My Colab assignment is here and my Observable assignment is here.
I enjoyed working with both of these platforms, as I’ve never used either before and they’re both useful tools for learning and practicing new programming languages without any barriers to entry – no need to download any software or do anything complex to just get started. I’m pretty familiar with basic JavaScript but have only really used it for simple interactivity on websites (like forms and menus and the like), so I’m interested to see how we’ll use it in the context of analyzing historical data. I’ve never used Python, but I do use R (a similar statistical programming language) fairly often — I’m excited to learn Python, though, as its a more modern and less ‘clunky’.
One reply on “Module 3: Observable & Colab Assignment”
Ha, both the ease of entry of the platforms and Python’s fairly straightforwardness are the main reasons we’re doing Python and not other languages. I find R a pain in the neck for a lot of reasons and until recently worked mainly in Ruby, but with colabs and jupyter format getting more widespread in research use, Python has the lowest barrier to entry right now. We’re not going to use it for this class, but the Pandas library might be of interest.
For javascript, we’re mainly not going to be using it for analysis but rather display; there’s optional assignments in modules 5 and 7 that you might find interesting. D3js can be used for analysis, in the sense that you can use it to find and display trends, but it can get extremely slow and crash browsers if you don’t do a lot of prep work summarizing big datasets.