Reading and Parsing JSON Data in R

R is a wonderful statistical language with a lot of features.R can read and parse a large number of data formats including .xls,.txt,.json etc.

JSON stands for Java Script Object Notation.For reading and parsing json data in R consists of following steps:

1.Grabbing Data:

Our first step includes how we grab the data.The data can be on a Server,html link or stored in a database.In my case the data is stored on a Server,which i was given access via SSH.

                                       

Here I have 11 Gb of tweets which i need to download.I had used the jsonlite package in R to get the data from server.The feature I liked the most is the streaming part.You can give the number of lines you want to read in one iteration.

Here I had used jsonlite package and i opted to read 10000 lines in one run.This is the process of reading json data in R.

2.Extracting Data from JSON file

Now we have loaded our data in R,now it is the time to extract our data from the file.With the following code we can extract data from json file.We need to use [['  ']] (double braces) to get our data.

After getting data,i converted the data to a data frame.After then we can apply text mining,social media analytics on it.

How to import different data formats into R

Data Import

It is often necessary to import sample textbook data into R before you start working on your homework.

Excel File

Quite frequently, the sample data is in Excel format, and needs to be imported into R prior to use. For this, we can use the function read.xls from the gdata package. It reads from an Excel spreadsheet and returns a data frame. The following shows how to load an Excel spreadsheet named "mydata.xls". This method requires Perl runtime to be present in the system.

> library(gdata)                   # load gdata package 
> help(read.xls)                   # documentation 
> mydata = read.xls("mydata.xls")  # read from first sheet

Alternatively, we can use the function loadWorkbook from the XLConnect package to read the entire workbook, and then load the worksheets with readWorksheet. The XLConnect package requires Java to be pre-installed.

> library(XLConnect)               # load XLConnect package 
> wk = loadWorkbook("mydata.xls") 
> df = readWorksheet(wk, sheet="Sheet1")

Minitab File

If the data file is in Minitab Portable Worksheet format, it can be opened with the functionread.mtp from the foreign package. It returns a list of components in the Minitab worksheet.

> library(foreign)                 # load the foreign package 
> help(read.mtp)                   # documentation 
> mydata = read.mtp("mydata.mtp")  # read from .mtp file

SPSS File

For the data files in SPSS format, it can be opened with the function read.spss also from theforeign package. There is a "to.data.frame" option for choosing whether a data frame is to be returned. By default, it returns a list of components instead.

> library(foreign)                 # load the foreign package 
> help(read.spss)                  # documentation 
> mydata = read.spss("myfile", to.data.frame=TRUE)

Table File

A data table can resides in a text file. The cells inside the table are separated by blank characters. Here is an example of a table with 4 rows and 3 columns.

100   a1   b1 
200   a2   b2 
300   a3   b3 
400   a4   b4

Now copy and paste the table above in a file named "mydata.txt" with a text editor. Then load the data into the workspace with the function read.table.

> mydata = read.table("mydata.txt")  # read text file 
> mydata                             # print data frame 
   V1 V2 V3 
1 100 a1 b1 
2 200 a2 b2 
3 300 a3 b3 
4 400 a4 b4

For further detail of the function read.table, please consult the R documentation.

> help(read.table)

CSV File

The sample data can also be in comma separated values (CSV) format. Each cell inside such data file is separated by a special character, which usually is a comma, although other characters can be used as well.

The first row of the data file should contain the column names instead of the actual data. Here is a sample of the expected format.

Col1,Col2,Col3 
100,a1,b1 
200,a2,b2 
300,a3,b3

After we copy and paste the data above in a file named "mydata.csv" with a text editor, we can read the data with the function read.csv.

> mydata = read.csv("mydata.csv")  # read csv file 
> mydata 
  Col1 Col2 Col3 
1  100   a1   b1 
2  200   a2   b2 
3  300   a3   b3

In various European locales, as the comma character serves as the decimal point, the functionread.csv2 should be used instead. For further detail of the read.csv and read.csv2 functions, please consult the R documentation.

> help(read.csv)

Working Directory

Finally, the code samples above assume the data files are located in the R working directory, which can be found with the function getwd.

> getwd()               # get current working directory

You can select a different working directory with the function setwd(), and thus avoid entering the full path of the data files.

