Program 6: Data Visualization

Logistics

• Due Date: Friday, April 26th no later than 11:59 p.m.
• Partner Information: You may complete this assignment individually or with exactly one partner. If you work with a partner, you must both be enrolled in the same lab section or you will both lose 10 points.
• Submission Instructions: Upload your solution, renamed to YourFirstName-YourLastName-PartnerFirstName-PartnerLastName-Program6.py to the BrightSpace Program 6 Dropbox. If you work with a partner, only one person should submit the solution.
• Deadline Reminder: Once the submission deadline passes, BrightSpace will no longer accept your Python submission and you will no longer be able to earn credit. Thus, if you are not able to fully complete the assignment, submit whatever you have before the deadline so that partial credit can be earned.

Learning Outcomes

• Use pandas to visualize data.
• Gain experience visualizing data in an insightful manner.
• Design and implement a solution to a problem with no starting code.

Assignment

• Use the Airlines CSV Library for this assignment.
• Use pandas (and possibly also matplotlib) to produce two different visualizations that help the user gain insight into the information contained in the csv file.

Grading - 100 points

• 20 points - pandas is used to produce two insightful visualizations. It is also OK to use matplotlib for things that can not be done easily in pandas. All or nothing.
• 10 points - Each pandas visualization is a different type. For example, one visualization could be a bar chart and the other could be a pie chart. All or nothing.
• 10 points - The visualizations use the underlying data to show different things. All or nothing.
• 20 points - All aspects of each visualization are clearly labeled. 3 points for each type of improvement up to 20 points.
• 10 points - The first visualization contains at least two insights that are explained carefully in a comment at the top of your program. For example, when we did the Montana population example in class, the graph enabled us to see that something interesting (e.g. drought and depression!) happened from 1920 through 1940 that caused the population growth to flatten or even decrease. 5 points per explained insight.
• 10 points - The second visualization will be graded in the same manner as the first visualization.
• 20 points - The Python solution is properly commented, easy to understand and does not contain unnecessary code. 3 points for each type of improvement up to 20 points.