R Introduction: Part I

R Introduction: Part I

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1. Basic Syntax and Operations

In the initial section, you’ll dive into the foundational elements of R, such as generating output and performing elementary operations. This section will conclude with an exploration of the theory behind variables.

Basic Arithmetic

Using the print() Function

Integer Division and Remainders

Revenue Calculation

Assignment Operators

2. Basic Data Types and Vectors

You’ll become familiar with the vector class in R, which also handles individual values. Here, you’ll delve into the primary data types for singular values and learn how to manage multiple values of the same type simultaneously.

Type Conversion

Labeling Vectors

Indexing in Vectors

Modifying Vectors

Deleting Elements from Vectors

Arithmetic Operations with Vectors

3. Factors

Factors, also known as categorical variables, are prevalent in the real world. Examples include blood types, currencies, nationalities, and brands. Unlike numerical variables, factors have a limited set of possible values.

What is a Factor?

Indexing in Factors

Counting Values

Grouping Numeric Data

Comments in R

When you've written an extensive script for research and need to revisit it later for updates or improvements, remembering the purpose of each line of code can be challenging. That’s where annotations within the code, known as comments, become invaluable.

A comment is a portion of code that isn't executed. To signal which parts should not be processed, we use the # symbol.

For instance, we can add comments in two ways: as a standalone line and alongside a computation:

The console will only show the result of 11 + 3 and ignore all the comments.

While not mandatory, the inclusion of comments is widely regarded as a best practice for maintaining clarity and readability in your code. However, comments should only be used for complicated parts of the code, as excessive commenting can clutter the code and reduce its readability.

Comments are useful not just for clarification, but also for debugging purposes, allowing you to deactivate certain lines of code without deleting them.

Task

To make the code executable by deactivating certain lines, apply the hash # symbol to correct the errors.

Everything was clear?

Section 1. Chapter 4

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Course Content

R Introduction: Part I

R Introduction: Part I

Comments in R

When you've written an extensive script for research and need to revisit it later for updates or improvements, remembering the purpose of each line of code can be challenging. That’s where annotations within the code, known as comments, become invaluable.

A comment is a portion of code that isn't executed. To signal which parts should not be processed, we use the # symbol.

For instance, we can add comments in two ways: as a standalone line and alongside a computation:

The console will only show the result of 11 + 3 and ignore all the comments.

While not mandatory, the inclusion of comments is widely regarded as a best practice for maintaining clarity and readability in your code. However, comments should only be used for complicated parts of the code, as excessive commenting can clutter the code and reduce its readability.

Comments are useful not just for clarification, but also for debugging purposes, allowing you to deactivate certain lines of code without deleting them.

Task

To make the code executable by deactivating certain lines, apply the hash # symbol to correct the errors.

Everything was clear?

Section 1. Chapter 4

toggle bottom row

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