Data as Objects, Analysis as Transformation
In R, you don’t command the data — you transform it.
Every R session is a living stream. Data flows in, and with each pipe, it changes shape — cleaner, clearer, closer to insight.
That is the essence of R: data as objects, analysis as transformation.
🧩 Seeing Data as Objects
Everything in R is an object — data frames, vectors, lists, models.
You don’t just run commands; you manipulate structures.
This object orientation makes R a consistent and expressive tool.
# A tibble is more than a table — it’s an object with behavior
library(tibble)
df <- tibble(
species = c("Elephant", "Tiger", "Turtle"),
weight_kg = c(5400, 220, 90)
)
print(df)
Each column is a vector, each row a moment in your data’s story.
🔄 The Pipe: The Language of Flow
The pipe (|>, or %>% from magrittr) changed everything.
Instead of nesting functions, you think in transformations — one step flows into the next.
library(dplyr)
df |>
mutate(weight_ton = weight_kg / 1000) |>
filter(weight_ton > 0.1) |>
arrange(desc(weight_ton))
Each line reads like a sentence: “Take the data, then mutate, then filter, then arrange.”
It’s not programming — it’s thought in motion.
🧠 Transformation as Understanding
Transformation is not just cleaning — it’s modeling your mental structure of reality.
When you reshape a dataset, you’re deciding what matters, what disappears, and what stays visible.
In this way, analysis becomes an act of philosophy: how you choose to see the world.
💡 Reflection
What does your pipeline say about how you think?
Try this:
library(dplyr)
starwars |>
select(name, species, height, mass, homeworld) |>
mutate(bmi = mass / (height/100)^2) |>
arrange(desc(bmi)) |>
head(5)
This is not just code — it’s a thought process, rendered in syntax.
📘 Try It Yourself
- Take any dataset from
datasets:: - Apply at least three transformations using the pipe
- Observe how your mental model of the data changes
🔗 Further Reading
- Wickham, H. (2014). Tidy Data. Journal of Statistical Software.
- Bache & Wickham (2014). Magrittr: A Forward-Pipe Operator for R.
- Hadley Wickham’s Advanced R, Chapter 6: Functions.
In R, transformation is not a step — it’s the soul of the analysis.