Over the past few months as my learning journey continued, I finally completed my first introductory course in data visualization and plotting in Python. It was a short course on Udemy which focused on utilizing the matplot library. Besides learning the actual course objective, which was plotting, I also learned something very important from this course, which was how to utilize a library in Python.
Plotting with matplotlib and pyplot

Above is a screenshot of my screen with the code we wrote in the course and the chart that was produced once the code ran. This was incredibly exciting for me to see and test for myself because I had no idea how writing code would create a chart. I had a lot of questions about data science and absolutely no frame of reference into the subject prior to this course, but this introduction has piqued my interest!
The library that we were working with had a lot of features that made it simple to create visuals and change them as needed. The image above shows many lines of code beginning with plt. and that is because we were heavily working within that library and using its prewritten features. I never actually took a course that focused on utilizing a single library; the other courses and projects I have done used multiple libraries, so although I was able to follow the general philosophy behind their usage, this course really helped me understand the basics much better.
Scale Matters
One takeaway I took from this introductory course is that when working with data, scale matters. Scale alters the initial impression of what the visual data is saying. For example, we changed the y and x axis values often, and when doing this, the lines on the graph, including where they began and ended, shifted in ways that changed the visual to relay different messages. This made me realize why data science, interpretation, and visualization is so important.
Since I’m a visual learner, the visual aspect of data science is very satisfying for me because it combines two aspects that I favor: information and art.(Yes, for the sake of this post, I will consider a graph a piece of art!)
I’ve worked heavily with data in previous jobs, and with this new knowledge, I think back to all of our excel spreadsheets with statistical data sorted from A-Z, and wonder what that data would have said if plotted in a chart. What trends that may have been overlooked would we be able to see?
What’s Next?!
I will be posting soon about this year’s Hacktoberfest! Because I’ve been traveling these past few months, it’s been a tad difficult to write as many posts as I would like, but that won’t be the case for much longer!
Lastly, once I get back to my home base and re-unite with my Raspberry Pi and Vector Robot, I will be utilizing my new knowledge for more projects. This course made me better able to understand how to utilize the libraries offered in the Anki Vector SDK, which I’m very happy to test out! It feels wonderful to witness information click together.