> setwd("<new path>")   # set working directory

Step-by-Step Guide to Setting Up an R-Hadoop System

It is assumed that you had already installed hadoop in your system.If you dont had installed now,you can visit the following link:

Install hadoop 

1.Install R

The version of R that I used is 3.1.0, the latest version as of May 2014. Previously I set up an R-Hadoop system with R 2.15.2 before, so it should work with other versions of R, at least with R 2.15.2 and above.

It is recommended to install RStudio as well, if it is not installed yet. This will make it easier for R programming and managing R projects, although it is not mandatory.

2. Install GCC, Homebrew, git, pkg-config and thrift

GCC, Homebrew, git, pkg-config and thrift are mandatory for installing rhbase. If you donot use HBase orrhbase, you donot need to install pkg-config or thrift.

2.1 Download and install GCC

Download GCC at https://github.com/kennethreitz/osx-gcc-installer. Without GCC, you will get error “Make Command Not Found” when installing some R packages from source.

2.2 Install Homebrew

Homebrew is a missing package manager for Mac OS X. The current user account needs to be an administrator or be granted with administrator privileges using “su” to install Homebrew.

su <administrator_account>
ruby -e "$(curl -fsSL https://raw.github.com/Homebrew/homebrew/go/install)"
brew update
brew doctor

Refer to the Homebrew website at http://brew.sh if any errors at above step.

2.3 Install git and pkg-config

brew install git
brew install pkg-config

2.4 Install thrift 0.9.0

Thrift is needed for installing rhbase. If you donot use HBase, you might skip thrift installation.

Install thrift 0.9.0 instead of 0.9.1. I first installed thrift 0.9.1 (which was the latest version at that time), and found it didn't work well for rhbase installation. And then it was a painful process to figure out the reason, uninstall 0.9.1 and then install 0.9.0.

Do NOT run command below, which will install latest version of thrift (0.9.1 as of 9 May 2014).

## Do NOT run command below !!!
brew install thrift

Instead, follow steps below to install thrift 0.9.0.

$ brew versions thrift

Warning: brew-versions is unsupported and may be removed soon.
Please use the homebrew-versions tap instead:
  https://github.com/Homebrew/homebrew-versions
0.9.1    git checkout eccc96b Library/Formula/thrift.rb
0.9.0    git checkout c43fc30 Library/Formula/thrift.rb
0.8.0    git checkout e5475d9 Library/Formula/thrift.rb
0.7.0    git checkout 141ddb6 Library/Formula/thrift.rb
...

Find the formula for thrift 0.9.0 in above list, and install with that formula.

## go to the homebrew base directory
$ cd $( brew --prefix )

## check out thrift 0.9.0
git checkout c43fc30 Library/Formula/thrift.rb

## instal thrift
brew install thrift

Then we check whether pkg-config path is correct.

pkg-config --cflags thrift

The above command should return -I/usr/local/Cellar/thrift/0.9.0/include/thrift or -I/usr/local/include/thrift. Note that it should end with /include/thrift instead of /include. Otherwise, you will come across errors saying that some .h files can not be found when installing rhbase.

If you have any problem with installing thrift 0.9.0, see details about how to install a specific version of formula with Homebrew at http://stackoverflow.com/questions/3987683/homebrew-install-specific-version-of-formula.

2.5 More instructions

If there are problems with installing other packages above, more instructions can be found at links below.

• http://diggdata.in/post/67561846971/fetch-data-from-hbase-database-from-r-using-rhbase
• https://github.com/RevolutionAnalytics/RHadoop/wiki/rhbase

Note that there are some differences between this process and instructions from the links below. For example, On Mac, there is no libthrift-0.9.0.so but libthrift-0.9.0.dylib, so I haven't run the command below to copy Thrift library.

sudo cp /usr/local/lib/libthrift-0.9.0.so /usr/lib/

3. Environment settings

Run code below in R to set environment variables for Hadoop.

