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- Lists. Python Lists are just like the arrays, declared in other languages which is an ordered collection of data. It is very flexible as the items in a list do not need to be of the same type.
- Dictionary. Python dictionary is like hash tables in any other language with the time complexity of O(1). It is an unordered collection of data values, used to store data values like a map, which, unlike other Data Types that hold only a single value as an element, Dictionary holds the key:value pair.
- Tuple. Python Tuple is a collection of Python objects much like a list but Tuples are immutable in nature i.e. the elements in the tuple cannot be added or removed once created.
- Set. Python Set is an unordered collection of data that is mutable and does not allow any duplicate element. Sets are basically used to include membership testing and eliminating duplicate entries.
Jun 6, 2024 · At its core, a data structure is a method of organizing data that facilitates specific types of queries and operations on that data. We'll begin by covering linear data structures like arrays, lists, queues, and stacks.
- François Aubry
- Lists
- Dictionaries
- Sets
- Tuples
Lists in Python are implemented as dynamic mutable arrays which hold an orderedcollection of items. First, in many programming languages, arrays are data structures that contain a collection of elements of the same data types (for instance, all elements are integers). However, in Python, lists can contain heterogeneous data types and objects. For i...
Dictionaries in Python are very similar to real-world dictionaries. These are mutable data structures that contain a collection of keys and, associated with them, values. This structure makes them very similar to word-definition dictionaries. For example, the word dictionary (our key) is associated with its definition (value) in Oxford online dicti...
Sets in Python can be defined as mutable dynamic collections of immutable uniqueelements. The elements contained in a set must be immutable. Sets may seem very similar to lists, but in reality, they are very different. First, they may only contain unique elements, so no duplicates are allowed. Thus, sets can be used to remove duplicates from a list...
Tuples are almost identical to lists, so they contain an ordered collection of elements, except for one property: they are immutable. We would use tuples if we needed a data structure that, once created, cannot be modified anymore. Furthermore, tuples can be used as dictionary keys if all the elements are immutable. Other than that, tuples have the...
- Lists. Python Lists are ordered collections of data just like arrays in other programming languages. It allows different types of elements in the list. The implementation of Python List is similar to Vectors in C++ or ArrayList in JAVA.
- Tuple. Python tuples are similar to lists but Tuples are immutable in nature i.e. once created it cannot be modified. Just like a List, a Tuple can also contain elements of various types.
- Set. Python set is a mutable collection of data that does not allow any duplication. Sets are basically used to include membership testing and eliminating duplicate entries.
- Frozen Sets. Frozen sets in Python are immutable objects that only support methods and operators that produce a result without affecting the frozen set or sets to which they are applied.
Oct 1, 2024 · Learn about Python's built-in data structures and how to implement abstract structures like stacks, queues, hash tables, etc. Understanding these will enhance your problem-solving skills in Python and equip you with additional tools in your Python tool belt.
Aug 5, 2022 · Data Structures are fundamental building blocks of a programming language. It aims to provide a systematic approach to fulfill all the requirements mentioned previously in the article. The data structures in Python are List, Tuple, Dictionary, and Set. They are regarded as implicit or built-in Data Structures in Python.
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In this tutorial, you'll learn about Python's data structures. You'll look at several implementations of abstract data types and learn which implementations are best for your specific use cases.
