Learn Python from scratch: Complete Guide

Learn Python from scratch: With this complete guide for beginners

In this article, we will explore the Python worldPython, a versatile and powerful programming language that has gained popularity in recent years. The aim of this article is to provide a comprehensive introduction to Python, from its installation and configuration to its use in different areas such as web programming, artificial intelligence and data analysis.

What is Python and why learn it?

Python is a high-level, interpreted programming language characterized by its clear and readable syntax. It was created by Guido van Rossum in the 1990s and has since gained a large following due to its ease of use and wide range of applications.

One of Python's main features is its focus on code readability, which makes it ideal for beginners in programming. In addition, Python has a large number of libraries and modules that facilitate the development of applications in different areas, such as data analysis, artificial intelligence and web development.

Learning Python is important in today's world because it has become one of the most popular and in-demand languages in the industry. Many companies use Python to develop web applications, perform data analysis and build artificial intelligence models. In addition, Python is used by scientists and researchers to conduct research and experiments because of its ease of working with data.

Installation and configuration of the development environment

Before you can start programming in Python, you need to install it on your operating system. Fortunately, Python is compatible with most operating systems, including Windows, macOS and Linux.

To install Python on Windows, we can download the installer from the official Python website and follow the steps in the installation wizard. On macOS, Python comes pre-installed, but it is recommended to install the latest version using the Homebrew package manager. On Linux, we can install Python using the package manager of our distribution.

Once we have Python installed, it is important to set up our development environment. We can use a simple text editor such as Notepad++ or Sublime Text, or use an integrated development environment (IDE) such as PyCharm or Visual Studio Code. In addition, it is advisable to use a package management system such as pip to install additional libraries and modules.

Basic Python syntax: variables, operators and control structures

The basic syntax of Python is quite simple and easy to understand. In Python, we can declare variables without specifying their type, since Python is a dynamically typed language.

For example, we can declare a variable called "name" and assign a value to it:

name = "Juan"

In addition to variables, Python also has a wide range of arithmetic, logical and relational operators that allow us to perform calculations and comparisons. For example, we can add two numbers using the "+" operator:

result = 10 + 5

Python also has control structures such as loops and conditionals that allow us to control the flow of the program. For example, we can use a for loop to iterate over a list of items:

for i in range(5):
print(i)

Python functions and modules

Functions are reusable blocks of code that allow us to perform a specific task. In Python, we can define our own functions using the "def" keyword. For example, we can define a function that adds two numbers together:

def sum(a, b):
return a + b

In addition to functions, Python also has a wide range of modules and libraries that allow us to extend the functionality of the language. For example, we can use the "math" module to perform more advanced mathematical operations:

import math

result = math.sqrt(25)

Working with files and directories in Python

Python allows us to read and write text files using the built-in "open" and "write" functions. For example, we can open a file named "data.txt" in write mode and write a line of text:

file = open("data.txt", "w")
file.write("Hello, world!")
file.close()

In addition to working with files, Python also allows us to manipulate directories and files on the system using the "os" module. For example, we can create a directory called "data" using the "mkdir" function:

Import

os.mkdir("data")

Object-oriented programming in Python

Object-oriented programming (OOP) is a programming paradigm based on the creation of objects that interact with each other. In Python, we can use classes and objects to implement OOP.

A class is a template that defines the properties and methods of an object. For example, we can define a class called "Person" with properties such as name and age, and methods such as greet:

class Person:
def __init__(self, name, age):
self.name = name
self.age = age

def greet(self):
print("Hello, my name is", self.name).

To create an object of the "Person" class, we simply call the constructor of the class and pass the values of the properties:

person = Person("John", 25)
person.greet()

Data Manipulation with Pandas and NumPy

Pandas and NumPy are two popular Python libraries that allow us to work with data efficiently. Pandas provides us with flexible data structures and tools for data analysis, while NumPy allows us to perform numerical calculations efficiently.

For example, we can use Pandas to read a CSV file and perform operations such as filtering and data aggregation:

import pandas as pd

data = pd.read_csv("data.csv")
filtering = data[data[data["age"] > 18]]
aggregation = filtered.groupby("city").mean()

Creating graphics and visualizations with Matplotlib

Matplotlib is a Python library that allows us to create graphs and visualizations in a simple way. With Matplotlib, we can create line, bar, scatter and many other types of graphs.

For example, we can use Matplotlib to create a line chart showing the evolution of sales over time:

import matplotlib.pyplot as plt

sales = [100, 150, 200, 200, 250, 300]]
months = ["January", "February", "March", "April", "May"]

plt.plot(months, sales)
plt.xlabel("Months")
plt.ylabel("Sales")
plt.title("Evolution of sales")
plt.show()

Result

Web development with Flask and Django

Flask and Django are two popular frameworks in Python that allow us to develop web applications quickly and easily. Flask is a minimalist framework that focuses on simplicity and flexibility, while Django is a more complete framework that includes many additional features.

For example, we can use Flask to create a simple web application that displays a welcome message:

from flask import Flask

app = Flask(__name__)

@app.route("/")
def index():
return "Hello, world!"

if __name__ == "__main__":
app.run()

Introduction to artificial intelligence and machine learning in Python

Artificial intelligence (AI) and the automatic learning (AA) are areas of computer science that focus on developing algorithms and models that can learn and make decisions autonomously. In Python, we can use libraries such as TensorFlow and Keras to develop AI and AI models.

For example, we can use TensorFlow to train an image recognition model:

import tensorflow as tf

# Code to train the model...

Resources and communities to continue learning Python

Learning Python is an ongoing process, as there are always new techniques and tools to discover. Fortunately, there are many online resources that can help us continue learning Python.

Some recommended resources include online tutorials, specialized books, online courses and official documentation. In addition, there are also online communities and forums where we can solve doubts and share knowledge with other programmers.

At this page you can find solved Python exercises to take as a guideline

Conclusion

In short, Python is a versatile and powerful programming language that has become an indispensable tool in today's world. Throughout this article, we have explored different aspects of Python, from its installation and configuration to its use in areas such as web programming, artificial intelligence and data analysis.

We hope this article has been helpful to those who wish to learn Python or expand their knowledge of the language. As you continue to learn and explore Python, you will discover that the possibilities are endless and there is always something new to discover. Keep learning and enjoying Python!