## Table of Contents

### Introduction to Input Data in R Language

There are many ways to input data in R Language. Here, I will concentrate only on typing data directly at the keyboard using `c()`

and `scan()`

functions, which are very common ways to input data in R language.

Traditional statistical computer software such as Minitab, SPSS, and SAS, etc., are designed to transform rectangular datasets (a dataset whose rows represent the observations and columns represent the variables) into printed reports and graphs. However, R and S languages are designed to transform data objects into other data objects (such as reports, and graphs).

S and R language both support rectangular datasets, in the form of data frames and other data structures. Here we will learn to know about data in R to work efficiently as a statistical data analyst.

### Data Input Functions in R

There are many ways to input data in R and S-Plus. Let us learn to type data directly on the keyboard.

#### Input Data Using c() Function

The best choice is to enter small datasets directly on the keyboard. Remember that it is impractical to enter a large data set directly at the keyboard.

Let us use the `c()`

function to enter the vector of numbers directly as:

x <- c(1, 3, 5, 7, 9) char <- c('a', 'b', 'c', 'd') TF <- c(TRUE, FALSE)

Note that the character strings can be directly inputted in single or double quotation marks. For example, `"a"`

and `'a'`

both are equivalent.

#### Input Data Using Scan Function

It is also very convenient to use the `scan()`

function, which prompts with the index of the next entry. Consider the example,

xyz <- scan() 1: 10 20 30 35 5: 40 35 25 8: 9 100 50 11: Read 10 items

The number before the colon on each of the inputted lines is the index of the next data entry point (observation) to be entered. Note that entering a blank line terminates the `scan()`

function input behavior.

Click the following links to learn about data entry (import and export internal and external data) in R Language