated virtual denizens in this article and any persons, living or dead, is a miracle.)

Rita Desjardins a Female Adult of 22 year old, born in Europe.
– Who attended College, CEGEP or other non-university certificate or diploma.
– Is not in the work force.
– Has an income of $5,000 to $9,999.
– Usually move around by means of Car, truck or van – as a passenger.

Youssef Bedard a Male Kid of 3 year old, born in Quebec.
– Is currently attending daycare.
– Usually move around by means of Car, truck or van – as a passenger.

Louis Martel who is not a Canadian citizen.

Lyana Belanger a Female Kid of 16 year old, born in Quebec.
– Is currently attending school.
– Usually move around by means of Car, truck or van – as a passenger.

Sam Roy a Male Adult of 22 year old, born in Quebec.
– Who attended Bachelor’s degree.
– Is currently working full-time in: Business, finance and administration occupations
– For the Educational services industry and Worked at usual place.
– Has an income of $60,000 to $79,999.
– Usually move around by means of Car, truck or van – as a driver.

Matheo Gagnon a Male Adult of 22 year old, born in Asia.
– Who attended College, CEGEP or other non-university certificate or diploma.
– Is currently working full-time in: Trades, transport and equipment operators and related occupations
– For the Manufacturing industry and Worked at usual place.
– Has an income of $60,000 to $79,999.
– Usually move around by means of Car, truck or van – as a driver.

Marc Bouchard a Male Adult recent immigrant of 45 year old, born in Europe.
– Who attended Bachelor’s degree.
– Is not in the work force.
– Has an income of $50,000 to $59,999.
– Usually move around by means of Public transit.

You can expect I’ll publish some portion of the Python Notebook performing this generation somewhere in the new year, if this is of interest to you.

In the mean time I wish you joyful end of year festivities!

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More Adventures in Geolocation!

I’m in Sweden this week for an Ericsson internal event where I presented a demo and the jet lag was really hitting me yesterday… couldn’t sleep much after midnight. So I took some time to continue my adventures in geolocation.

As I stated last time, more could be done on the data with the approach I am taking, like a clustering / analysis of when I’m at those locations. So to go a little bit further with the analysis I’ve updated my Jupyter Notebook to perform such analysis.

As expected, it shows that I’m at work weekdays from around 6h to 15h. It shows I’m at my cottage on weekends and it shows I’m at home otherwise. The system works!

locationTime.jpg

I’ve decided to push that notebook to GitHub as this is strictly learning, so you can access it from there if you want details on the method I used.

Finally, I am still progressing on the Advent of Code 2016. Now completed Day 8, you can follow the code I produced on GitHub as well.

That’s it, tomorrow I’m heading back home.

Advent of Code 2016

Last year I mentioned the advent calendar made specifically for peoples who want some small exercise to train or retrain in coding. The Advent of Code is back this year with the 2016 edition. As I said last year, if you are born a coder, you should go back to coding from time to time, if only to remind you of the inherent complexity of the task and Advent of Code is a good way to do it.

The concept is simple, every day till Christmas, the site proposes a two-part challenge. If you pass the first part, you can go on with the second part. Input for the problem is provided as text and you enter your solution in a text box on the site. Nothing fancy, which allow you to use pretty much any programming language you want.

Last year I did most of it using Python, this year I’m doing the same but with the twist of using as much as possible of pandas as I can since I am ramping up my python data science skills. One of my colleague and friend is trying it out with R for the same reasons.

Funny enough if you look at the first day challenge solution we provided, although being in two different programming languages are still quite close one to the other. You can take a look at my Python Notebook or my colleague R Notebook on github. It seems that pandas and R both propose a similar way to approach the problems.

Do not pass up on this opportunity to brush up your skills in one or many programming languages. And as I do, nothing prevent you for giving it a twist to learn a new library as you go.

Happy Advent 2016!