cbind() function in R programming

In a recent blog post, Google announced that CPU overcommit for sole-tenant nodes is generally available. With CPU overcommit for sole-tenant nodes, customers can over-provision their dedicated host virtual CPU resources by up to two times.

Two years ago, GooglYou can use cbind() function in R exclusively to bind or combine the multiple columns together.

Hello folks, today, our focus will be on the applications and use cases of the cbind() function in R.

cbind() function stands for column binding. If you want to bind or combine multiple columns, then no other function will serve better than cbind().

In this article, you will be witnessing many examples that clearly explains the use and benefits of cbind() function.

Let’s roll!!!


Syntax of the cbind() function

cbind(): The cbind() function in R is used to bind the multiple columns of the data frame.

cbind``(x,x1)

Where,

  • X = The input columns of the data frame.
  • X1 = The columns of the data frame needs to be bonded.

The idea of binding the columns

The main objective of the cbind() function is to combine or to bind the multiple columns.

The columns may include vectorsdata frames, or multiple columns (more than 2).

The basic idea of working of the cbind() function in R is illustrated below with the help of a diagram.

The function will take multiple inputs and binds them together. Exactly like rbind() function but it binds the columns.

announced the beta availability of sole-tenant nodes on Google Compute Engine as an option for customers to have their Virtual Machines (VM) on a dedicated physical host, i.e. an entire Google Compute Engine for their use. Later in early 2020, the company improved the flexibility of their sole-tenant nodes with a few new features such as node group autoscaler, migration between multi- and sole tenant nodes, and live migration within a fixed node pool for bringing your own license (BYOL). And recently, the company made CPU Overcommit for sole-tenant nodes generally available.

Enabling CPU Overcommit for sole-tenant nodes leads to automatic reallocation of virtual CPUs across sole-tenant nodes from idle VM instances to VM instances that need additional resources. Users can set on the VM instance level the minimum number of guaranteed virtual CPUs per VM along with the maximum burstable virtual CPUs per VM. Thus, users can manage VM sizes and overcommit levels on a single sole-tenant node to meet their specific workload needs.

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cbind() function in R programming
Dianna  Farrell

Dianna Farrell

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R Programming Tutorial for Beginners | Learn the Basics of R Programming | R & RStudio Tutorial

👉 This video will introduce you to the R programming language, and will give you a hands-on overview of the statistical programming language R, one of the most important programming tools in data science…

Enjoy the video!

⏰Timestamps⏰

  • 00:00 Welcome
  • 00:24 R Introduction
  • 01:38 R Installation
  • 06:22 R Variables
  • 15:20 R Math Functions
  • 17:06 R Strings
  • 24:04 R Comparison Operators
  • 28:16 R If Else
  • 35:37 R While Loop
  • 40:13 R For Loop
  • 45:18 R Functions
  • 52:55 R Lists
  • 57:29 R Apriori Algorithm

Link to download R:
https://cran.r-project.org/bin/windows/base/
Link to Download RStudio:
https://www.rstudio.com/products/rstudio/download/

#r #r-programming #programming

Angela  Dickens

Angela Dickens

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Functional Programming

Functional Programming is a Declarative style of Programming Paradigm for writing computer programs.
But, What are Functions ?
Functions in general, applies computation on given input and returns the output. It relates input to an output.
f(x) = x + 2;
f(1) = 1 + 2 = 3;
f(2) = 2 + 2 = 4;
Above mentioned is a simple function that adds 2 to the input value and returns output. It relates value [1,2] => [3,4]. Similarly, a function in computer programming is a block of instruction that performs computation on given input and returns the output.
Functional Programming is such a style of writing computer programs using these tiny functions that works together and perform required computation.
Functions in Functional Programming
The philosophy of functional programming is to maintain certain characteristics while writing functions in a computer program. These characteristics are the fundamental nature of functional programming that describe what shall be the behaviour of a function. These are as follows :
Declarative
A function must be declarative, it simply tells what to compute, without specifying how to compute it.
f(x) = x * 4; 👍
Declarative function that tells to multiply input by 4;
f(x) = { y = x + x; z = x + x; return y + z;} 👎
Non-Declarative function that specify how to multiply input by 4;
Pure
A function must give the same output for a given input value, at any period of time. It is not dependent upon anything outside the function definition.
f(x) = It’s never too late; 👍
Pure function that will always return It’s never too late
f(x) = If today’s Friday or Saturday then It’s never too late else It’s late. 👎
Impure function that consider day for returning value. The value is not predictable. It can change. So a function that performs anything which is unpredictable is not a pure function. The condition or the execution is dynamic or unfixed in an impure function.

#development #functional-programming #software #software-programming #declarative-programming #function

Are functions from programming really functions?

If you are reading this, then most probably you already know quite well what functions are in programming. A function is quite a common and spread programming construct that is present in almost all programming languages.

Generally, a function is a block of code that takes some parameters from outside, executes some operations in which these parameters may be used, then it returns an output value. Actually, in many programming languages functions are allowed to not return something or to return multiple values, not only one. But these cases can be also be represented, for the sake of generality, as only one value. For the “no return” case we can use a special value to represent that (in Python that special value is None; whenever you don’t return something from a function it’s returned None). And for the case of more values, we can use a vector of multiple values as a single object.

For example, in Python a function definition looks like this:

def func_name(param1, param2, ...):

    ## do some stuff with input parameters
    return output_value

Now, the question I want to ask: Are these functions from programming true mathematical functions?

Well…, let’s first recall what a mathematical function is.

In mathematics, a function is just a mapping from a set A to a set B, in which any element from A has only one associated element in B.

#python #programming #function #mathematics #functional-programming

Dock  Koelpin

Dock Koelpin

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Data Types In R

Data types are kept easy.

Data types of R are quite different when we compare with other programming languages. Here, we’ll outline the data types of R.

Integers

Integers are numbers without a decimal point. Unlike other programming languages, R represents all integers as a “double” data type. But the main difference is, you need to write “L” to represent integers in arithmetic operations. For example 9L.

Double

Instead of floats, R has a double data type to represent both for making arithmetic calculations simpler. And when you look for integers and floats in programming languages, you’ll see double after writing the function to specify the data type. As an example: 9 and 3,4.

Vectors

The most basic data type of R that is the lifeblood of its operations because R works with vectorized operations. When we define vectors in R, they’re a sequence of the data element of the same basic time. It only contains the element of the same data type. If not, R will try to convert it into the most dominant data type.

Complex

The complex data type is only used to represent complex (imaginary) numbers in R. Unlike most data types, the complex data type is not used commonly in R. We can give a+bi as an example.

#data-type #r-programming #r-programming-language #r #programming-languages #data science

akshay L

akshay L

1611665228

R Programming Course

In this R Tutorial For Beginners video, you will learn r programming language from scratch to advance concepts. This R training video also covers hands-on demo and interview questions. This R Programming Course is a must-watch video for everyone who wishes to learn the R language and make a career in the data science domain.

#r programming course #r programming course #r tutorial for beginners #learn r language