Angela May

Exploring Product Design

Posts Tagged ‘python’

Abundance Mentality

A reading-focused week, been working through this Abundance book by Diamandis and Kotler. It’s not exactly what I was looking for (in terms of what a post-scarcity economy would look like and how to micro-implement it) but it’s a really interesting book so far. I’ve been taking a lot of notes on topics for further research. The fundamental premise is that technological growth is exponential, and certain exponential technologies are going to change everything and soon. The exponential technologies that are explored in the text are Biotechnology, Bioinformatics, Computational systems, Networks and sensors, Artificial intelligence, Robotics, Digital manufacturing, Infinite computing, Nano materials, and Nanotechnology. I’m still working through it, but I’m learning a lot.

This week I also attended a Conscious Business seminar, where I met others who are interested in conscious business practices. It was fairly introductory but I found a number of terms I’ll be looking into in more detail in the future.

On Wednesday my coworkers Div and Taylor presented a lunch and learn about Python. It was mostly an introduction to the syntax, but I did learn quite a bit about an IDE called PyCharm that I’ll be looking into, and it helped to clarify some of the points that were still confusing to me. Dylan made an interesting point in how remarkable it is that all of these IDEs, libraries and even Python itself is completely free and open source. Everything coming back to abundance…

Today will be more chunking through the Udemy Python course, away we go!

Posted: October 23rd, 2015
Categories: Journal
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Pythoning

Plodding through this Udemy course. So far it seems much more applicable than the Coursera course, and it moves at a fairly brisk pace so that’s nice. Slowly chipping away at it a little at a time.

Otherwise at lunches I’ve been reading the next Tufte book, Envisioning Information. A lot of overlap with the previous book, the Visual Display of Quantitative Information, but still a good read, some really interesting examples so far from Tokyo.

Denis linked to a really interesting article I’ve been chewing on about what the author termed the “Post Capitalist” society. I’m not so sure about the author, but I am interested in the idea of exploring the inevitable outcomes of a major upheaval in our working society. Preliminary research has led me to this youtube channel, which is ok, still updating. If possible I’d like to break away from theory written by old white guys because I feel like the solution is going to come from somewhere else. Getting data is tough, because other societies don’t tend to get the respsect in academic circles that they deserve. May become an anthropology exercise, we’ll see.

Started a new initiative at work where we try new methods every Friday, working out well so far!

Posted: October 16th, 2015
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Python Sloggin’

I want to get back into journalling my progress in an effort to keep a bit more focused on ProD.

Awhile back I did a bunch of soul searching. I spent quite a bit of time on this. I was trying to answer: what should I pursue to get to the next level? What skillset is valuable, but naturally complimented by my existing skills? How can I become more of an asset to my current team? I didn’t think that duplicating their skillset would be the way to go, and I decided to pursue something a bit more uncommon.

Data Visualization is something that I eventually settled on. I’ve always been fascinated by graphs, and I think communicating information clearly is going to become an even bigger challenge going forward. This leverages much of my existing skillset (my technical background, some programming background, as well as good experience with excel and illustrator). I started researching Data Vis – what methods people were using and which tool would be the best to become familiar with.

I started with an OSU course through iTunes U which was very good, but was mostly focused on R. (more info)

Then I read a few books to give a broader context and get an impression on best practices for data vis. In order to select these books I did a lot of internet searching and collected the most-often recommended books, as well as scouring the Amazon ratings. My selections included The Quantitative Display of Visual Information by Tufte which I LOVED and immediately went out to buy his next two books in the series. I also read Visualize This which was interesting but more tutorial-based… I might check back with it later.

The two languages most often cited for Data Vis were R and Python, with an honourable mention to a couple of other languages including PHP and JavaScript.

R looks achievable, and I may still go back to it, but I decided to pursue Python instead, mostly because of its broader flexibility and usefulness in my field of work. So the mission became learn how to program in Python.

After floundering for a bit trying to teach myself this (there is a lot of conflicting information and lot of easy stuff to slog through before I get to what I actually want) I bit the bullet, enrolled in and completed this Coursera Course from Rice. It was okay. I found it very easy to keep up with, and I’m now confident I have fundamentals of the language, but the whole thing took place in this walled garden of a web-based development environment that has all these shortcuts… in actual real life I’m going to need to learn to do all that (installing an IDE, managing libraries, dealing with broken imports blah blah blah).

So my NEXT tactic is THIS course from Udemy:

https://www.udemy.com/learning-python-for-data-analysis-and-visualization/learn/

And I’m going to try to apply what I learn to the data exports in Harvest, because that will be handy for the team :)

Posted: October 9th, 2015
Categories: Journal
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