Difference between revisions of "Python Basics"
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==Hello World!== | ==Hello World!== | ||
This entry is the introduction of Python logic and syntaxt. You will know how to output text and interact with the Python environment, and understand how the code executes. This is the beginning of your code journey. | This entry is the introduction of Python logic and syntaxt. You will know how to output text and interact with the Python environment, and understand how the code executes. This is the beginning of your code journey. | ||
| − | [[Hello World!|''Go to the Hello World entry | + | [[Hello World!|''Go to the Hello World entry'']] |
==Types, Expression and Variables== | ==Types, Expression and Variables== | ||
| Line 17: | Line 17: | ||
Moreover, expressions in Python are used to perform operations and return values. Variables store data and can be assigned dynamically. In this entry, you will learn how to use the different data types by storing and manipulating data using expressions and variables. | Moreover, expressions in Python are used to perform operations and return values. Variables store data and can be assigned dynamically. In this entry, you will learn how to use the different data types by storing and manipulating data using expressions and variables. | ||
| − | [[Types, Expressions, and Variables in Python|Go to Types, Expression and Variables entry]] | + | [[Types, Expressions, and Variables in Python|''Go to Types, Expression and Variables entry'']] |
==String Operations== | ==String Operations== | ||
| − | Strings are a key data type in Python, especially in data analysis, where working with text data is common. Python provides many built-in methods for manipulating and analyzing strings, such as concatenation, slicing, and formatting. | + | Strings are a key data type in Python, especially in data analysis, where working with text data is common. Python provides many built-in methods for manipulating and analyzing strings, such as concatenation, slicing, and formatting. |
| + | [[String Operations|''Go to String Operations entry'']] | ||
==Conditional statements and branching== | ==Conditional statements and branching== | ||
| − | Conditional statements and branching allow programs to make decisions. Python’s if-else structure is used to execute code based on certain conditions, a fundamental concept in controlling the flow of a program. In other words, conditional statements are key in telling Python what you want it to do if certain condition is met or not. | + | Conditional statements and branching allow programs to make decisions. Python’s if-else structure is used to execute code based on certain conditions, a fundamental concept in controlling the flow of a program. In other words, conditional statements are key in telling Python what you want it to do if certain condition is met or not. |
| − | + | [[Conditions and Branching in Python|''Go to Conditional Statements and Branching entry'']] | |
| − | == [[Functions in Python|Functions]] == | + | ==Iteration and Loops== |
| + | Loops are an essential part of Python, enabling repeated execution of a block of code. They are frequently used in data processing tasks, making them indispensable for data science workflows.This entry covers the two primary types of loops in Python: | ||
| + | |||
| + | • For loops: Iterate over a sequence of items. | ||
| + | • While loops: Continue execution while a condition is true. | ||
| + | |||
| + | Moreover, there are also more complex arrangements of loops, such as nested loops and enumerate loops. | ||
| + | [[Loops in Python|''Go to the Iteration and Loops entry'']] | ||
| + | |||
| + | ==Functions== | ||
| + | Functions in Python are reusable blocks of code that perform specific tasks, allowing for better code organization and reducing redundancy. They can take inputs (called parameters), process them, and return outputs, making them highly flexible for handling various data operations. By defining custom functions, you can streamline workflows, automate tasks, and improve the readability and maintainability of your programs. | ||
| + | [[Functions in Python|''Go to the Functions entry'']] | ||
| + | |||
| + | ==References== | ||
| + | To be added soon | ||
| + | |||
| + | The author of this entry is J. Gustavo Rodriguez Aboytes | ||
| + | |||
| + | [[Category: Python]] [[Category: Python Basics]] | ||
Latest revision as of 12:53, 13 September 2024
EDITION MODE
Python provides a wide array of basic functions and commands that are essential for beginners in data analysis and science. These functions allow you to perform fundamental tasks like displaying output, handling user inputs, performing mathematical operations, and working with different types of data. By mastering these basic commands, you can efficiently manipulate data, automate repetitive tasks, and lay a solid foundation for more complex programming challenges. Whether you’re working with numerical data, text, or logical conditions, Python’s simple and intuitive syntax ensures that you can quickly grasp the essentials, making it a powerful tool for newcomers in data-driven fields. This page provides an overview of essential Python concepts and each section below links to a detailed entry covering the basic commands and functions in Python.
Contents
Hello World!
This entry is the introduction of Python logic and syntaxt. You will know how to output text and interact with the Python environment, and understand how the code executes. This is the beginning of your code journey. Go to the Hello World entry
Types, Expression and Variables
As in any other programming language, understanding type of data you are working with is fundamental. Python has several built-in data types, such as:
• Integers (int): Whole numbers. • Floating-point numbers (float): Decimal-point numbers. • Strings (str): Sequences of characters. • Booleans (bool): True/False values.
Moreover, expressions in Python are used to perform operations and return values. Variables store data and can be assigned dynamically. In this entry, you will learn how to use the different data types by storing and manipulating data using expressions and variables.
Go to Types, Expression and Variables entry
String Operations
Strings are a key data type in Python, especially in data analysis, where working with text data is common. Python provides many built-in methods for manipulating and analyzing strings, such as concatenation, slicing, and formatting. Go to String Operations entry
Conditional statements and branching
Conditional statements and branching allow programs to make decisions. Python’s if-else structure is used to execute code based on certain conditions, a fundamental concept in controlling the flow of a program. In other words, conditional statements are key in telling Python what you want it to do if certain condition is met or not. Go to Conditional Statements and Branching entry
Iteration and Loops
Loops are an essential part of Python, enabling repeated execution of a block of code. They are frequently used in data processing tasks, making them indispensable for data science workflows.This entry covers the two primary types of loops in Python:
• For loops: Iterate over a sequence of items. • While loops: Continue execution while a condition is true.
Moreover, there are also more complex arrangements of loops, such as nested loops and enumerate loops. Go to the Iteration and Loops entry
Functions
Functions in Python are reusable blocks of code that perform specific tasks, allowing for better code organization and reducing redundancy. They can take inputs (called parameters), process them, and return outputs, making them highly flexible for handling various data operations. By defining custom functions, you can streamline workflows, automate tasks, and improve the readability and maintainability of your programs. Go to the Functions entry
References
To be added soon
The author of this entry is J. Gustavo Rodriguez Aboytes
