R/C2/OperationsonMatricesandDataFrames/English
Title of script: Operations on Matrices and Data Frames
Author: Shaik Sameer (IIIT Vadodara) and Sudhakar Kumar (IIT Bombay)
Keywords: R, RStudio, matrices, data frames, adding row, adding column, video tutorial
Visual Cue  Narration 
Show slide
Opening slide 
Welcome to the spoken tutorial on Operations on Matrices and Data Frames. 
Show slide
Learning Objectives 
In this tutorial, we will learn how to:

Show slide
Prerequisites 
To understand this tutorial, you should know
If not, please locate the relevant tutorials on R on this website. 
Show slide
System Specifications 
This tutorial is recorded on
Install R version 3.2.0 or higher. 
Show slide
Download Files 
For this tutorial, we will use the data frame CaptaincyData.csv and the script file myMatrix.R.
Please download these files from the Code files link of this tutorial. 
[Computer screen]
Highlight CaptaincyData.csv and myMatrix.R in the folder MatrixOps 
I have downloaded and moved these files to MatrixOps folder' in myProject folder on the Desktop.
I have also set MatrixOps folder as my Working directory. 
Let us switch to RStudio.  
Click myMatrix.R in RStudio
Point to myMatrix.R in Rstudio 
Open the script myMatrix.R in RStudio.
For this, click on the script myMatrix.R Script myMatrix.R opens in Rstudio. 
Highlight matrixA in the Source widow  Recall that, we had created a matrix named matrixA.
This matrix was extracted as a subset from the captaincy data frame. We will use matrixA here also. 
Highlight the Source button  Run this script myMatrix.R to load the values in the Workspace. 
Highlight captaincy in the Source window  captaincy data frame opens in the Source window. 
I will resize the Source window.  
Highlight matrixA in the Environment window.  Now let us learn how to find the inverse of matrixA. 
Click on the script myMatrix.R  
[RStudio]
solve(matrixA) 
In the Source window, type solve, within parentheses matrixA.
Press Enter. Press Enter at the end of every command. 
Press Ctrl + S >> Press Ctrl+Enter keys.  Save the script and run this line. 
Highlight the output in the Console window  The inverse of matrixA in shown in the Console window. 
For more information on calculating inverse of a matrix in R, please refer to the Additional materials section on this website.  
[RStudio]
Highlight matrixA in the Environment window 
Now let us calculate the sum of all the elements in matrixA.
First, we shall use nested for loops for calculating this sum. Also, we shall estimate the time taken to calculate the sum in this way. 
[RStudio]
# Calculating sum using for loop 
Let us add a comment  Calculating sum using for loop in the script.
In the Source window, type # hash space Calculating sum using for loop. Press Enter. 
[RStudio]
startTime < Sys.time() 
To calculate the time taken, we record the present time.
In the Source window, type start Time with capital T. Then press Alt and (hyphen) keys simultaneously. Next, type Sys dot time followed by parentheses. 
Highlight Sys.time in the Source window  Sys.time() is used to find the absolute datetime value in the current time. 
[RStudio]
totalSum < 0 
Let us initialise a variable totalSum.
In the Source window, type totalSum then press Alt and (hyphen) keys simultaneously. Then type zero. This variable will store the sum of elements in matrixA. 
[RStudio]
for(i in 1:3) { } 
Now, we will create two for loops to iterate through the rows and columns of the matrixA.
In the Source window, type for in parentheses i space in space 1 colon 3 space Now type opening curly bracket. RStudio automatically adds a closing curly bracket. 
[RStudio]
for(j in 1:3) { totalSum < totalSum + matrixA[i,j] } 
Press Enter just after the opening curly bracket and type the following command. 
[RStudio]
print(totalSum) 
Press Enter after the closing curly bracket of outer loop for(i in 1:3).
In the Source window, type print totalSum in parentheses. 
[RStudio]
endTime < Sys.time() endTime  startTime 
Now, we record the current time again.
Type endTime then press Alt and (hyphen) keys simultaneously. Now type Sys dot time parentheses. Press Enter. Type endTime space minus sign space startTime to know the total time taken. And save the script. 
I am resizing the Source window.  
[RStudio]
Highlight the sum in Console window 
Run the block of code from the comment line Calculating sum using for loop to the end.
The totalSum is evaluated to be 237. 
[RStudio]
Highlight the time taken in Console window 
The time taken to calculate the sum of elements in matrixA using for loop is approximately 8 milliseconds.
However, it may vary from system to system. 
Highlight matrixA in the Source window  Now, let us calculate the sum of all elements in matrixA using the sum function. 
We shall estimate the time taken to calculate the sum in this way also.  
[RStudio]
# Calculating sum using inbuilt function 
In the script myMatrix.R, add a comment Calculating sum using inbuilt function.
In the Source window, type # hash space Calculating sum using inbuilt function. 
[RStudio]
startTime < Sys.time() sum(matrixA) endTime < Sys.time() endTime  startTime 
Now, type the following commands. 
[RStudio]
Highlight the time taken in the Console window 
Save the script and run the block of code from the comment line Calculating sum using inbuilt function to the end.
The time taken to calculate the sum of elements using sum function is 1.6 milliseconds. Whereas, it took 8 milliseconds to calculate the same sum using for loop. 
Cursor on the interface.  So, it is advisable to use inbuilt functions of R. 
Cursor on the interface  Let us learn how to calculate sum of each row and sum of each column. 
[RStudio]
rowSums(matrixA) colSums(matrixA) 
In the Source window, type rowSums matrixA in parentheses.
Next, type colSums matrixA in parentheses. Save the script and run these two lines to see the corresponding sums on the Console. 
I am resizing the Console window to see the output properly.  
Now let us learn how to add rows and columns to an existing data frame.  
Click on the captaincy data frame.  
Highlight captaincy data frame in the Source window  Let us add a new row to the captaincy data frame. 
Click on the script myMatrix.R  
[RStudio]
captaincy < rbind(captaincy, data.frame(names="Kohli", Y = 2016, played = 30, won = 20, lost = 9, victory = 20/30)) 
In the Source window, type the following command. Press Enter .
Press Enter after the comma for better visibility. . 
I am resizing the Source window  
Highlight captaincy in the Source window  We have used rbind() function with the following arguments

