Industrial Training




R - XML Files

XML is a file format which shares both the file format and the data on the World Wide Web, intranets, and elsewhere using standard ASCII text. It stands for Extensible Markup Language (XML). Similar to HTML it contains markup tags. But unlike HTML where the markup tag describes structure of the page, in xml the markup tags describe the meaning of the data contained into he file.


You can read a xml file in R using the "XML" package. This package can be installed using following command.


install.packages("XML")

Input Data

Create a XMl file by copying the below data into a text editor like notepad. Save the file with a .xml extension and choosing the file type as all files(*.*).


   
      1
      Rick
      623.3
      1/1/2012
      IT
   
	
   
      2
      Dan
      515.2
      9/23/2013
      Operations
   
   
   
      3
      Michelle
      611
      11/15/2014
      IT
   
   
   
      4
      Ryan
      729
      5/11/2014
      HR
   
   
   
      5
      Gary
      843.25
      3/27/2015
      Finance
   
   
   
      6
      Nina
      578
      5/21/2013
      IT
   
   
   
      7
      Simon
      632.8
      7/30/2013
      Operations
   
   
   
      8
      Guru
      722.5
      6/17/2014
      Finance
   
	

Reading XML File

The xml file is read by R using the function xmlParse(). It is stored as a list in R.

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

# Also load the other required package.
library("methods")

# Give the input file name to the function.
result <- xmlParse(file = "input.xml")

# Print the result.
print(result)

When we execute the above code, it produces the following result −

1
Rick
623.3
1/1/2012
IT

2
Dan
515.2
9/23/2013
Operations

3
Michelle
611
11/15/2014
IT

4
Ryan
729
5/11/2014
HR

5
Gary
843.25
3/27/2015
Finance

6
Nina
578
5/21/2013
IT

7
Simon
632.8
7/30/2013
Operations

8
Guru
722.5
6/17/2014
Finance

Get Number of Nodes Present in XML File

# Load the packages required to read XML files.
library("XML")
library("methods")

# Give the input file name to the function.
result <- xmlParse(file = "input.xml")

# Exract the root node form the xml file.
rootnode <- xmlRoot(result)

# Find number of nodes in the root.
rootsize <- xmlSize(rootnode)

# Print the result.
print(rootsize)

When we execute the above code, it produces the following result −

output
[1] 8

Details of the First Node

Let's look at the first record of the parsed file. It will give us an idea of the various elements present in the top level node.

# Load the packages required to read XML files.
library("XML")
library("methods")

# Give the input file name to the function.
result <- xmlParse(file = "input.xml")

# Exract the root node form the xml file.
rootnode <- xmlRoot(result)

# Print the result.
print(rootnode[1])

When we execute the above code, it produces the following result −

$EMPLOYEE
   1
   Rick
   623.3
   1/1/2012
   IT
 

attr(,"class")
[1] "XMLInternalNodeList" "XMLNodeList" 

Get Different Elements of a Node

# Load the packages required to read XML files.
library("XML")
library("methods")

# Give the input file name to the function.
result <- xmlParse(file = "input.xml")

# Exract the root node form the xml file.
rootnode <- xmlRoot(result)

# Get the first element of the first node.
print(rootnode[[1]][[1]])

# Get the fifth element of the first node.
print(rootnode[[1]][[5]])

# Get the second element of the third node.
print(rootnode[[3]][[2]])

When we execute the above code, it produces the following result −

1 
IT 
Michelle 

XML to Data Frame

To handle the data effectively in large files we read the data in the xml file as a data frame. Then process the data frame for data analysis.

# Load the packages required to read XML files.
library("XML")
library("methods")

# Convert the input xml file to a data frame.
xmldataframe <- xmlToDataFrame("input.xml")
print(xmldataframe)

When we execute the above code, it produces the following result −

      ID    NAME     SALARY    STARTDATE       DEPT 
1      1    Rick     623.30    2012-01-01      IT
2      2    Dan      515.20    2013-09-23      Operations
3      3    Michelle 611.00    2014-11-15      IT
4      4    Ryan     729.00    2014-05-11      HR
5     NA    Gary     843.25    2015-03-27      Finance
6      6    Nina     578.00    2013-05-21      IT
7      7    Simon    632.80    2013-07-30      Operations
8      8    Guru     722.50    2014-06-17      Finance

As the data is now available as a dataframe we can use data frame related function to read and manipulate the file.



Hi I am Pluto.