Homework 7:
Files
CS-UY 1114 NYU Tandon
Your submission for this assignment must be via Gradescope.
Submit your solution to all problems in a single file named YourNetID_hw7.py
Your submitted file must start with the mandatory comment header, containing you
name, the class number, the date, and the homework number.
Your submitted code may use only the material that we’ve covered so far this semester.
Download the file colleges.csv from Classes. Place it in the same folder as your Python
program. If you find that your program is not able to access the file, make sure that it is
in the same folder.
Problem 1
You are given a file colleges.csv, containing a data set of all US colleges and universities.
Open this file in a spreadsheet program (e.g. Microsoft Excel, Li
eOffice Calc, Apple
Numbers, etc) and take a look at its contents. Notice which data are provided for each
college. Some of this data will be relevant to this assignment, and some won’t. Notice
the headers in the first row. For example, the SAT_AVG column indicates the average SAT
score for that college. Not all colleges release that information, so some colleges have the
special value NULL instead.
Now open the same file in a text editor (e.g. IDLE, Notepad, TextEdit, SublimeText,
etc) and notice how its data is represented. You’ll see that the first line in the file consists
of a sequence of comma-separated column headers. Subsequent lines in the file contain
comma-separated values. The position of an element in a row matches the co
esponding
header: for example, the fifth column header is CITY, so the fifth value in each row
indicates the college’s city. The lines are very long and may wrap around to fit in the
windows, but they are still just one line!
Write a function read_file with the following header:
def read_file(filename):
"""
sig: str -> list(list(str))
Loads the named file and returns all data rows in the file as
a list of lists of strings.
"""
Your function should open the file named in its parameter, skip over the header row,
parse the remaining lines into a list of strings, and return a list of all such lists.
The list returned by your function should not include the header row.
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For example:
colleges = read_file("colleges.csv") # read the file into a variable
somecollege = colleges[50] # select college at row 50
print(somecollege[3]) # print the college's name
Snead State Community College
print(somecollege[6]) # print the college's zip code
XXXXXXXXXX
Test your code thoroughly. Make sure that it works as shown above.
Don’t forget to close the file after reading it!
Hint: open the file in read mode using open, then use a for loop to iterate through each
line in the file. Then use the split method to separate each line into a list of values.
Problem 2
Write a function with the following signature:
def find_most_exclusive_womens_college(colleges):
"""
sig: list(list(str)) -> st
Returns the name of the women's college with the lowest
admission rate
"""
That is, your function takes the data structure produced by read_file and finds the
name of the women’s college with the lowest admission rate. A college will have a 1 in
the WOMENONLY column if it’s a women’s college. The admission rate for a college is given
as a float in the ADM_RATE column.
For example:
colleges = read_file("colleges.csv")
print("The most selective women's college is "+find_most_exclusive_womens_college(colleges))
Hint: you’ll have to iterate through all colleges (using a for loop) and keep track of what
is the lowest admission rate you’ve seen so far. Every time you find a lower admission
ate, you’ll also need to keep track of the name of the college.
Problem 3
Write a function with the following signature:
def average_sat_score_in_ny(colleges):
"""
sig: list(list(str)) -> float
Returns the value of the average SAT score of all
colleges in New York
"""
That is, your function takes the data structure produced by read_file and finds the
average of all average SAT scores of all colleges located in the state of New York. The
STABBR field tells you the state of a college, and its SAT_AVG field tells you its average
SAT score. Not all colleges release their SAT scores, so you should skip over colleges if
the SAT score column contains NULL.
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Hint: you’ll have to iterate through all colleges (using a for loop) and sum up the total
of all SAT scores, then divide by the number of schools that provide an SAT score.
Problem 4
Write a function with the following signature:
def distance(first , second):
"""
sig: tuple(float , float), tuple(float , float) -> float
Returns the Cartesian distance between two points , expressed
as a latitude/longitude pai
"""
That is, given two tuples, each containing a pair of floats representing the latitude and
longitude of a point on Earth, calculate their Cartesian distance. You can use the usual
formula:
? = √(?1 − ?1)2 + (?2 − ?2)2
For example, given the location of New York City and Los Angeles:
print(distance XXXXXXXXXX, XXXXXXXXXX), XXXXXXXXXX, XXXXXXXXXX)))
XXXXXXXXXX
Problem 5
Write a function with the following signature:
def find_college_nearest_center_of_us(colleges):
"""
sig: list(list(str)) -> st
Returns the name of the college nearest the
geographical center of the contiguous United
States
"""
The geographical center of the contiguous United States is located at the latitude/lon-
gitude position XXXXXXXXXX, XXXXXXXXXXThe location of each college is given in the
LATITUDE and LONGITUDE columns. Find which college is nearest the geographical cente
of the US.
Not all colleges provide their location, so if either of the position columns contain NULL,
skip over that college.
Hint: use your distance function.
Hint: you’ll have to iterate through all colleges (using a for loop) and keep track of what
is the college nearest to the center point. Every time you find a nearer college, you’ll also
need to keep track of the name of the college.
Problem 6
Tying together all the code you’ve written in this assignment, write a function main that
calls the read_file function to load the file colleges.csv and then prints out the result
of the other functions you’ve written. When run, the final output should look like this:
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Most exclusive women 's college: [college name here]
Average SAT of all NY schools: [number here]
College nearest geographical center of contiguous US: [college name here]
Your main function should call read_file only once.
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