Jan 31

Topics for this week : visualization, vectors, matrices Please explore chapters 3 & 4 in the text.

visualize

Chapter 3 shows you how to make some basic plots such as histograms and scatterplots in jupyter.

(Be aware that matplotlib - one of the standard ways to make these plots in this environment - has its own idiosyncrasies. Most of the functions change a global default "figure" object, and it may draw (or not draw) a plot depending on what it expects you want. Trying to initiate or show a plot from within a function may not behave the way you expect. Check out its docs - I've put links on the resources page - and follow their examples.)

manipulate

Chapter 4 discusses briefly vectors (1D arrays of numbers) and matrices (2D arrays of numbers), and some ways to combine and operate on them.

I'll walk through some of the code from the book for both chapters and show you another file of graphics I wrote last year, using the attached files.

your mission ...

Your job for this week:

• Grab some data from kaggle or elsewhere.
• Manipulate it a bit. (Put it into buckets, combine pieces, fill in missing values, ...)
• Make some plots to visualize what you have.
• Rinse and repeat.

We'll play around in class with these ideas using the iris flower dataset.

Think of this as getting your feet wet for the project(s) you'll dive into more deeply later in the term.

Here are a few datasets you might consider. See the resources page for more options, or search online with terms like "dataset" and a topic you're interested in.

• kaggle: cost of living
• kaggle: wine reviews
• kaggle: border crossings (big)
• fivethirtyeight: fight songs (data link is near bottom)

attachments

		last modified	size
	3_visualizing.html	Tue Oct 15 2024 05:40 am	555K
	3_visualizing.ipynb	Tue Oct 15 2024 05:40 am	263K
	4_vectors.html	Tue Oct 15 2024 05:40 am	280K
	4_vectors.ipynb	Tue Oct 15 2024 05:40 am	5.8K
	fib_fit.html	Tue Oct 15 2024 05:40 am	537K
	fib_fit.ipynb	Tue Oct 15 2024 05:40 am	248K