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Importing Data in R Script

  • Difficulty Level : Basic
  • Last Updated : 25 Nov, 2021

In this article, we are going to see how to Import data in R Programming Language.

Importing Data in R

First, let’s consider a data-set which we can use for the demonstration. For this demonstration, we will use two examples of a single dataset, one in .csv form and another .txt

Reading a Comma-Separated Value(CSV) File

Method 1: Using read.csv() Function Read CSV Files into R

The function has two parameters: 

  • file.choose(): It opens a menu to choose a csv file from the desktop.
  • header: It is to indicate whether the first row of the dataset is a variable name or not. Apply T/True if the variable name is present else put F/False.

Example: 



R




# import and store the dataset in data1
data1 <- read.csv(file.choose(), header=T)
 
# display the data
data1

Output: 

Method 2: Using read.table() Function

This function specifies how the dataset is separated, in this case we take sep=”, “ as an argument.

Example: 

R




# import and store the dataset in data2
data2 <- read.table(file.choose(), header=T, sep=", ")
 
# display data
data2

Output: 



Reading a Tab-Delimited(txt) File in R Programming Language

Method 1: Using read.delim() Function

The function has two parameters: 

  • file.choose(): It opens a menu to choose a csv file from the desktop.
  • header: It is to indicate whether the first row of the dataset is a variable name or not. Apply T/True if the variable name is present else put F/False.

Example: 

R




# import and store the dataset in data3
data3 <- read.delim(file.choose(), header=T)
 
# display the data
data3

Output: 

Method 2: Using read.table() Function

This function specifies how the dataset is separated, in this case we take sep=”\t” as the argument.

Example: 

R




# import and store the dataset in data4
data4 <- read.table(file.choose(), header=T, sep="\t")
 
# display the data
data4

Output: 



Using R-Studio

Here we are going to import data through R studio with the following steps.

Steps: 

  • From the Environment tab click on the Import Dataset Menu
  • Select the file extension from the option
  • In the third step, a pop-up box will appear, either enter the file name or browse the desktop.
  • The selected file will be displayed on a new window with its dimensions.
  • In order to see the output on the console, type the filename.

Example:

R




# display the dataset
dataset

Output:

  • In order to load the data onto the console for use, we use the attach command.

Example:

R




# To load the data for use
attach(dataset)

Read JSON Files Into R

In order to work with JSON files in R, one needs to install the “rjson”  package. The most common tasks done using JSON files under rjson packages are as follows:

  • Install and load the rjson package in R console
  • Create a JSON file
  • Reading data from JSON file
  • Write into JSON file
  • Converting the JSON data into Dataframes
  • Working with URLs

JSON file for demonstration:

{ 
   "ID":["1","2","3","4","5"],
   "Name":["Mithuna","Tanushree","Parnasha","Arjun","Pankaj"],
   "Salary":["722.5","815.2","1611","2829","843.25"],
   "StartDate":["6/17/2014","1/1/2012","11/15/2014","9/23/2013","5/21/2013"],
   "Dept":["IT","IT","HR","Operations","Finance"]
}

Code:

R




# Read a JSON file
 
# Load the package required to read JSON files.
library("rjson")
 
# Give the input file name to the function.
result <- fromJSON(file = "E:\\example.json")
 
# Print the result.
print(result)

Output:

$ID
[1] "1" "2" "3" "4" "5"

$Name
[1] "Mithuna"   "Tanushree" "Parnasha"  "Arjun"     "Pankaj"

$Salary
[1] "722.5"  "815.2"  "1611"   "2829"   "843.25"

$StartDate
[1] "6/17/2014"  "1/1/2012"   "11/15/2014" "9/23/2013"  "5/21/2013"

$Dept
[1] "IT"         "IT"         "HR"         "Operations" "Finance"



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