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Study guide · Python

Python Lists: Slicing, Methods, and Comprehensions for Exams

Lists are the most-tested Python data structure. Here's what exams focus on — slicing syntax, mutating methods, and comprehensions.

Examifyr·2026·5 min read

Creating lists and accessing elements

Lists are ordered, mutable sequences. Indexing starts at 0. Negative indexes count from the end.

items = [10, 20, 30, 40, 50]

print(items[0])   # 10  (first)
print(items[-1])  # 50  (last)
print(items[-2])  # 40  (second from last)

Slicing — the syntax that trips everyone up

Slice syntax is list[start:stop:step]. The stop index is excluded. Omitting start defaults to 0; omitting stop defaults to the end of the list.

nums = [0, 1, 2, 3, 4, 5]

print(nums[1:4])    # [1, 2, 3]  — stop is excluded
print(nums[:3])     # [0, 1, 2]
print(nums[2:])     # [2, 3, 4, 5]
print(nums[::2])    # [0, 2, 4]  — every 2nd item
print(nums[::-1])   # [5, 4, 3, 2, 1, 0]  — reversed

Notenums[::-1] is the idiomatic way to reverse a list. Memorise this — it appears in nearly every Python exam.

Key list methods

Know which methods modify the list in place and which return a new value.

lst = [3, 1, 4, 1, 5]

lst.append(9)       # adds to end — returns None
lst.extend([2, 6])  # adds multiple items — returns None
lst.insert(0, 0)    # insert at index — returns None
lst.pop()           # removes and returns last item
lst.pop(0)          # removes and returns item at index
lst.remove(1)       # removes first occurrence of value
lst.sort()          # sorts in place — returns None
new = sorted(lst)   # returns new sorted list
lst.reverse()       # reverses in place — returns None

Noteappend(), sort(), and reverse() all return None. A common trap: lst = lst.sort() sets lst to None.

List comprehensions

A list comprehension builds a new list in a single readable expression. It can include a filter condition.

# Basic
squares = [x**2 for x in range(5)]
# [0, 1, 4, 9, 16]

# With filter
evens = [x for x in range(10) if x % 2 == 0]
# [0, 2, 4, 6, 8]

# Nested
matrix = [[i * j for j in range(3)] for i in range(3)]
# [[0,0,0], [0,1,2], [0,2,4]]

Shallow vs deep copy

Assigning a list to a new variable doesn't copy it — both variables point to the same object.

a = [1, 2, 3]
b = a           # same object
b.append(4)
print(a)        # [1, 2, 3, 4]  — a was modified!

c = a.copy()    # shallow copy
c.append(5)
print(a)        # [1, 2, 3, 4]  — a unchanged

NoteFor nested lists, use copy.deepcopy() to avoid shared references inside the list.

Exam tipSlice notation is the single most-tested list topic. Practice [start:stop:step] until nums[::-1] and nums[1:4] are instinctive. Also memorise that sort() returns None.

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