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Taming Big Data (CSC 103)

Winter 2022

Programming Project 4: Tame your own data

In this project you will write a program to analyze some data of your own choice.

Learning Objectives:

1. Demonstrate that you can use the programming concepts you have learned in this class, such

as variables, functions, if-statements, loops, lists, dictionaries and file i/o

2. Apply what you have learned in this class to a domain of your own interest

Due dates: There are two milestones for this project with two separate due dates.

1. By Friday, 3/4 at the end of the day: Pick a dataset and decide how you want to analyze

it (Milestone 1).

2. By Friday, 3/11 before class: Implement a Python program that analyzes your chosen

dataset (Milestone 2). And prepare to present your results in class (Milestone 3).

1 Milestone 1: Pick a dataset and decide how you want to analyze it

1.1 Where to find a dataset

Here are some collections of datasets that you can use to find a dataset for this assignment. You can also use a dataset that you find elsewhere.

Requirements:

The dataset should either be in .csv format or a spreadsheet format, like .xslx, .ods, or a google sheet. If the data comes as a spreadsheet, save it as/export it to .csv. Files in the .csv format are text files where each line represents one row of data from the spreadsheet and the different measurements in each row are separated from each other by commas (csv stands for comma separated values). Because they are text files, you can use the techniques for reading from files you have seen in class. E.g. the temperature and precipitation data you worked with in one of the labs was stored in a format that is very similar to csv. And so was the districts data from the last project.

You can open .csv files in your Python editor. That will allow you to see the format of the file. Or you can open .csv files in a spreadsheet program (like Excel or Open Office). That will make it easier for you to look at the data and get a sense of what information is contained in the file.

1.2 Plan your data analysis

What are some interesting questions that you could explore with this dataset? You should pick at

least two different questions. The questions can be related, but one should not be a trivial extension

of the other. E.g. calculating the average would be a trivial extension of calculating the sum.

Let’s take Project 3 as an example. In that project you explored three different questions. First, how

many wasted votes are there in a given state; second, is the given state considered gerrymandered

according to one mathematical definition of gerrymandering; and third, visualizing the votes cast

in the state district by district.

1.3 What to submit

Upload the following two items to Nexus by Friday, 3/4.

1. Your dataset. If your dataset is too large for a Nexus upload, upload it to google drive instead,

allow viewing and copying for people from the Union community, and add a link to the data

file to your write-up (item 2).

2. A 1-2 page write-up (in pdf format) that addresses the following points

2 Milestone 2: Implement a Python program that analyzes your

chosen dataset.

Implement your program to analyze your dataset.

All the normal guidelines concerning academic honesty apply. You may refer to and reuse pieces

of any programs that you have worked on in the course of this class. (In fact, make sure to look

back at prior projects and exercises as you are working on this program.) But you should not use

any code you find on the Internet (or elsewhere). All work you submit has to be your own.

If you want to make use of a Python library that we have not used in class, please discuss this with

us first.

2.1 Programming guidelines

Please follow the same style guidelines you have been using for the previous projects:

1. Are all of your Python files properly commented? (Header comments consisting of your name

and a brief description of the program in that file as well as comments within your code to

clarify the logical structure of your program.)

Are your programs formatted neatly and consistently? Do you use whitespace (but not too

much) to help a human reader understand the logical organization of your code?

3. Did you clean up your code once you got it to work? It should not contain any code snippets that don’t contribute to the purpose of the program, commented out code from earlier

attempts, or unnecessary comments.

4. Do you use variable and function names that are informative and describe what the variable

stands for or what the function does?

5. Did you re-read and revise your program to make sure that you use all programming constructs

appropriately, that your logic is not unnecessarily complicated, and that all lines contribute

to the behavior of the program.

2.2 What to submit

Upload the following items to Nexus by Friday, 3/11.