Sys.setenv("HADOOP_PREFIX"="/Users/hadoop/hadoop-1.1.2")
Sys.setenv("HADOOP_CMD"="/Users/hadoop/hadoop-1.1.2/bin/hadoop")
Sys.setenv("HADOOP_STREAMING"="/Users/hadoop/hadoop-1.1.2/contrib/streaming/hadoop-streaming-1.1.2.jar")

Alternatively, add above to ~/.bashrc so that you don't need to set them every time.

export HADOOP_PREFIX=/Users/hadoop/hadoop-1.1.2
export HADOOP_CMD=/Users/hadoop/hadoop-1.1.2/bin/hadoop
export HADOOP_STREAMING=/Users/hadoop/hadoop-1.1.2/contrib/streaming/hadoop-streaming-1.1.2.jar

4. Install RHadoop: rhdfs, rhbase, rmr2 and plyrmr

4.1 Install relevant R packages

install.packages(c("rJava", "Rcpp", "RJSONIO", "bitops", "digest", 
                   "functional", "stringr", "plyr", "reshape2", "dplyr", 
                   "R.methodsS3", "caTools", "Hmisc"))

RHadoop packages are dependent on above packages, which should be installed for all users, instead of in personal library. Otherwise, you may see RHadoop jobs fail with an error saying “package *** is not installed”. For example, to make sure that package functional are installed in the correct library, run commands below and it should be in path/Library/Frameworks/R.framework/Versions/3.1/Resources/library/functional, instead of/Users/YOUR_USER_ACCOUNT/Library/R/3.1/library/functional. If it is in the library under your user account, you need to reinstall it to /Library/Frameworks/R.framework/Versions/3.1/Resources/library/. If your account has no access to it, use an administrator account.

The destination library can be set with function install.packages() using argument lib (see an example below), or with RStudio, choose from a drop-down list under “Install to library” in a pop-up window Install Packages.

## find your R libraries
.libPaths()
#"/Users/hadoop/Library/R/3.1/library" 
#"/Library/Frameworks/R.framework/Versions/3.1/Resources/library"

## check which library a package was installed into
system.file(package="functional")
#"/Library/Frameworks/R.framework/Versions/3.1/Resources/library/functional"

## install package to a specific library
install.packages("functional", lib="/Library/Frameworks/R.framework/Versions/3.1/Resources/library")

In addition to above packages, you are also suggested to install data.table. Without it, I came across an error when running an RHadoop job on a big dataset, although the same job worked fine on a smaller dataset. The reason could be that RHadoop uses data.table to handle large data.

install.packages("data.table")

4.2 Set environment variables HADOOP_CMD and HADOOP_STREAMING

Set environment variables for Hadoop, if you haven't done so at step 6.

Sys.setenv("HADOOP_PREFIX"="/Users/hadoop/hadoop-1.1.2")
Sys.setenv("HADOOP_CMD"="/Users/hadoop/hadoop-1.1.2/bin/hadoop")

4.3 Install RHadoop packages

Download packages rhdfs, rhbase, rmr2 and plyrmr fromhttps://github.com/RevolutionAnalytics/RHadoop/wiki and install them. Same as step 7.1, these packages need to be installed to a library for all users, instead of to a personal library. Otherwise, you would find R-Hadoop jobs fail on those nodes where packages are not installed in the right library.

install.packages("<path>/rhdfs_1.0.8.tar.gz", repos=NULL, type="source")
install.packages("<path>/rmr2_2.2.2.tar.gz", repos=NULL, type="source")
install.packages("<path>plyrmr_0.2.0.tar.gz", repos=NULL, type="source")
install.packages("<path>/rhbase_1.2.0.tar.gz", repos=NULL, type="source")

4.4 Further information

If you follow above instructions but still come across errors at this step, refer to rmr prerequisites and installation at https://github.com/RevolutionAnalytics/RHadoop/wiki/rmr#prerequisites-and-installation.

5. Run an R job on Hadoop

Below is an example to count words in text files from HDFS folder wordcount/data. The R code is fromJeffrey Breen's presentation on Using R with Hadoop.

First, we copy some text files to HDFS folder wordcount/data.

## copy local text file to hdfs
bin/hadoop fs -copyFromLocal /Users/hadoop/try-hadoop/wordcount/data/*.txt wordcount/data/

After that, we can use R code below to run a Hadoop job for word counting. 

