Python · Module 3

Data Structures

Take each lesson, answer its quiz, then do its practice. After the last lesson come the module quiz, the project and the interview questions.

Lessons

Module material

Take these after the last lesson, in this order. Next on each page leads through them.

Module quiz15 questions across the whole module. Take it after the last lesson; your first pick on each question is the one that counts.
Project: The Most Common Words in Product ReviewsStated as a problem, with no template and no step-by-step instructions. Working out the steps is the point.
NotebooksOpen them in Google Colab. Each answer is checked as you go: correct, wrong with the expected value, or not answered yet.
Cheat sheetLists, tuples, dictionaries and sets on one page: the terms, which structure to use, the syntax at a glance, the rules and the common mistakes. Free to read and share, no account needed.
Interview questions25 questions interviewers ask on data structures, from first principles to the follow-ups. The first 3 model answers are free to read; Pro opens the rest.

Glossary

Every term the module introduces, with the lesson that introduces it.

alias: A second name bound to the same object: after backup = cart, backup is an alias of cart. 3.1
element: One value stored in a list. 3.1
index: An element's position, counting from zero. A negative index counts from the end, from -1. 3.1
method: A function that belongs to an object, called with a dot: cart.append(...), review.lower(). 3.1
mutable: A type whose objects can be changed after they are created; a list is mutable, and so are sets and dictionaries. 3.1
mutation: Changing an object in place, which every alias sees: append, remove, sort, assigning to an index. 3.1
rebinding: Making an existing name refer to an object by assigning to that name. 3.1
shallow copy: A new outer collection that still refers to the original elements; nested mutable elements remain shared. 3.1
slice: A range of elements, from a start up to but not including a stop, with an optional step: temps[2:5], temps[::-1]. Slicing a list creates a new outer list; slicing a tuple or string returns the same type, possibly reusing an unchanged immutable object. 3.1
slice step: The spacing and direction used to select positions in a slice. 3.1
immutable: An object that can not be changed after it is created: a tuple, a string, a number. 3.2
packing: Collecting several values, separated by commas, into one tuple: point = 12.9716, 77.5946. 3.2
tuple: An ordered sequence of values, written with commas, that can not be changed: (12.9716, 77.5946). 3.2
unpacking: Binding each item of a sequence to its own name, in order: lat, lon = point. 3.2
difference: The values in the first set that are not in the second, a - b. 3.3
frozenset: An immutable, hashable set: frozenset({1, 2}). 3.3
hash: A number Python computes from a value, which a set uses to decide where the value is stored. A dictionary uses its keys' hashes in the same way. 3.3
hashable: A value whose hash stays stable during its lifetime and whose equal values have equal hashes, so it can be a set member or dictionary key: numbers, strings, and tuples of hashable values. Lists, sets and dictionaries are not. 3.3
intersection: Every value in both sets, a & b. 3.3
KeyError: The exception for a missing dictionary key or an absent member passed to set.remove. 3.3
set: An unordered collection in which each value appears at most once. An empty set is set(). 3.3
Counter: A dictionary that counts; a missing key counts zero. Counter(votes).most_common(1) gives [('tea', 3)]. From collections. 3.4
defaultdict: A dictionary that creates a missing key's value when the key is read: defaultdict(list) creates []. From collections. 3.4
dictionary: A collection of key value pairs, looked up by key: {"Pasta": 12.50, "Salad": 8.25}. Its type is dict. 3.4
insertion order: The order keys were first added to a dictionary; updating a value preserves its position. 3.4
key: What a dictionary looks a value up by, such as "Pasta" in the menu. Each key appears once, and must be hashable. 3.4
key value pair: One entry of a dictionary: a key and its value, written "Pasta": 12.50. 3.4
nested dictionary: A dictionary whose values are dictionaries: cafe["drinks"]["Juice"]. 3.4
value: What a dictionary stores for each key, such as 12.50 for "Pasta". Values can be anything, including lists and dictionaries. 3.4
chaining: Calling a method on the value the previous method returned: review.strip().lower(). 3.5
iterator: An object that yields its items one at a time when asked for the next item. 3.5
palindrome: Text that reads the same forwards and backwards. 3.5
separator: Text used between fields when splitting or joining strings. 3.5
string: An immutable sequence of characters, indexed and sliced like a list. 3.5
substring: A contiguous sequence of characters within a string. 3.5
token: One of the pieces tokenisation produces. Our tokeniser lowercases text, removes only ., ,, ! and ?, then splits on whitespace; other punctuation may remain. 3.5
tokenisation: Splitting text into pieces. Language models split into subword pieces; the video's tokeniser splits on whitespace. 3.5
tokeniser: A procedure that splits text into tokens. 3.5
Unicode: The standard for representing characters in Python strings; one indexed item is one code point and may be only part of a displayed character. 3.5
whitespace: Spacing characters such as spaces, tabs and newlines. 3.5
dictionary comprehension: A dictionary built from a key and a value evaluated for each item: {item: price for item, price in zip(items, prices)}. 3.6
filter: A condition that determines which items are included. 3.6
generator expression: An expression that yields values on demand, such as sum(s for s in week if s >= 10000), without building a list first. 3.6
list comprehension: A list built from an expression evaluated for each item of an iterable: [round(p * 1.08, 2) for p in prices], with an optional if at the end to filter. 3.6
scope: The region of a program in which a name is available; a comprehension's loop variable has its own scope. 3.6
set comprehension: A set built from an expression evaluated for each item: {len(item) for item in items}. 3.6
side effect: An action such as printing or mutating an object, beyond producing a return value. 3.6