R Examples for Beginners – R Program to Add Two Vectors

Hits: 10

(R Example for Citizen Data Scientist & Business Analyst)

 

R Program to Add Two Vectors

In this example, you’ll learn to add two vectors using R operators.


We can add two vectors together using the + operator.

One thing to keep in mind while adding (or other arithmetic operations) two vectors together is the recycling rule.

If the two vectors are of equal length then there is no issue. But if the lengths are different, the shorter one is recycled (repeated) until its length is equal to that of the longer one.

This recycling process will give a warning if the longer vector is not an integral multiple of the shorter one.

Example: Add Two Vectors

> x
[1] 3 6 8
> y
[1] 2 9 0
> x + y
[1]  5 15  8
> x + 1    # 1 is recycled to (1,1,1)
[1] 4 7 9
> x + c(1,4)    # (1,4) is recycled to (1,4,1) but warning issued
[1]  4 10  9
Warning message:
In x + c(1, 4) :
longer object length is not a multiple of shorter object length

As we can see above the two vectors x and y are of equal length so they can be added together without difficulty.

The expression x + 1 also works fine because the single 1 is recycled into a vector of three 1‘s.

Similarly, in the last example, a two element vector is recycled into a three element vector. But a warning is issued in this case as 3 is not an integral multiple of 2.

 

Beginners tutorial with R – Vectors

 

R Examples for Beginners – R Program to Add Two Vectors

 

Sign up to get end-to-end “Learn By Coding” example.


 

 

Introduction to Applied Machine Learning & Data Science for Beginners, Business Analysts, Students, Researchers and Freelancers with Python & R Codes @ Western Australian Center for Applied Machine Learning & Data Science (WACAMLDS) !!!

Latest end-to-end Learn by Coding Projects (Jupyter Notebooks) in Python and R:

Applied Statistics with R for Beginners and Business Professionals

Data Science and Machine Learning Projects in Python: Tabular Data Analytics

Data Science and Machine Learning Projects in R: Tabular Data Analytics

Python Machine Learning & Data Science Recipes: Learn by Coding

R Machine Learning & Data Science Recipes: Learn by Coding

 

There are 2000+ End-to-End Python & R Notebooks are available to build Professional Portfolio as a Data Scientist and/or Machine Learning Specialist. All Notebooks are only $79.95. We would like to request you to have a look at the website for FREE the end-to-end notebooks, and then decide whether you would like to purchase or not.

Please do not waste your valuable time by watching videos, rather use end-to-end (Python and R) recipes from Professional Data Scientists to practice coding, and land the most demandable jobs in the fields of Predictive analytics & AI (Machine Learning and Data Science).

The objective is to guide the developers & analysts to “Learn how to Code” for Applied AI using end-to-end coding solutions, and unlock the world of opportunities!

 

Disclaimer: The information and code presented within this recipe/tutorial is only for educational and coaching purposes for beginners and developers. Anyone can practice and apply the recipe/tutorial presented here, but the reader is taking full responsibility for his/her actions. The author (content curator) of this recipe (code / program) has made every effort to ensure the accuracy of the information was correct at time of publication. The author (content curator) does not assume and hereby disclaims any liability to any party for any loss, damage, or disruption caused by errors or omissions, whether such errors or omissions result from accident, negligence, or any other cause. The information presented here could also be found in public knowledge domains.