Sys.setenv("HADOOP_PREFIX"="/Users/hadoop/hadoop-1.1.2")
Sys.setenv("HADOOP_CMD"="/Users/hadoop/hadoop-1.1.2/bin/hadoop")
Sys.setenv("HADOOP_STREAMING"="/Users/hadoop/hadoop-1.1.2/contrib/streaming/hadoop-streaming-1.1.2.jar")

library(rmr2) 

## map function
map <- function(k,lines) {
  words.list <- strsplit(lines, '\\s') 
  words <- unlist(words.list)
  return( keyval(words, 1) )
}

## reduce function
reduce <- function(word, counts) { 
  keyval(word, sum(counts))
}

wordcount <- function (input, output=NULL) { 
  mapreduce(input=input, output=output, input.format="text", 
            map=map, reduce=reduce)
}


## delete previous result if any
system("/Users/hadoop/hadoop-1.1.2/bin/hadoop fs -rmr wordcount/out")

## Submit job
hdfs.root <- 'wordcount'
hdfs.data <- file.path(hdfs.root, 'data') 
hdfs.out <- file.path(hdfs.root, 'out') 
out <- wordcount(hdfs.data, hdfs.out)

## Fetch results from HDFS
results <- from.dfs(out)

## check top 30 frequent words
results.df <- as.data.frame(results, stringsAsFactors=F) 
colnames(results.df) <- c('word', 'count') 
head(results.df[order(results.df$count, decreasing=T), ], 30)

If you can see a list of words and their frequencies, congratulations and now you are ready to do MapReduce work with R! 

Working with Ebola Dataset

During the first month of training I was given the task to work on ebola Dataset.I was asked to plot the dataset on the Google maps.I gone to the wrong track for the first 15 days.After that I visited udacity.com which saved my life and guided me good.I recommend all the new R developers to follow this Udacity course.


Data Analysis with R

After that I tried hard to load a Google map in R.After 3-4 days of hard work I get this output of google map of Africa.

After getting this I plotted the number of death cases the suspected cases due to Ebola in different countries.In the plot.ly you can showcase your R data.Here is the presentation of Ebola Datatest.

How to create a WordCloud in R

R, the open source package, has become the de facto standard for statistical computing and anything seriously data-related (note I am avoiding the term ‘big data’ here – oops, too late!).  From data mining to predictive analytics to data visualisation, it seems like any self-respecting data professional now uses R. Or at least they pretend to. We all know that most people use Excel when nobody’s watching.

Wordcloud comes under Text mining process in R.Text mining means we are provided with a bunch of text documents and we need to extract different trends regarding the trends of text in the documents i.e the most used keywords in the documents.

1.Create a Corpus:

For creating a word cloud in R,we need to create a corpus of text,so that tm package can process it.A corpus is a collection of documents.

2.Apply Text Mining functions on the Corpus

In the tm package,there are various functions for mining your text i.e converting to lowercase,removing punctuation,removing stopwords etc.

3.Creating a WordCloud:

Now we need to pass the arguments to the wordcloud function and display the result.

How to setup RStudio Server accessible via SSH

RStudio Server enables you to provide a browser based interface (the RStudio IDE) .You can easily access your R work anywhere in the world.All you need is one System having Internet.Major advantages for setting up RStudio Server.

>>Easy sharing of code, data, and other files with colleagues.

>>Allowing multiple users to share access to the more powerful compute resources (memory, processors, etc.) available on a well equipped server.

>>Centralized installation and configuration of R, R packages, TeX, and other supporting libraries.

Downloading and Installation:

You can download the RStudio Server from their official website.RStudio server is available for all major Linux distributions.

RStudio Server Download

Accessing RStudio Server:

RStudio Server by default opens on port 8787.After installing the serv:er,you can redirect your browser to the following address:

http://<server-ip>:8787

RStudio server will prompt for the Username Password for the account you want to Log in.You will only be allowed to log in if the account have access to Home directory.

In case you are unable to access the server you can verify your installation with following command.

$ sudo rstudio-server verify-installation

How to disable secure boot and fast boot in Windows 8

Windows 8 has got a very special feature named "Secure Boot".Until this is enabled you are unable to load any new Operating System on your system.It basically prevent unauthorized Softwares to load into your system.But this also got a disadvantage that it prevents you from creating Dual boot for your system.

Another special feature Windows 8 provide you is "Fast Boot".Fast boot helps you boot your system faster than any other OS.That is why Windows 8 boot at lightening speed.

How to disable Secure boot in Windows 8

1. Press Win+C button to open charm screen.Click Settings.

2.Now click on change PC settings.

3.Select General and under the Advanced Startup click in Restart now as shown below

4.Now your system will restart and new windows will open,select Troubleshoot

5.Under the troubleshoot click on Advanced options and then on UEFI Firmware Settings.Now from here your actual task will begin.

