I’m doing some form of data visualization learning for 180 days because I need to #JFDI.
It’s pretty cool to just see how much information I’ve consumed in the last 112 days I’ve been doing this. Honestly, it’s brought a lot of self-awareness about the learning process that I didn’t have before; I’ve never been quite the stellar student, but rather an enthusiastic piecemeal learner of things. This process is teaching me how to be a better student to actually master something I really want to master. A lot of my normal habits in information consumption, doing things piecemeal or reading a lot of material hasn’t necessary been the best at helping me master D3 or Data Viz in general. Namely, I just gotta make more stuff.
The shifting gears piecemeal way I’ve also been going about this with different learning sources of learning D3 simultaneously with D3 (out of necessity) has made this process difficult and stressful because I’m not sure where I’m at really. Just in general, my coding skills aren’t that strong because I haven’t had to work consistently in one project – was in grad school prior to this one so it was quite haphazard – and now I gotta clamp down. It’s a very different approach to become more specialized. I think I need to really focus on fundamentals in coding while simultaneously upping my game in D3 and still be reading about design as much as possible.
All things I love, but I gotta stay more focused.
One drawback of doing the 180 days, especially because when I started I wasn’t working full-time, is the impetus to have something to show for it at end of everyday, whether it’s takeaways from coding or reading. It’s much harder doing an actual project, where you can’t see the results day-to-day, even though you’ve been solving serious problems to move forward the on the project. I need to start letting that go a bit – maybe do the three takeaways approach for what doesn’t work.
Will go back and finishing what I should have stuck with- which is the Udacity Data Visualization and D3.js course that I learned the most from starting tomorrow.
Reading and Learning Data Visualization Theoretically/Critically:
Reading Nathan Yau’s book Visualize This
287-300 Visualizing Spatial Relationships
- SVG is actually an XML file -> text with tags editable in text editor -> when you want to fill in a choropleth you are modifying style attributes of path p 292
- Wikipedia is a good source of base mags in svg p 298
- Use code to iterate through data values and assign color values and use if else statements to hep you p 300