Difference between revisions of "R/C2/Operations-on-Matrices-and-Data-Frames/English-timed"
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Revision as of 16:42, 5 June 2020
Time | Narration |
00:01 | Welcome to the spoken tutorial on Operations on Matrices and Data Frames. |
00:08 | In this tutorial, we will learn how to: |
00:13 | Perform operations on matrices |
00:16 | Add rows or columns to a data frame |
00:20 | To understand this tutorial, you should know |
00:24 | Data frames and Matrices in R |
00:27 | R script in RStudio |
00:32 | How to set working directory in RStudio |
00:37 | If not, please locate the relevant tutorials on R on this website. |
00:44 | This tutorial is recorded on |
00:47 | Ubuntu Linux OS version 16.04 |
00:53 | R version 3.4.4 |
00:58 | RStudio version 1.1.456 |
01:05 | Install R version 3.2.0 or higher. |
01:10 | For this tutorial, we will use the data frame CaptaincyData.csv and the script file myMatrix.R. |
01:21 | Please download these files from the Code files link of this tutorial. |
01:28 | I have downloaded and moved these files to MatrixOps folder' in myProject folder on the Desktop. |
01:39 | I have also set MatrixOps folder as my Working directory. |
01:46 | Let us switch to Rstudio. |
01:51 | Open the script myMatrix.R in RStudio. |
01:56 | For this, click on the script myMatrix.R |
02:02 | Script myMatrix.R opens in Rstudio. |
02:08 | Recall that, we had created a matrix named matrixA. |
02:14 | This matrix was extracted as a subset from the captaincy data frame. |
02:21 | We will use matrixA here also. |
02:25 | Run this script myMatrix.R to load the values in the Workspace. |
02:32 | captaincy data frame opens in the Source window. |
02:37 | I will resize the Source window. |
02:41 | Now let us learn how to find the inverse of matrixA. |
02:48 | Click on the script myMatrix.R |
02:53 | In the Source window, type solve, within parentheses matrixA. |
03:00 | Press Enter. Press Enter at the end of every command. |
03:07 | Save the script and run this line. |
03:12 | The inverse of matrixA in shown in the Console window. |
03:18 | For more information on calculating inverse of a matrix in R, please refer to the Additional materials section on this website. |
03:29 | Now let us calculate the sum of all the elements in matrixA. |
03:36 | First, we shall use nested for loops for calculating this sum. |
03:43 | Also, we shall estimate the time taken to calculate the sum in this way. |
03:50 | Let us add a comment - Calculating sum using for loop in the script. |
03:57 | In the Source window, type # hash space Calculating sum using for loop. |
04:05 | Press Enter. To calculate the time taken, we record the present time. |
04:12 | In the Source window, type start Time with capital T. |
04:18 | Then press Alt and -(hyphen) keys simultaneously. |
04:23 | Next, type Sys dot time followed by parentheses. |
04:30 | Sys.time() is used to find the absolute date-time value in the current time. |
04:38 | Let us initialise a variable totalSum. |
04:43 | In the Source window, type totalSum |
04:47 | then press Alt and -(hyphen) keys simultaneously. Then type zero. |
04:55 | This variable will store the sum of elements in matrixA. |
05:01 | Now, we will create two for loops to iterate through the rows and columns of the matrixA. |
05:10 | In the Source window, type for in parentheses i space in space 1 colon 3 space |
05:21 | Now type opening curly bracket. RStudio automatically adds a closing curly bracket. |
05:30 | Press Enter just after the opening curly bracket and type the following command. |
05:39 | Press Enter after the closing curly bracket of outer loop for(i in 1:3). |
05:48 | In the Source window, type print totalSum in parentheses. |
05:54 | Now, we record the current time again. |
05:59 | Type endTime then press Alt and -(hyphen) keys simultaneously. Type Sys dot time parentheses. |
06:10 | Press Enter. Type endTime space minus sign space startTime to know the total time taken.
