CSE 160 Section 6

Sets and Nested Dictionaries!

TA1 & TA2

How Was the Midterm?

(People have not taken the exam to we won’t provide answers yet)

Logistics

• Coding Activity 5 (due Friday November 1)

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• HW4 Part 1 (due Friday October 28)
• No resubmission for Hw 4 Part 1
• If you want to resubmit, wait until Part 2 is due, the resubmissions will open then
• HW4 Part 2 (due Friday November 8)
• Submitting on Gradescope
• Wait for autograder!

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Lecture Review: Sets

Sets

• Sets are a type of data structure which is unordered and unindexed
• There can be no duplicates
• Imagine it as a “bag of values”

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You can imagine a set that contains the values 1 through 6 like this:

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Sets

You can imagine a set that contains the values 1 through 6 like this:

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s = set([1, 2, 3, 4])

s = {1, 1, 1, 1, 1, 1, 2, 3, 4}

s = {1, 2, 3, 4}

s = set()

s.add(1)

s.add(2)

s.add(3)

s.add(4)

Add, Remove, and Discard

Say we have the set s that has elements 1, 2, 3, 4 inside

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Add

• adds an element to the set
• s.add(5)

Remove

• takes out an existing element from the set (Must exist in the set!)
• s.remove(5)

Discard

• takes out an element from the set (doesn’t need to be in there already)
• s.discard(5)

Pop

• Returns a random element
• s.pop()
• Could return 1, 2, 3, or 4

Sets

• Although you can convert any data structure into a set, you can only add immutable types into a set (just like dict keys)
• Data types that can not go in a set (mutable types)
• Dictionaries
• Lists
• other sets
• Data types that can go in a set (immutable types)
• Integers
• Floats
• Booleans (but why would you do this?)
• Strings
• Tuples

Looping Through a Set

To see all elements in a set, we can loop through it

Would print 1, 2, 3, 4 in some random order

for element in s:

print(element)

Checking If Something Is In A Set

We can use in to see if an element is in a set

Returns True

Returns False

2 in s

6 in s

Set Operations

A | B

A & B

A - B

A ^ B

Set Operations

Lecture Review: Nested Dictionaries

Lists of Dictionaries

• List of dictionaries:
• [{‘a’ : 1, ‘b’ : 2, ‘c’ : 3}, {‘a’ : 4, ‘b’ : 5, ‘c’ : 6}, {‘d’ : 1, ‘e’ : 2, ‘f’ : 3}]
• They might be used to represent a table (e.g. an excel file)
• Where each item in the list in the dictionary is a row in the table
• In this version, each dictionary should have the same keys 
• Example:
• [{‘County’ : ‘King’, ‘Population’ : 2269675, “Temperature” : 57}, {‘County’ : ‘Pierce’, ‘Population’ : 921130, “Temperature” : 61}, {‘County’ : ‘Snohomish’, ‘Population’ : 827957, “Temperature” : 53}]

Nested Dictionaries

• Dictionaries themselves can hold mutable elements as values which means we can put a dictionary inside a dictionary

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• {“dict_1” : {“a” : 1, “b” : 2, “c” : 3}, “dict_2” : {“a” : 5, “b” : 4, “c” : 3}, “dict_3” : {“a” : 1, “b” : 2, “c” : 3}}
• Can have duplicate values

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• This can be used to better categorize data, transforming the list of dictionaries

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• {‘King’ : {‘Population’ : 2269675, ‘Temperature’ : 57}, ‘Pierce’ : {‘Population’ : 921130 , ‘Temperature’ : 61}, ‘Snohomish’ : {‘Population’ : 827957 , “Temperature” : 53}}

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• Can now easily find information based on county instead of traversing through a list

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Section Handout Problems

Problem 1

Write a function called all_unique_words(file_name) that takes in a string file_name and returns the number of unique words in the file. You may use the split() function for this problem, which takes in a string and returns a list of the words in the string separated by empty spaces.

Example:

If colors.txt has the content "red green blue green"

Your output should be: 3

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Problem 1

def all_unique_words(file_name):

file = open(file_name):

words = file.read()

unique = set(words.split())

file.close()

return len(unique)

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Problem 2

Write a function called sum_dict(nested_dict) that, given a dictionary of dictionaries, creates a single dictionary containing the sums of values with the same key in the given dictionaries.

For example: Given this list of dictionaries:

{“dict_1” : {"b": 10, "a": 5, "c": 90},

“dict_2” : {"b": 78, "a": 45},

“dict_3” : {"a": 90, "c": 10}}

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Your code should create : {"b": 88, "a": 140, "c": 100}

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Python Tutor

Problem 2

def sum_dict(nested_dict):

new_dict = {}

for inner_dict in nested_dict.values():

for key in inner_dict:

if key not in new_dict:

new_dict[key] = 0

new_dict[key] += inner_dict[key]

return new_dict

Problem 3

Write a function called reformat_dict(dict_list, new_key) that when given a list of dictionaries and a key returns a dictionary of dictionaries with the keys being the value of the given key for each dictionary and the value being a dictionary with the rest of the information.

For example, given: key = “County”

nested_dict = [{"County": "King", "Population": 2269675, "Temperature": 57},{"County": "Pierce", "Population": 921130, "Temperature": 61},{"County": "Snohomish", "Population": 827957, "Temperature": 53}]

Your code should produce:

{‘King’ : {‘Population’ : 2269675, ‘Temperature’ : 57}, ‘Pierce’ : {‘Population’ : 921130 , ‘Temperature’ : 61}, ‘Snohomish’ : {‘Population’ : 827957 , “Temperature” : 53}}

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Python Tutor

Problem 3

def reformat_dict(dict_list, new_key):

new_dict = {}

for inner_dict in dict_list:

current_key = inner_dict[new_key]

new_dict[current_key] = {}

for key in inner_dict:

if key != new_key:

new_dict[current_key][key] = inner_dict[key]

return new_dict

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Problem 4

Given a file.csv that looks like the following, write code that reads the data into a nested dictionary, where the first entry is the outer key, the second entry is the inner key, and the third entry is the value of the inner dictionary. You can ignore the header when reading in the file.

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# Sample CSV:

State, City, Population

Washington, Seattle, 733919

Oregon, Portland, 641162

California, San Francisco, 815201

Michigan, Detroit, 632464

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Example Output:

{“Washington”: {“Seattle”: 733919}, “Oregon”: {“Portland”: 641162}, {“California”: {“San Francisco”: 815201}, “Michigan”: {“Detroit”: 632464}}

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Python Tutor

Python Tutor Snippet:

import io

file = io.StringIO("""Washington, Seattle, 733919

Oregon, Portland, 641162

California, San Francisco, 815201

Michigan, Detroit, 632464""")

Problem 4

def read_data(file_name):

nested_dict = {}

file = open(example.txt)

for line in file:

data = line.split()

inner_dict = {}

inner_dict[data[1]] = data[2]

nested_dict[data[0]] = inner_dict

file.close()

return nested_dict