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Introduction

Python is a powerful, versatile programming language that’s perfect for data science. This module covers the essential building blocks you’ll need to start writing Python code.

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Variables and Data Types

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Understanding Variables

Variables in Python are used to store data. Unlike some languages, Python uses dynamic typing, meaning you don’t need to declare the type explicitly. 
EDAD_JUBILACION = 60
NOTA_MINIMA = 4.0

# Solicitar nombre y edad
nombre = "Ingrid"
edad_texto = "30"
edad = int(edad_texto)  # Conversión a int

# Años faltantes para jubilarse
faltan = EDAD_JUBILACION - edad
ya_jubilado = (faltan <= 0)
Best Practice: Use UPPERCASE for constants (values that shouldn’t change) and lowercase for regular variables.

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Common Data Types

  • int: Integer numbers (e.g., 30, -5, 1000)
  • float: Decimal numbers (e.g., 4.0, 3.14, -2.5)
  • bool: Boolean values (True or False)
edad = 30  # int
promedio = 4.5  # float
aprueba = True  # bool
Strings are sequences of characters enclosed in quotes.
nombre = "Ingrid"
categoria = 'estudiante'
mensaje = """Este es un
texto multilínea"""
  • list: Ordered, mutable collection
  • dict: Key-value pairs
  • tuple: Ordered, immutable collection
inventario = [
    {"nombre": "laptop", "precio": 800, "stock": 5},
    {"nombre": "mouse", "precio": 25, "stock": 0},
    {"nombre": "teclado", "precio": 45, "stock": 10}
]

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Control Flow

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Conditional Statements

Control the flow of your program based on conditions using if, elif, and else. 
# Simple conditional
if aprueba:
    print("Estado:", "Aprueba ✅")
else:
    print("Estado:", "Reprueba ❌")
Logical Operators: Use and, or, and not to combine multiple conditions. Use parentheses for clarity.

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Input Validation

Always validate user input to prevent errors: 
# Validar entrada numérica
edad_txt = input("Ingrese su edad: ")

if not edad_txt.isdigit():
    print("❌ Edad inválida. Debes ingresar un número entero (ej: 20).")
    raise SystemExit

edad = int(edad_txt)

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Functions

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Defining Functions

Functions help organize code into reusable blocks: 
def calcular_imc(peso, altura):
    """Calcula el IMC usando la fórmula: peso / altura al cuadrado."""
    return peso / (altura ** 2)

# Uso
valor_imc = calcular_imc(75, 1.75)
print(f"Tu IMC es: {valor_imc:.2f}")
The if __name__ == "__main__": pattern ensures code only runs when the file is executed directly, not when imported as a module.

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Functional Programming Concepts

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Lambda Functions and Higher-Order Functions

Python supports functional programming with lambda functions, map(), filter(), and reduce(): 
from functools import reduce

# Lista de productos
inventario = [
    {"nombre": "laptop", "precio": 800, "stock": 5},
    {"nombre": "mouse", "precio": 25, "stock": 0},
    {"nombre": "teclado", "precio": 45, "stock": 10},
    {"nombre": "monitor", "precio": 150, "stock": 3}
]

def obtener_disponibles(lista):
    """Filtra productos que están en stock."""
    return list(filter(lambda producto: producto["stock"] > 0, lista))

def formatear_nombres(lista):
    """Formatea los nombres de los productos a mayúsculas."""
    return list(map(lambda producto: producto["nombre"].upper(), lista))

def calcular_valor_total(lista):
    """Calcula el valor total del inventario disponible."""
    return reduce(
        lambda total, producto: total + (producto["precio"] * producto["stock"]), 
        lista, 
        0
    )

# Uso
disponibles = obtener_disponibles(inventario)
nombres_formateados = formatear_nombres(disponibles)
valor_total = calcular_valor_total(disponibles)

print("Productos disponibles:", nombres_formateados)
print("Valor total del inventario:", valor_total)
Lambda functions are anonymous functions defined in a single line:
# Lambda function
cuadrado = lambda x: x ** 2

# Equivalent regular function
def cuadrado(x):
    return x ** 2
Use lambda for simple operations, especially with map(), filter(), and sorted().

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Best Practices

Use Descriptive Names

Choose variable and function names that clearly describe their purpose.
# Good
edad_jubilacion = 60

# Avoid
x = 60

Add Docstrings

Document your functions with docstrings.
def calcular_imc(peso, altura):
    """Calcula el IMC usando la fórmula: 
    peso / altura al cuadrado."""
    return peso / (altura ** 2)

Handle Errors

Use try-except blocks to handle potential errors gracefully.
try:
    edad = int(input("Edad: "))
except ValueError:
    print("Por favor ingresa un número")

Validate Input

Always validate user input before processing.
if not edad_txt.isdigit():
    print("❌ Entrada inválida")
    return

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Practice Exercises

Create a program that:
  1. Takes three grades as input
  2. Calculates the average
  3. Determines if the student passes (average >= 4.0)
  4. Prints a formatted result
Hint: Use float(input()) for input and conditional statements for evaluation.
Write a function that takes an age and returns the appropriate category:
  • 0-12: “niño/a”
  • 13-17: “adolescente”
  • 18-59: “adulto/a”
  • 60+: “adulto/a mayor”
Hint: Use if-elif-else statements.
Given a list of product dictionaries, write functions to:
  1. Filter products with stock > 0
  2. Convert product names to uppercase
  3. Calculate total inventory value
Hint: Use filter(), map(), and reduce().

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Next Steps

Now that you understand Python basics, you’re ready to explore:

Object-Oriented Programming

Learn about classes, objects, and inheritance

Python Projects

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