CSE 160 Section 6

Midterm Review!

Logistics

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Midterm: Friday Oct. 31

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• HW3 due October 31
• Submitting on Gradescope
• Wait for autograder!
• Resubmissions due Friday Oct 31 @ 11PM
• Don’t forget to fill out the resubmission form!
• Written Check-in 5 due Friday Oct 31
• Coding Practice 5 due Sunday Nov 2

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Lecture Review: File I/O

File I/O

my_file = open(filepath)

for line_of_text in my_file:

# process line_of_text

my_file.close()

Split

• Split can be a really helpful function when dealing with strings (which is what you’re processing in file i/o)

Example:

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Output:

line_of_text = “you’re going to be amazing”

x = line_of_text.split()

print(x)

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[“you’re”, “going”, “to”, “be”, “amazing”]

Split

• If you give split an argument, it will split the line of text on that. If you don’t give it anything, it will by default split on spaces.

Example:

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Output:

line_of_text = “you’re,going,to,be,amazing”

x = line_of_text.split(“,”)

print(x)

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[“you’re”, “going”, “to”, “be”, “amazing”]

Lecture Review: Dictionary

Dictionary

Collection of key-value pairs

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• Key type must be immutable and keys must be unique

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• Key-value pair order doesn’t matter (dictionaries are unordered)

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• Access value from a key using index syntax (square brackets)

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• If you try to access a key not that doesn’t exist in the dictionary, it will throw an error

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Dictionary

heights = {"Ella": 68,

"Martin": 72,

"Lilly": 49,

"William": 50,

"Simon": 70}

print(heights["Lilly"]) # 49

print(heights["Wen"]) # KeyError

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heights["Wen"] = 63 # Add a key-value pair

heights["Lilly"] = 50 # Update value

print(heights["Lilly"]) # 50

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Dictionary

# print out all keys

for key in heights.keys():

print(key)

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# print out all values

for value in heights.values():

print(value)

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# print out keys and values

for (key, value) in heights.items():

print(key, value)

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# another method

for key in heights:

value = heights[key]

print(key, value)

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Lecture Review: Nested Structures

Review of nested structures

• So far you have seen lists and dictionaries.
• There are ways to combine them into nested structures in order to represent different types of data.

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Review of nested structures

• Why do we care about nested structures?
• A lot of the data that we work with in real life come in tables, which cannot be represented by a single list or dictionary

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Nested Lists

• Useful for representing data in which only the order matters.
• Can be multidimensional.
• Used in HW 3 for image data (how would you represent color images?)

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Midterm Review Questions?

Practice Questions

Problem A

Write a function called report_long_lines that takes a string file_name and an integer max_length as arguments. It should return the number of lines that were longer than the given length.You may assume the file name provided describes a file that exists.

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Example:

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numbers.txt:

one

two

three

four

five

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print(report_long_lines(“numbers.txt”, 3)) Output: 3

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Solution A

def report_long_lines(file_name, max_length):

num_lines = 0

f = open(file_name, "r")

for line in f:

if len(line) > max_length:

num_lines += 1

close(f)

return num_lines

Problem B

Write code that would loop over this list and create a list of the last names of only the female patients.

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Should return ['Chan', 'Ross']

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Python Tutor

Solution B

female_patients = []

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for solo_patient in patients:

if solo_patient[3] == ‘female’:

female_patients.append(solo_patient[1])

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print(female_patients)

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Problem C

Now write code to restructure the list so that the inner lists each contain all of the data of one type i.e. first name, last name , etc

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Should return

[ ['Milos', ‘Delia’, ‘Denise’],

[‘Jones’, ’Chan’, ‘Ross’],

[48, 39, 62],

….

[210, 170, 150]]

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Problem C

Now write code to restructure the list so that the inner lists each contain all of the data of one type i.e. first name, last name , etc

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new_list = []

For i range(len(patients[0]))

Data_list = []

For patient in patients:

Data_list.append(patient[i])

new_list.append(Data_list)

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