Master Python Lists, Dictionaries, Tuples, and Sets: Essential Operations

List

In Python, a list is an ordered, mutable collection that can hold any type of object, including other lists, dictionaries, or tuples.

Ordered collection accessed by index

Supports heterogeneous elements and nesting

Mutable: items can be added, removed, or changed in place

Common List Operations

Concatenation: list1 + list2 joins two lists

Repetition: list * 3 repeats the list three times

Iteration: for i in list: print(i) Membership test: 3 in list Index lookup: list.index(1) Count occurrences: list.count(1) Slicing: list[1:3] creates a new sub‑list

Length:

len(list)

Basic List Creation

>> list=[]
>>> list=[1, 2, '3', []]
>>> list
[1, 2, '3', []]

Indexing and Slicing

>> list[1]
2
>>> list[0:3]
[1, 2, '3']

Repeating a List

>> list*3
[1, 2, '3', [], 1, 2, '3', [], 1, 2, '3', []]

In‑place Modification

>> food=['spam', 'eggs', 'milk']
>>> food[1] = 'Eggs'
>>> food
['spam', 'Eggs', 'milk']

List Methods

Append: food.append('cake') Sort: food.sort() Extend (merge): list1.extend(list2) Pop: list1.pop() Reverse: list1.reverse() Insert: list.insert(2, 10) Delete: del list[2] Index:

list.index(3)

Dictionary

A dictionary is an unordered collection of key‑value pairs where keys must be immutable and unique.

Access by key rather than position

Mutable: values can be added, updated, or removed

Keys can be any immutable type (strings, numbers, tuples)

Basic Dictionary Operations

>> dict={'a':97,'b':98}
>>> len(dict)
2
>>> print("ascii code of 'a' is {}, ascii code of 'b' is {}".format(dict['a'], dict['b']))
ascii code of 'a' is 97, ascii code of 'b' is 98

Key Presence

>> 'a' in dict
True
>>> dict.get('c', 'none')
'none'

Updating Values

>> food={'eggs':3,'ham':1,'spam':4}
>>> food['ham'] = 2
>>> food['branch'] = ['bacon', 'bake']
>>> del food['eggs']
>>> food
{'ham': 2, 'spam': 4, 'branch': ['bacon', 'bake']}

Dictionary Methods

get: safe retrieval with default

pop: remove and return a value

clear: empty the dictionary

update: merge another mapping

Tuple

A tuple is an ordered, immutable collection. Because it cannot be changed, it is often used for fixed‑size groups of items.

Ordered and indexable

Immutable: no in‑place modifications

Can contain heterogeneous elements and be nested

Creating Tuples

>> tuple=()
>>> tuple=(1,)
>>> type(tuple)
<class 'tuple'>
>>> tuple=(1,2,'3',(4,5))
>>> tuple
(1, 2, '3', (4, 5))

Conversion from List

>> lst=[1,2,3,4]
>>> tup=tuple(lst)
>>> tup
(1, 2, 3, 4)

Tuple Operations

Concatenation: (1,2)+(3,4) Repetition: (1,2)*3 Index lookup: tup.index(3) Count: tup.count(3) Slicing works like lists

Set

A set is an unordered collection of unique, hashable elements. Sets support mathematical operations such as union, intersection, and difference.

Unordered, no duplicate elements

Elements must be immutable

Useful for membership testing and eliminating duplicates

Creating Sets

>> s=set('a')
>>> a=set({'k1':1,'k2':2})
>>> c={'a','b','c'}
>>> d=('a','b','c')  # tuple, not a set

Set Operations

Difference: a.difference(b) Intersection: a.intersection(b) Union: a.union(b) Symmetric difference: a.symmetric_difference(b) Subset / Superset checks: a.issubset(b), a.issuperset(b) Update (in‑place union): a.update(b) Discard / Remove / Pop for element deletion

>> a={1,2,3,4}
>>> b={3,4,5,6}
>>> a.intersection(b)
{3, 4}
>>> a.union(b)
{1, 2, 3, 4, 5, 6}
>>> a.difference(b)
{1, 2}
>>> a.symmetric_difference(b)
{1, 2, 5, 6}
>>> a.update(b)
>>> a
{1, 2, 3, 4, 5, 6}

Conversion

>> a=set(range(5))
>>> li=list(a)
>>> tup=tuple(a)
>>> st=str(a)
>>> print(li)
[0, 1, 2, 3, 4]
>>> print(tup)
(0, 1, 2, 3, 4)
>>> print(st)
{0, 1, 2, 3, 4}