At the 2.5th month mark of my monkish pursuit in relearning Python and Pythonic concepts in Data Science, I found myself wanting to closely chronicle my journey. For me, the biggest question in writing about my thoughts and ideas (related to this pursuit) has everything to do with outlining. How do I organize and clearly present my often random — and most likely novice — realizations?
The simple answer, of course, is just that; as cluttered and as close to the bone as possible. Hence, this roundup format. The idea is to notate what feels relevant and urgent. My goal is make these posts as my metaphorical version controls, my milestones, so I can someday look back and see how far I’ve come.
Let’s get right to it!
For this first-ever post, I want to ribbon cut by listing some of my online finds due to a confusing first date with Matplotlib.
- Jake VanderPlas’ Visualization with Matplotlib (Chapter 4 of his Python Data Science Handbook, via Github) was a lifesaver. It gave the conceptual overview I needed to better grasp the linguistic / syntactical quirks of Matplotlib. His prologue on the history of MPL provided some useful background on why the scripting is a little different from everyday Python.
- HTML5 makes me excited about possibly learning Javascript, or researching more on converting Python to Javascript. I’ve been thinking a lot about how to make interactive web visualizations, and this might be a great answer to it.
- r/place is such a conceptual mood. I want to be able to create something similar to it, probably in a much smaller scale in the beginning.
- Speaking of reddit, r/dataisbeautiful seems to be a serendipitous find. Haven’t explored it yet, but I think it’ll be a great future resource.