The collection of facts is known as data. Data can be in different forms. To analyze data using R programming Language, data should be first imported in R which can be in different formats like txt, CSV, or any other delimiter-separated files. After importing data then manipulate, analyze, and report it.

Import Data from a File in R Programming Language

In this article, we are going to see how to import different files in the R Programming Language.

Import CSV file into R

Method 1: Using read.csv() methods.

Here we will import csv file using the read.csv() method in R.

Syntax: read.csv(path, header = TRUE, sep = “,”)

Arguments : 

• path : The path of the file to be imported
• header : By default : TRUE . Indicator of whether to import column headings.
• sep = “,”  : The separator for the values in each row.

# specifying the path
path <- "/gfg.csv"

# reading contents of csv file
content <- read.csv(path)

# contents of the csv file
print (content)

Output:

  ID Name    Post Age 
1  5    H      CA  67 
2  6    K     SDE  39 
3  7    Z   Admin  28

Method 2: Using read.table() methods

Here we will use read.table() methods to import CSV files into R Programming Language.

# simple R program to read csv file using read.table()
x <- read.csv2("D://Data//myfile.csv", header = TRUE, sep=", ")

# print x
print(x)

Output: 

  Col1.Col2.Col3
1      100, a1, b1
2      200, a2, b2
3      300, a3, b3

Importing Data from a Text File

We can easily import or read .txt file using basic R function read.table(). read.table() is used to read a file in table format. This function is easy to use and flexible. 

Syntax: 

# read data stored in .txt file

x<-read.table("file_name.txt", header=TRUE/FALSE)

# Simple R program to read txt file
x<-read.table("D://Data//myfile.txt", header=FALSE)

# print x
print(x)

Output: 

   V1 V2 V3
1 100 a1 b1
2 200 a2 b2
3 300 a3 b3

If the header argument is set at TRUE, which reads the column names if they exist in the file.

Importing Data from a delimited file

R has a function read.delim() to read the delimited files into the list. The file is by default separated by a tab which is represented by sep="", that separated can be a comma(, ), dollar symbol($), etc. 

Syntax:  read.delim("file_name.txt", sep="", header=TRUE)

x <- read.delim("D://Data//myfile.csv", sep="|", header=TRUE)

# print x
print(x)

# print type of x
typeof(x)

Output:

X.V1.V2.V3
1 1, 100, a1, b1
2 2, 200, a2, b2
3 3, 300, a3, b3
[1] "list

Importing Json file in R

Here we are going to use rjson package to import the JSON file into R Programming Language.

# Read a JSON file

# Load the package required to read JSON files.
library("rjson")

# Give the input file name to the function.
res <- fromJSON(file = "E:\\exp.json")

# Print the result.
print(res)

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"

Importing XML files in R

To import XML files here we are going to use XML Package in R Programming language.

XML file for demonstration:

<RECORDS>
<STUDENT>
    <ID>1</ID>
    <NAME>Alia</NAME>
    <MARKS>620</MARKS>
    <BRANCH>IT</BRANCH>
</STUDENT>
<STUDENT>
    <ID>2</ID>
    <NAME>Brijesh</NAME>
    <MARKS>440</MARKS>
    <BRANCH>Commerce</BRANCH>
</STUDENT>
<STUDENT>
    <ID>3</ID>
    <NAME>Yash</NAME>
    <MARKS>600</MARKS>
    <BRANCH>Humanities</BRANCH>
</STUDENT>
<STUDENT>
    <ID>4</ID>
    <NAME>Mallika</NAME>
    <MARKS>660</MARKS>
    <BRANCH>IT</BRANCH>
</STUDENT>
<STUDENT>
    <ID>5</ID>
    <NAME>Zayn</NAME>
    <MARKS>560</MARKS>
    <BRANCH>IT</BRANCH>
</STUDENT>
</RECORDS>

Reading XML file:

It can be read after installing the package and then parsing it with xmlparse() function.

# loading the library and other important packages
library("XML")
library("methods")

# the contents of sample.xml are parsed
data <- xmlParse(file = "sample.xml")

print(data)

Output:

1
Alia
620
IT
2
Brijesh
440
Commerce
3
Yash
600
Humanities
4
Mallika
660
IT
5
Zayn
560
IT

Importing SPSS sav File into R

Here we are going to read SPSS .sav File in the R programming language. For this, we will use the haven package. To read SPSS files in R we use the read_sav() function which is inside the haven package.

Syntax: read_sav(“FileName.sav”)

# import haven library package
library("haven")

# Use read_sav() function to read SPSS file
dataframe <- read_sav("SPSS.sav")    
dataframe

Output:

priyanka_bajpai

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Article Tags :

• Misc
• R Language
• R Functions
• R-FileHandling

Practice Tags :

• Misc