Highlight data.frame in the Source window  To data.frame() function, we provide the values according to the columns of the actual data frame.

[RStudio]
View(captaincy) Highlight new row in the Source window 
In the Source window, type View within parentheses captaincy
Save the script and run the last two lines of code. One new row with the details of Kohli is added in the captaincy data frame. 
[RStudio]
defeat < captaincy$lost / captaincy$played 
Now let us create a new column named defeat in the captaincy data frame.
Click on the script myMatrix.R. In the Source window, type the following command. Press Enter. 
captaincy < cbind(captaincy, defeat)  Now we add defeat as a new column in captaincy data frame.
In the Source window, type the following command Press Enter. 
Highlight cbind in the Source window  We have used cbind() function with following two arguments:

View(captaincy)  Now type View, captaincy in parentheses
Save the script and run the block of code starting from the declaration of defeat to the end. defeat column is added in the captaincy data frame. 
Let us summarize what we have learnt.  
Show slide
Summary 
In this tutorial, we have learned how to:

Show slide
Assignment 
We now suggest an assignment.
For solutions, please refer to the Additional materials section on this website. 
Show slide
About the Spoken Tutorial Project 
The video at the following link summarises the Spoken Tutorial project.
Please download and watch it. 
Show slide
Spoken Tutorial Workshops 
We conduct workshops using Spoken Tutorials and give certificates.
Please contact us. 
Show Slide
Forum to answer questions 
Please post your timed queries in this forum. 
Show Slide
Forum to answer questions 
Please post your general queries in this forum. 
Show Slide
Textbook Companion 
The FOSSEE team coordinates the TBC project.
For more details, please visit these sites. 
Show Slide
Acknowledgement 
The Spoken Tutorial project is funded by NMEICT, MHRD, Govt. of India 
Show Slide
Thank You 
The script for this tutorial was contributed by Shaik Sameer (FOSSEE Fellow 2018).
This is Sudhakar Kumar from IIT Bombay signing off. Thanks for watching. 