Curso de PYTHON desde CERO (Completo)

Python is a widely used language in various fields including technology, science, and web development. It is known for its general-purpose programming capabilities and easy learning curve.

Python is a general-purpose programming language, high-level, and dynamically typed. It is easy to learn and understand, making it suitable for beginners and experienced programmers alike.

Learning Python can lead to various job opportunities and salary increases. It is a versatile language used in web development, artificial intelligence, data analysis, and more.

Python was created by Guido Van Rossum in 1991 with subsequent versions adding new features and improvements over the years. The language continues to evolve with updates and enhancements.

Variables in Python store data values that can be changed or updated throughout the program. Python allows for different data types like strings, integers, floats, and booleans to be stored in variables.

In Python, strings can be concatenated using various methods like the + operator or f-strings. Numbers can also be converted to strings for integration purposes in the code.

Explanation of variable declaration using the assignment operator and deletion using the 'del' operator in Python.

Introduction to case-sensitive language in Python and demonstration of conditional statements using 'if', 'else', and 'elif' statements.

Explanation and demonstration of lists and tuples as composite data types in Python.

Overview of sets and dictionaries as composite data types in Python, with examples of set creation and dictionary key-value pairs.

Explanation and demonstration of arithmetic operators such as addition, subtraction, multiplication, division, exponentiation, and modulus in Python.

Explanation and demonstration of comparison operators for comparing values in Python, returning 'true' or 'false' based on conditions.

Further explanation and demonstration of conditional statements including 'if-else' and 'if-elif-else' constructs in Python.

Explanation of how IF statements work in Python with examples of conditional checks based on income levels in different countries.

Demonstration of nested IF statements and the concept of putting an IF statement inside another IF statement for more complex conditions in Python programming.

Explanation of logical operators including AND, OR, and NOT in Python to combine conditions for decision making in programming.

Overview of string methods in Python, showing how to manipulate text such as converting to uppercase or lowercase, capitalizing letters, finding substrings, and replacing text within a string.

Demonstration of methods to search for specific characters within a string, count occurrences of characters, and check if a string is numeric or alphanumeric in Python.

Explanation of list methods in Python including creating lists, checking the length of a list, appending elements, extending lists, inserting elements, removing items by index or value, and more.

Demonstration of deleting items in a list and avoiding elimination of the entire list.

Explanation of sorting and reversing lists in Python, along with the functions sort() and reverse().

Discussion on using tuples, counting elements in tuples, and working with the count() function.

Explanation of using index and get methods in dictionaries to find elements and handle errors effectively.

Demonstration of clearing and popping items from dictionaries in Python.

Explanation of working with user inputs in Python and starting practical exercises to reinforce learning.

Introduction to the Python course and explanation of the content covered in the intermediate basic section.

Explanation of the variable unpacking technique in Python using tuples and lists.

Creation and manipulation of tuples in Python, focusing on their immutability and memory optimization.

Introduction to sets in Python, including creating sets and using frozen sets for nested sets.

Explanation of subset, superset, and disjoint sets in Python with examples.

Demonstration of different types of loops in Python including 'for' loops, iterating lists and tuples, and using 'else' in loops.

Iterating through dictionaries in Python and using the 'items' method to access keys and values.

Demonstration of advanced iteration techniques in Python using 'continue' and 'break' statements in loops.

The video introduces loops in programming, explaining concepts like looping through strings, creating lists of numbers, and iterating through characters. It also covers the 'for' loop, 'break' statements, and the 'else' clause within loops.

The 'while' loop is explained, detailing how it continues as long as the condition is true and how it can potentially lead to infinite loops. Practical examples and demonstrations are provided to illustrate its functionality.

The video delves into functions, emphasizing their significance in programming, the benefits of using functions to avoid code repetition, enhance modularity, and ease debugging. It covers the concept of abstraction in Python and the creation of custom functions.

Explains how to show the optimal form of using the args parameter in Python by putting numbers, using asterisks, and converting parameters into a list.

Describes the usage of the F-string parameter to return the sum of a list of numbers passed as arguments.

Demonstrates another way to pass a list but instead of running the sum asterisk numbers, it works the same way to find the total amount.

Illustrates the process of creating lists by requesting and displaying elements within the list using Python functions and parameters.

Guides on creating a function to determine prime numbers using nested loops and providing explanations on how the code works efficiently.

Explains the concept of modules in Python, categorizing them into programming, third-party, and own modules, and demonstrates the import and usage of modules within Python scripts.

Explained how to work with modules and namespaces in Python, including referencing functions as methods within a module and how to use namespaces effectively to avoid heavy and redundant code.

Demonstrated how to create, rename, import, and work with modules in Python, including renaming variables, importing specific functions, and understanding the best practices for module management.

Discussed how to import modules from folders, access module paths, and work with multiple modules within a directory structure, emphasizing the importance of organization and efficient importing methods.

Explained the concept of packages in Python, how to create and import packages, differentiate between modules and packages, and handle subpackages within a directory structure.

Covered the basics of file manipulation in Python, including reading, writing, and manipulating text files, understanding file formats, encoding, and the importance of proper file handling and resource management.

Demonstrates how to add lines to a file in Python, including creating a dialogue-like structure and running the program to see the results.

Discusses working with files in Python, including copying, deleting, overwriting, and appending data to files.

Shows how to create and read CSV files in Python using the pandas library, emphasizing the importance and advantages of using pandas over CSV for data analysis.

Explains how to install pandas, read CSV files using pandas, and manipulate data frames to perform data analysis effectively.

Covers data manipulation tasks in pandas such as accessing specific rows and columns, changing data types, replacing values, and handling missing or repeated data in data frames.

Introduces visualizing data using matplotlib and seaborn libraries to create line plots and bar charts based on the data in a CSV file.

The speaker discusses various sources of income including permanent work, freelance work, influencer work, advertising income, and investments in crypto.

The speaker explains how to create a graph showing different sources of income using bar plots instead of line plots for better representation.

The process of calculating the total income and displaying it along with the income sources in a print statement is described, along with troubleshooting errors in the program.

The speaker introduces a scatter plot, its uses, and the basics of object-oriented programming as a foundation for understanding data visualization techniques.

Details about object-oriented programming, including class, object, properties, behaviors, and its importance in software development are explained, with a recommendation for further learning.

A detailed explanation of exceptions, event handling, and creating custom exceptions using Python is provided along with practical examples and demonstrations.

The concept of regular expressions is introduced, covering various expressions, special characters, and their applications in searching and matching patterns within text data.

Explanation of various regular expression patterns like finding matches, replacements, and validations in text strings.

Details on using regular expressions to validate text strings, including specific examples like validating dates, phone numbers, and replacing characters.

Explanation of using regular expressions to validate email addresses based on specific patterns and criteria.

Demonstration of using regular expressions to validate URLs, including requirements like starting with 'HTTPS' and specific formats for validation.

Using regular expressions to validate text strings for specific country requirements, such as identifying a country code and hiding sensitive information like phone numbers.

Summary of the regular expressions section with a mention of available resources for further exploration and learning.

Discussion on the completion of the course, encouraging the application of knowledge in projects, and hinting at future content.