6.Click on Restart and wait for the system to restart.

7.After restart you will be taken to the BIOS Setup menu,if not taken automatically you need to press the F1,F2,Esc key depending on the key your system uses.

8.Under the Security,you will see an option namely Secure boot make it disabled.You might also find this option under the boot menu of your BIOS.If you see UEFI boot option then make it disabled.

9.Now save your Settings and Enjoy the dual boot in your system.

How to disable Fast boot in Windows 8

Another option you also want in order to load any other OS into your system,is to disable fast boot in Windows 8.

1.Go to your Control Panel<Power options.

2.Now click on "Choose what the power buttons do" and then click on "Change settings that are currently unavailable"

3.Now uncheck the "Turn on Fast startup" option.You are done.

Having both of the above steps done,you will be able to create dual boot for your Windows 8 system.

UPDATE,DELETE Operation in PostgreSQL Database

As discussed in previous post you had learnt about two basic operations on database i.e. INSERT,SELECT ,in this post I am going to discuss the another two basic operations of PostgreSQL database i.e. UPDATE and DELETE.Lets get started.

UPDATE operation in PostgreSQL Database:

In this operation,we will make use of UPDATE keyword as used in simple SQL language just like below:

             String sql;
             sql = "UPDATE TABLE_NAME set column_name = value  where id = value;";
             st.executeUpdate(sql);

The example for this can be:

              String sql;
             sql = "UPDATE NEW_GARAGE set age = 25 where id = 4;";
             st.executeUpdate(sql); 

Complete code snippet for Update Operation:

package database;
import java.sql.Connection;
import java.sql.DriverManager;
import java.sql.ResultSet;
import java.sql.SQLException;
import java.sql.Statement;
import java.util.logging.Level;
import java.util.logging.Logger;
public class Update {
    public static void main(String args[])
    {
    Connection c = null;
    Statement st = null;
     {
        try {
            Class.forName("org.postgresql.Driver");
             c = DriverManager.getConnection("jdbc:postgresql://localhost:5432/kanwar","postgres","osm");
             c.setAutoCommit(false);
              st = c.createStatement();
             
             String sql;
             sql = "UPDATE NEW_GARAGE set age = 25 where id = 4;";
             st.executeUpdate(sql);
             c.commit();
         ResultSet rs = st.executeQuery( "SELECT * FROM NEW_GARAGE;" );
         while ( rs.next() )
         {
             int id = rs.getInt("id");
             String name = rs.getString("name");
              int age = rs.getInt("age");
      System.out.println( "ID = " + id );
      System.out.println( "NAME = " + name );
      System.out.println( "AGE = " + age );
      System.out.println();
         }
         rs.close();
         st.close();
         c.close();
        }
   
catch ( Exception e )
{
    System.err.println( e.getClass().getName()+": "+ e.getMessage() );
System.exit(0);
}
          System.out.println("Operation done successfully");  
 }
}
} 

The output for this program goes here:

DELETE Operation in  PostgreSQL Database:

Delete operation in PostgreSQL database is executed the same query as in SQL language.We use DELETE keyword and the data which we want to delete.The syntax for Delete operation is as follow:

String sql = "DELETE from Table_Name where column_name=value;";

The example of this syntax ca be:

String sql = "DELETE from NEW_GARAGE where ID=2;"; 

Complete code snippet for DELETE operation is as below:

package database;
import java.sql.Connection;
import java.sql.DriverManager;
import java.sql.ResultSet;
import java.sql.Statement;

public class Delete {
    public static void main(String args[])
    {
      Connection c =null;
      Statement st = null;
        try
        {
           Class.forName("org.postgresql.Driver");
           c = DriverManager.getConnection("jdbc:postgresql://localhost:5432/kanwar","postgres","osm");  
       
       c.setAutoCommit(false);
       System.out.println("Opened Database Successfully");
        st = c.createStatement();
        String sql = "DELETE from NEW_GARAGE where ID=2;";
        st.executeUpdate(sql);
        c.commit();
        ResultSet rs = st.executeQuery("SELECT * FROM NEW_GARAGE");
       
        while(rs.next())
        {
        int id = rs.getInt("id");
        String name = rs.getString("name");
        int age = rs.getInt("age");
       
        System.out.println( "ID = " + id );  
          System.out.println( "NAME = " + name );
          System.out.println( "AGE = " + age );    
      System.out.println();
      }
      rs.close();
      st.close();
      c.close();
      }
        catch(Exception e)
        {
        System.err.println(e.getClass().getName()+":"+ e.getMessage());
        System.exit(0);
       
        }
        System.out.println("Operation performed Successfully");
        }
        }

     
The output for this program goes here:

Happy learning.Stay tuned.

