Una introducción a la programación en R: De los scripts a la programación

La transición de scripts a programación en R marca el cambio de ejecutar declaraciones interactivas aisladas a construir flujos de trabajo automatizados y escalables. Esta evolución implica organizar los datos en contenedores robustos como vector, matriz, factor, arreglo, y lista para gestionar arquitecturas de información complejas.

1. Flujo de control programático

En lugar de repetir manualmente, usamos bloques lógicos para gestionar la complejidad. R proporciona mecanismos estructurados de flujo de control:

Iteración:for (nombre en expr_1) expr_2, while (condición) expr, y repeat expr.
Condicionales:if (expr_1) expr_2 else expr_3 para ramificación lógica y el uso vectorizado de ifelse para tomar decisiones elemento a elemento.

# Agrupar expresiones
{ expr_1 ; ... ; expr_m }

2. Pensamiento vectorial y mapeo funcional

La programación en R aprovecha la iteración funcional para procesar estructuras de datos sin bucles explícitos. Funciones como apply, lapply, sapply, y tapply te permiten aplicar lógica sobre arreglos o listas. Por ejemplo, usando split para agrupar un dataframe por un factor y luego aplicando una media, var, o sqrt(sum(x)) calculación reduce significativamente la deuda de código y errores.

TERMINALbash — 80x24

> Ready. Click "Run" to execute.

QUESTION 1

Which structure allows you to group multiple R expressions into a single logical block?

( expr_1 , expr_2 )

{ expr_1 ; ... ; expr_m }

block[ expr_1 ]

list( expr_1 )

✅ Correct!

Braces {} are used to group multiple statements into one expression, often used in function bodies or loops.

❌ Incorrect

R uses curly braces {} to encapsulate a multi-line code block.

QUESTION 2

When would a programmer choose lapply over a standard for loop?

When the data is stored in a matrix only.

To explicitly use lsfit on single vectors.

To apply a function to each element of a list and return a list.

To stop execution immediately via repeat.

✅ Correct!

lapply is the functional way to iterate over lists, returning a result of the same length.

❌ Incorrect

lapply stands for 'list apply' and is part of R's functional programming toolkit.

QUESTION 3

What is the primary advantage of using for (i in 1:length(yc)) in the context of linear regression on multiple sets?

It automatically calculates the mean of xc.

It ensures logic remains concise regardless of the number of datasets.

It converts a list into a factor.

It forces the use of ifelse for plotting.

QUESTION 4

How does ifelse differ from if...else?

ifelse is used only inside repeat loops.

if...else is vectorized, while ifelse is not.

ifelse is vectorized; if...else handles only a single logical value.

There is no difference in R.

✅ Correct!

ifelse can process whole vectors at once, whereas if expects a single TRUE/FALSE.

❌ Incorrect

if is for control flow; ifelse is a vectorized function.

QUESTION 5

Which function would you use to group data by categories before applying a summary statistic like sum?

split

lsfit

abline

sqrt

✅ Correct!

split divides data into groups based on a factor, which can then be processed by the apply family.

❌ Incorrect

split is essential for 'Split-Apply-Combine' workflows in R.