Date & Time
Wednesday, December 10, 8:00-9:50am, PM 103
Overview
The final exam is comprehensive will cover all material from the
beginning of the semester through the end but with some emphasis on
material covered since Test 2. The final is more
comprehensive than Test 2 was. This material includes
everything discussed in lectures and covered in assignments, and aligns
with chapters 1-10 from the recommended text. We have covered some
additional topics (including concurrency, structural pattern matching,
data, visualization, and machine learning) the text has not, and we did
not specifically cover the data science additions to each chapter
although some overlap with the last weeks of the course. Because this is
a programming principles course, there will be questions related to
principles as well as questions that involve syntax. You may be asked to
write, analyze, and/or debug code.
Example Types of Questions
- Examples from Test 1
- Examples from Test 2
- What are the differences between threading, multiprocessing, and the
asyncio concurrency models?
- What is the GIL and how does it impact concurrency in Python?
- Which type of concurrency solution would you use to download a lot
of files from a slow internet site and perform some light processing on
them?
- What makes a match statement different from an if-elif-else
statement?
- How do you capture variable-length sequences in a match case?
- What are the differences between a numpy array, a tuple, and a
list?
- Write a statement to refer to a specified subarray (indexing,
slicing).
- What is the difference between a view and a copy of a numpy
array?
- What differentiates a pandas series from a numpy array?
- What differentiates a polars series from a pandas series?
- Given a data frame, write an expression to select the age and height
columns from rows with names starting with “A”.
- Given a data frame, which operations are used to make tidy data
(i.e. melt/unpivot, pivot, transpose)?
- Given a data frame of houses for sale in different parts of the
United States, write code to find the maximum price of a house in each
zipcode.
- What is the purpose of data visualization?
- Given a dataset, how might you create a visualization that shows all
of the columns? Think about the different ways to encode data
attributes.
- What are the differences between matplotlib’s stateful and
object-based styles?
- How can multiple visualizations of the same dataset be useful?
- Why is interaction important in visualization? What are these
different types of interactions?
- Why do we have a testing and training set in machine learning?