Introduction

Now the dynamic part of programming starts, python comes with built-in data structure to organize the data type depending on the need and building more complex structures. Data structure can be classified as mutable and no mutable, ordered and non-ordered, and those that accept repleted elements.

Data structures

Depending on the situation, Python provides structures that allow you to access data more efficiently. For programs, accessing data is like searching for a book in a library shell, where you have to look through all the books to find the one you want, but instead of book shells is the memory allocation.

Python provides by default some data structures, they can be classified in mutable and nonmutable.

Let’s start with the mutable.

List

The list are not homogeneous dynamic arrays, which means that it can store different data types, and they can be modifiable after being created (add, remove, update, …). As vectors in CPP they are allocated in memory closely for fast access.

Defining a list it can be in two ways:

• list() function.
• Writing the variables between brackets separated by commas.

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a = [23, 45, 12, 67, 34]
a.append(89)
a.remove(45)
print(a)

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[23, 12, 67, 34, 89]

Tuple

A tuple is an object collection separated by commas. In some ways, a tuple is similar to a list in terms of indexing, nested objects, and repetition, but a tuple is immutable, unlike list that are mutable, as list they are capable of storing all kind of variable.

Defining a list it can be in two ways:

• tuple() function.
• Writing the variables between parentheses separated by commas.

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a = (23, 45, 12, 67, 34)
print(a)

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(23, 12, 67, 34, 89)

Set

A set is an unordered collection of unique elements. It is mutable, meaning you can add or remove elements (only regular sets), and it supports mathematical operations like union, intersection, and difference, they do not support duplicate variables.

Defining a list it can be in two ways:

• set() function.
• Writing the variables between braces separated by commas.

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a = {23, 45, 12, 67, 34}
print(a)

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{23, 12, 67, 34, 89}

To remove duplicates from lists, converting the list to set is a quick and efficient way to do so.

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a = [1, 2, 2, 3, 4, 4, 5]
u = set(a)
print(u)

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(1,2,3,4,5)

Set operations

Sets are ideal for performing mathematical operations like union, intersection, and difference, which are useful in fields like data analysis, database management, and computational biology.

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a = {1, 2, 3, 4}
b = {3, 4, 5, 6}
print("Union:", a | b)
print("Intersection:", a & b)
print("Difference:", a - b)

Union: {1, 2, 3, 4, 5, 6}
Intersection: {3, 4}
Difference: {1, 2}

Dictionary

Dictionary are an ordered 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. Dictionaries store data in key: value pairs. They are ideal for fast lookups and representing structured data.

Defining a list it can be in two ways:

• dict() function.
• Writing the key value follow for columns and the variable between braces separated by commas.

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thisdict = {
  "brand": "Ford",
  "electric": False,
  "year": 1964,
  "colors": ["red", "white", "blue"]
}
print(thisdict)

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{'brand': 'Ford', 'electric': False, 'year': 1964, 'colors': ['red', 'white', 'blue']}