I am practicing being concise. I want to simultaneously explore the field of data science and document my journey.
As part of enrollment in a seminar covering humanitarian free (libre) and open software (HFOSS), I was introduced to Python for the sake of creating an educational application for the Sugar desktop environment. Sugar is not the focus of this post; instead, I want to focus more on learning Python.
I was born in December of 1997. I was first introduced to Python when I was seven years old. My father sat me down in front of an old computer tower that had a floppy disk drive in it - I don't remember the model name - and put me in front of an old IDE. I don't remember the name of that, either.
The syntax didn't stick, but, the concepts remained. I would go on to enroll at the Rochester Institute of Technology in 2015 and pursue my undegraduate degree in Game Design & Development.
Recently, I became enamoured with the idea of actually using my knowledge of computer science to explore datasets in a meaningful way. Many years ago, while enrolled in high school, I was privileged to be in a school that was fell-funded and held encouraging programs for those interested in the sciences. At the time, I was still learning the basics of Java and C#, so data never gripped me as much as the game development industry did.
I went on to watch my peers do interesting things with data - I recall one group mapped geography to crime data and won a competition for their findings. My memory fails me, and, I am unsure of the specific name of that competition - but the essence of what inspired me still influences me to pursue this field in my leisure time.
Python is only one option when dealing with data analysis and visualization. There are libraries for data visualization in
R is a free software environment created for statistical computing and graphics.
I simply chose Python since I was already using it for Sugar development and felt that the barrier to entry would be lower.
So that's the goal: learn python for the sake of getting better with Data Science and chronicle the journey along the way.