SELECT,INSERT Operation in PostgreSql Database

PostgreSql as discussed in earlier posts is an advanced database.Now in this post I am going to discuss the two basic database operations in Postgresql i.e. Insert,Select.The remaining two operations i.e. Update,Delete will be discussed in the next post.

1. Insert operation in Postgresql database

As the name suggests,this operation is basically used for Inserting values into your database,below is the command used to Insert data into database using Insert statement.

"INSERT INTO TABLE_NAME(COLUMN1,COLUMN2,COLUMN3)"+ "VALUES(1,'TROY',35);";

Here is the complete code snippet for the Insert operation:

package database;
import java.sql.Connection;
import java.sql.DriverManager;
import java.sql.Statement;
public class Insert_operation {
    public static void main(String args[])
    {
    try
    {
       Statement st = null;
       Connection c = null;
       Class.forName("org.postgresql.Driver");
       c=DriverManager.getConnection("jdbc:postgresql://localhost:5432/kanwar","postgres", "osm");

c.setAutoCommit(false);  
 
    st = c.createStatement();
    String sql;
    sql = "INSERT INTO NEW_GARAGE(ID,NAME,AGE)"+"VALUES(1,'Tarsem',35);";
        st.executeUpdate(sql);
 
        sql = "INSERT INTO NEW_GARAGE(ID,NAME,AGE)"+ "VALUES(2,'Gurpreet',36);";
        st.executeUpdate(sql);
 
   sql = "INSERT INTO NEW_GARAGE(ID,NAME,AGE)"+ "VALUES(3,'Jaspreet',37);";
        st.executeUpdate(sql);
     
          sql = "INSERT INTO NEW_GARAGE(ID,NAME,AGE)"+ "VALUES(4,'Maninder',39);";
        st.executeUpdate(sql);
     
          sql = "INSERT INTO NEW_GARAGE(ID,NAME,AGE)"+ "VALUES(5,'Ranjeet',38);";
        st.executeUpdate(sql);
     
     
     
     
    st.close();
    c.commit();
    c.close();
    }
    catch(Exception e)
            {
                System.err.println( e.getClass().getName()+": "+ e.getMessage() );
                System.exit(0);
            }
 
    System.out.println("Records created successfully");
     
 
    }
}

 This way your records are successfully saved into the database.

2.Select Operation in Postgresql database:

Since the insert operation helps us to insert the records into database,and the select statement help us to select the respective records specified in the query.

You can simply select a record using Select statement just like below:

"SELECT * FROM TABLE_NAME;"

 Here is the complete code snippet for illustrating the use of Select operation

package database;
import java.sql.Connection;
import java.sql.DriverManager;
import java.sql.ResultSet;
import java.sql.Statement;
public class Select_operation {
    public static void main(String args[])
    {
     Connection c = null;
     Statement st = null;
 
      try
      {
       Class.forName("org.postgresql.Driver");
         c= DriverManager.getConnection("jdbc:postgresql://localhost:5432/kanwar" ,"postgres", "osm");
         c.setAutoCommit(false);
        st = c.createStatement();
        ResultSet rs = st.executeQuery( "SELECT * FROM NEW_GARAGE;" );
   
      while ( rs.next() )
      {
        int id = rs.getInt("id");
          String name = rs.getString("name");
          int age = rs.getInt("age");
     
           System.out.println( "ID = " + id );
          System.out.println( "NAME = " + name );
          System.out.println( "AGE = " + age );  
      System.out.println();
      }
      rs.close();
      st.close();
      c.close();
      }
     
   
   
      catch(Exception e)
        {
        System.err.println(e.getClass().getName()+": "+ e.getMessage());
        System.exit(0);
        }
        System.out.println("Operation performed successfully");
     
     
    }
}

Here is the output of the Select query:

Happy learning.Stay tuned.