Exam 1 information

Exam details:

  • The exam starts at 4 PM and ends at 5:15 PM. Please arrive early and get logged in.
  • The exam will be available on the X:\ drive on winstat.
  • You will need to upload your finished notebook to Canvas. Allow yourself enough time to get your file uploaded before 5:15 PM. You might want to log into Canvas before the exam starts, so you can easily upload it once finished.
  • The exam is open-book and open-Internet. Having to rely too much on books and the Internet will slow you down.
  • You cannot work with others on the exam.

Some suggestions for studying:

  • Go over the notebooks we have covered in class (up to, and including, pandas_2_input)
  • Go over the coding practices.
  • You could try doing the practice parts from the class notebooks and the coding practice problems again, but without much outside help. Are there subjects that need more practice?
  • Take the practice exam as if it was a real exam. Keep track of time, and do not discuss the exam with others. Again, did you find subjects that could use more practice?

Office hours

During exam week, office hours are

  • Tuesday 2:30 PM-3:30 PM
  • Wednesday 2:00 PM - 3:00 PM
  • Thursday 10:00 AM - 10:45 AM
  • By email

Topics (a non-exhaustive list)

This list is meant to help you guide your studying. It is not, however, an exhaustive list of everything that I might ask about on the exam. Anything we have covered in class might show up on the exam.

  1. Markdown
    1. Fonts (bold, italic, etc)
    2. Lists (ordered, unordered)
    3. Links
    4. Formatted code
  2. Python basics
    1. Types (how to find a type, how to convert)
    2. Working with lists, strings (including string formatting), and dicts
    3. Bools and if statements
    4. Loops and list comprehensions
    5. Slicing
    6. User-defined functions
  3. Pandas
    1. Creating DataFrames (from a dict, from a file, handling messy files)
    2. Working with the index
    3. Dealing with column names
    4. Computation on DataFrames
    5. Summary statistics from a DataFrame
    6. Taking subsets (row and/or columns) from a DataFrame (using loc[], using conditionals)