Structure Precedes Power

Power in R does not come from knowing more functions. It comes from knowing what you are holding before you touch it.

Most analytical errors are not caused by wrong formulas or weak models. They are caused by acting on objects whose structure was never understood.

R assumes you will check. It does not forgive you when you don’t.

Structure Is the First Question

Before transformation, before visualization, before modeling, the responsible analyst asks:

• What type is this object?
• What class does it claim?
• What shape does it impose?
• What assumptions does this structure encode?

These are not academic questions.
They determine what operations are valid and which are nonsense.

Inspection Is How You Think in R

R provides blunt, honest tools:

str(obj)
class(obj)
typeof(obj)
length(obj)
names(obj)

These functions do not decorate.
They reveal.

Skipping them is not confidence.
It is negligence.

Structure Explains “Strange” Behavior

When R surprises you, it is almost never being inconsistent.

• Recycling warnings?
• Unexpected coercion?
• Silent NAs?
• Functions behaving “oddly”?

These are signals—not bugs.

They are R telling you:
you misunderstood the structure.

Why Power Tools Come Later

Tidy evaluation.
Functional programming.
Modeling frameworks.

All of them assume structural literacy. Without it:

• abstraction becomes fragile
• code becomes incantation
• results become untrustworthy

Structure is not optional groundwork.
It is the price of admission.

The Discipline That Scales

Experienced R users inspect reflexively—not because they doubt themselves, but because they respect complexity.

They know:

• objects lie quietly
• structure never lies
• and assumptions rot fastest in silence

This habit is what allows large analyses to remain intelligible months later.

Chapter One taught you how to think in R.
Chapter Two taught you what thought must hold.

From here on, the work becomes expressive rather than defensive.

You are now ready for grammar.