And save the script. |
06:23 | I am resizing the Source window. |
06:27 | Run the block of code from the comment line Calculating sum using for loop to the end. |
06:35 | The totalSum is evaluated to be 237. |
06:41 | The time taken to calculate the sum of elements in matrixA using for loop is approximately 8 milliseconds. |
06:51 | However, it may vary from system to system. |
06:56 | Now, let us calculate the sum of all elements in matrixA using the sum function. |
07:05 | We shall estimate the time taken to calculate the sum in this way also. |
07:12 | In the script myMatrix.R, add a comment Calculating sum using inbuilt function. |
07:21 | In the Source window, type # hash space Calculating sum using inbuilt function. |
07:30 | Now, type the following commands. |
07:35 | Save the script and run the block of code from the comment line Calculating sum using inbuilt function to the end. |
07:46 | The time taken to calculate the sum of elements using sum function is 1.6 milliseconds. |
07:56 | Whereas, it took 8 milliseconds to calculate the same sum using for loop. |
08:04 | So, it is advisable to use inbuilt functions of R. |
08:10 | Let us learn how to calculate sum of each row and sum of each column. |
08:18 | In the Source window, type rowSums matrixA in parentheses. |
08:26 | Next, type colSums matrixA in parentheses. |
08:32 | Save the script and run these two lines to see the corresponding sums on the Console. |
08:40 | I am resizing the Console window to see the output properly. |
08:47 | Now let us learn how to add rows and columns to an existing data frame. |
08:55 | Click on the captaincy data frame. |
08:59 | Let us add a new row to the captaincy data frame. |
09:04 | Click on the script myMatrix.R |
09:09 | In the Source window, type the following command. Press Enter . |
09:24 | Press Enter after the comma for better visibility. |
09:30 | I am resizing the Source window |
09:34 | We have used rbind() function with the following arguments |
09:40 | name of the data frame to which we want to add the new row. Here, it is captaincy. |
09:48 | the row to be added as an argument to data.frame(). |
09:54 | To data.frame() function, we provide the values according to the columns of the actual data frame. |
10:03 | names = “Kohli” |
10:06 | Y = 2016 |
10:10 | played = 30 |
10:13 | won = 20 |
10:17 | lost = 9 |
10:20 | victory = 20/30 |
10:24 | In the Source window, type View within parentheses captaincy |
10:30 | Save the script and run the last two lines of code. |
10:37 | One new row with the details of Kohli is added in the captaincy data frame. |
10:44 | Now let us create a new column named defeat in the captaincy data frame. |
10:52 | Click on the script myMatrix.R. |
10:57 | In the Source window, type the following command. |
11:03 | Press Enter. Now we add defeat as a new column in captaincy data frame. |
11:11 | In the Source window, type the following command Press Enter. |
11:17 | We have used cbind() function with following two arguments: |
11:23 | name of the data frame to which we want to add the new column. |
11:28 | Here, it is captaincy. name of the column to be added. Here, it is defeat. |
11:37 | Now type View, captaincy in parentheses |
11:42 | Save the script and run the block of code starting from the declaration of defeat to the end. |
11:52 | defeat column is added in the captaincy data frame. |
11:58 | Let us summarize what we have learnt. |
12:04 | In this tutorial, we have learned how to: |
12:07 | Perform operation on matrices |
12:11 | Add rows or columns to a data frame |
12:16 | We now suggest an assignment. |
12:20 | Consider 2 vectors (9,10,11,12) and (13,14,15,16). |
12:30 | Create a 4 by 2 matrix from these two vectors. |
12:35 | Add another vector (17,18,19,20) as a column to the previous matrix. |
12:45 | For solutions, please refer to the Additional materials section on this website. |
12:52 | The video at the following link summarises the Spoken Tutorial project. |
12:58 | Please download and watch it. |
13:01 | We conduct workshops using Spoken Tutorials and give certificates. Please contact us. |
13:11 | Please post your timed queries in this forum. |
13:16 | Please post your general queries in this forum. |
13:21 | The FOSSEE team coordinates the TBC project. For more details, please visit these sites. |
13:30 | The Spoken Tutorial project is funded by NMEICT, MHRD, Govt. of India |
13:37 | The script for this tutorial was contributed by Shaik Sameer (FOSSEE Fellow 2018). |
13:46 | This is Sudhakar Kumar from IIT Bombay signing off. |
13:51 | Thanks for watching. |