Python Collections

Python has built-in Collections which are used to store data, for example, lists, dictionaries, sets, and tuples, all of which are built-in collections.

The following are the differences between each of these collections.

	Lists	Tuples	Sets	Dictionaries
Ordered	Yes by index	Yes by index	No	Yes by key
Allow duplicates	Yes	Yes	No	Yes
Mutable	Yes	No	Yes	Yes
Slicing	Yes	Yes	No	No
Change of element	Yes	No	No	Yes
Represented by	[ ]	( )	( )	{ }
example	[1, 2, 3, 'four', 5]	​('gfg', 1, ['is', 'best'])	{1, 2, 3, 4, 5}	{1:"a", 2:"b", 3:"c"}

The above-mentioned collections have different actions.

Let's go through each of them.

	Lists	Tuples	Sets	Dictionaries
Initiate	l = []	t = ()	a = set()	d = {}
Add	l.append(2)		s.add(2)	d[0] = "One"
Remove	l.pop()		s.remove(2)	del d[0]

Let's see the time complexity of each of these collections.

	List	Tuple	Set	Dictionary
Addition	O(1)	-	O(1)	O(1)
Deletion	O(n)	-	O(1)	O(1)
Access by index	O(1)	O(1)	-	O(1)
Check inclusion	O(n)	O(n)	O(1)	O(1)
Get length	O(1)	O(1)	O(1)	O(1)

As a summary let's see which is best to use and where.

List	Tuple	Set	Dictionary
Used in JSON format. Useful for Array operations. Used in Databases.	Used to insert records in the database through SQL query at a time. Used in parentheses checker. More memory & time efficient compared to list. Can have various data types.	Finding unique elements Join operations	Used to create a data frame with lists Used in JSON