Spring 2021: Python in Math 152

Overview

• Problems will be posted below. The first week will consist of an introduction to/review of the basics of symbolic Python; content from then on will come from previous course material.
• Students will work together in their assigned teams during lab to complete as many of the problems as possible. All unfinished problems must be completed before the start of the next computer lab. Due to redefined days throughout the semester, some lab instruction and work may have to be done outside of class.
• You will use a Jupyter Notebook as your Python interface. Jupyter is available for free from the Anaconda website (see "Accessing Python" below for details.If you are uploading your work to GradeScope, use the template file provided for each lab for consistency and ease of uploading. If not, you do not have to run each problem in one block of code, but problems should be separated by explanatory text (change "Code" to "Markdown" in the appropriate drop-down menu, then press Shift-Enter when you are done. Alternatively, use comment lines in your code.)
• When you have finished, convert your notebook to PDF using the following steps:
  1. Select "File/Print Preview"
  2. Print the resulting screen (Ctrl-P) and select "Save as PDF" as the printer.
  Team members' names should be entered at the beginning of the file (see the templates for more details).
• Once your PDF is created, ONE team member should upload it to the place in GradeScope, eCampus, or Canvas as specified by your TA.
• Do any hand/setup work on scratch paper, which will not be submitted. All computational aspects of each problem must be done in Python unless otherwise specified in the problem.
• Attendance in lab is strongly encouraged, as you are able to get help from each other and from the TA during that time.
• Teams who prefer to use a different interface, such as PyCharm or Spyder, may do so, but it is their responsibility to create ONE PDF containing all commands, output and graphs.

Assignments

Schedule

Accessing Python

• All Open Access Lab computers have Jupyter and Python installed on their devices. If you need to transfer files to/from your university account, use a flash drive, cloud storage, email, or FileZilla.
• If you do not have Python installed on your device, it is free. Details on how to download are available HERE AND in greater detail at the Course Overview above.

Helpful Resources

• List of Commands used in lab: includes brief summaries and links to online help pages
• Python Instructional Video Series c/o the Math Learning Center
• Taming math and physics using SymPy by Ivan Savov.
• SymPy 1.7.1 documentation tutorial (includes a Quick search box)
• Can't find what you're looking for at the links above? There is no formal textbook, so search and learn-just like in the real world!