TDM 10200: Python Project 11 — Spring 2025

Motivation: We continue to learn how to create functions and apply the functions to many data sets in an efficient way. We can extract information in a straightforward way.

Context: We learn how to apply functions using map and using list comprehensions.

Scope: Applying functions to data.

Learning Objectives:

Learn how to apply functions to large data sets and extract information.

Make sure to read about, and use the template found here, and the important information about project submissions here.

Dataset(s)

This project will use the following datasets:

/anvil/projects/tdm/data/flights/subset/* (flights data)
/anvil/projects/tdm/data/election/itcont/* (election data)
/anvil/projects/tdm/data/icecream/* (ice cream data)

In this project, we walk students through these powerful techniques.

It should be enough to use 2 cores in your Jupyter Lab session for this project.

Some of the questions in this project take a few minutes to run.

Please remember to make comments (in full English sentences) about your understanding of each of the questions and solutions. This is especially important in this project, where we walk you through the solutions, but we still want you to write some explanations of your own!

Questions

Question 1 (2 pts)

For this question, only use the data corresponding to flights with Origin at the Indianapolis IND airport.

Hint: If you only want to import the 3 columns of the data that you need, recall that column 1 (the second column) is the month; column 15 (the 16th column) is the DepDelay; and column 16 (the 17th column) is the Origin. Python starts numbering from 0.

Write a function called monthlydepdelays that takes a year as the input and uses groupby to return a Series of length 12 with the average DepDelay for flights starting at IND in each of the 12 months of that year.
Test your function individually, one at a time, on the years 1990, 1998, and 2005. For instance, if you run monthlydepdelays(1990), the output should be something like:

1     7.282772
2     9.497027
3     6.924841
4     4.949858
5     5.471487
6     6.010835
7     4.307377
8     5.639782
9     4.455586
10    4.473725
11    3.408304
12    9.764105

Deliverables

Write a function called monthlydepdelays that takes a year as the input and returns a Series of length 12 with the average DepDelay for flights starting at IND in each of the 12 months of that year.
Show the output of monthlydepdelays(1990) and monthlydepdelays(1998) and monthlydepdelays(2005).

Question 2 (2 pts)

Consider this page, about using matplotlib to display several plots all at once:

matplotlib.org/stable/gallery/subplots_axes_and_figures/subplots_demo.html

We want to display 6 plots, which appear in 3 rows and 2 columns, namely: plot the results of monthlydepdelays for the years 1988 through 1993.

It could look as simple as this:

import matplotlib.pyplot as plt
results1988 = monthlydepdelays(1988)
results1989 = monthlydepdelays(1989)
results1990 = monthlydepdelays(1990)
results1991 = monthlydepdelays(1991)
results1992 = monthlydepdelays(1992)
results1993 = monthlydepdelays(1993)
fig, axs = plt.subplots(2, 3)
axs[0, 0].bar(results1988.index, results1988)
axs[0, 0].set_title("1988 Delays")
axs[0, 1].bar(results1989.index, results1989)
axs[0, 1].set_title("1989 Delays")
axs[0, 2].bar(results1990.index, results1990)
axs[0, 2].set_title("1990 Delays")
axs[1, 0].bar(results1991.index, results1991)
axs[1, 0].set_title("1991 Delays")
axs[1, 1].bar(results1992.index, results1992)
axs[1, 1].set_title("1992 Delays")
axs[1, 2].bar(results1993.index, results1993)
axs[1, 2].set_title("1993 Delays")

or if you want to use a loop, you could write:

import matplotlib.pyplot as plt
allmyyears = [myyear for myyear in range(1988,1994)]
myresults = [monthlydepdelays(myyear) for myyear in allmyyears]
nrow = 2
ncol = 3
fig, axs = plt.subplots(nrow, ncol)
for i, ax in enumerate(fig.axes):
    ax.bar(myresults[i].index, myresults[i])
    ax.set_title(str(allmyyears[i]) + " Delays")

Deliverables

Make a 3 by 2 frame of 6 plots, corresponding to the results of monthlydepdelays in the years 1988 through 1993.

Question 3 (2 pts)

For this question, only use the data corresponding to donations from the state of Indiana.

Write a function called myindycities that takes a year as the input and uses groupby to make a Series of length 10, containing the top 10 cities in Indiana according to the sum of the amount of donations (in dollars) given in each city, during that year.
Test your function individually, one at a time, on the years 1980, 1986, and 1992. For instance, if you run myindycities(1984), the output should be something like:

FT WAYNE         44665
TERRE HAUTE      52650
CARMEL           53200
EVANSVILLE       65250
SOUTH BEND       68387
INDPLS           76520
FORT WAYNE       80882
ELKHART          93171
MUNCIE          104260
INDIANAPOLIS    511935

Deliverables

Write a function called myindycities that takes a year as the input and uses groupby to make a Series of length 10, containing the top 10 cities in Indiana according to the sum of the amount of donations (in dollars) given in each city, during that year.
Show the output of myindycities(1980) and myindycities(1986) and myindycities(1992).

Question 4 (2 pts)

Run the function myindycities on each of the even-numbered election years 1984 to 1994 as follows:

allmyyears = [myyear for myyear in range(1984,1995,2)]
myresults = [myindycities(myyear) for myyear in allmyyears]

Now display 6 plots, which appear in 3 rows and 2 columns, namely: plot the results of myindycities for the even-numbered years 1984 through 1994.

If you want to use a loop, you could write:

import matplotlib.pyplot as plt
nrow = 2
ncol = 3
fig, axs = plt.subplots(nrow, ncol)
for i, ax in enumerate(fig.axes):
    ax.barh(myresults[i].index, myresults[i])
    ax.set_title(str(allmyyears[i]) + " Indy Cities")

Do not worry about the fact that the plots are overlapping.

Deliverables

Show the results of myindycities for each even-numbered year from 1984 to 1994.
Make a horizontal bar plot for each of the 6 years in part a.

Question 5 (2 pts)

Find the average number of stars in each of these four files:

/anvil/projects/tdm/data/icecream/bj/reviews.csv

/anvil/projects/tdm/data/icecream/breyers/reviews.csv

/anvil/projects/tdm/data/icecream/hd/reviews.csv

/anvil/projects/tdm/data/icecream/talenti/reviews.csv

Write a function myavgstars that takes a company name (e.g., either "bj" or "breyers" or "hd" or "talenti") as input, and returns the average number of stars for that company.
Define a vector of length 4, with all 4 of these company names:

mycompanies = ["bj", "breyers", "hd", "talenti"]

and now use a list comprehension to run the function from part b that re-computes the values from part a, all at once, like this:

[myavgstars(x) for x in mycompanies]

Deliverables

Print the average number of stars for each of the 4 ice cream companies.
Write a function myavgstars that takes a company name (e.g., either "bj" or "breyers" or "hd" or "talenti") as input, and returns the average number of stars for that company.
Use a list comprehension to run the function from part b on the list mycompanies, which should give the same values as in part a.

Submitting your Work

Please make sure that you added comments for each question, which explain your thinking about your method of solving each question. Please also make sure that your work is your own work, and that any outside sources (people, internet pages, generating AI, etc.) are cited properly in the project template.

If you have any questions or issues regarding this project, please feel free to ask in seminar, over Piazza, or during office hours.

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