DATA 311 - Lecture 0 Worksheet

Write the names of the students at your table:

1. Let’s revisit the example datasets we looked at last class. For each one, consider: is it structured or unstructured? Can you describe the structure more precisely using the terms we’ve now talked about? It’s posible there may not be one correct answer, or we may not know enough to say in all cases.

• Daily temperature records

• Social media connections (who follows who)

• A collection of textbooks

• A course gradebook

• Daily sky conditions (cloudy, sunny, foggy, etc.)

• Browsing history of all users of Google Chrome

• All youtube videos

• A database of WWU students

• Satellite images of the USA

• An org chart (who works for who)

2. Let’s explore the limits of some of the data types we talked about, as implemented in numpy, our favorite Python numerical computation library. Go to the department’s JupyterHub, start a Jupyter server, and create a new notebook. For each of the following subtasks, create a Markdown cell with a descriptive title, followed by a code cell that answers the question.
   1. Import numpy using import numpy as np
   2. Confirm for yourself that 0.1 + 0.2 == 0.3 returns False.
   3. Call np.iinfo on some different integer datatypes (np.[u]int{8,32,64} to see the exact limits of those types.
   4. Call np.finfo on some different floating-point datatypes (np.float{16,32,64}) to see what numpy can tell you about them.