R/C2/Merging-and-Importing-Data/English-timed

Time	Narration
00:01	Welcome to the spoken tutorial on Merging and Importing Data
00:07	In this tutorial, we will learn how to:
00:11	Use built-in functions for exploring a data frame
00:16	Merge two data frames.
00:19	Import data in different formats in R
00:24	To understand this tutorial, you should know
00:28	Data frames in R
00:31	R script in RStudio
00:34	How to set working directory in RStudio
00:39	If not, please locate the relevant tutorials on R on this website.
00:46	This tutorial is recorded on,
00:50	Ubuntu Linux OS version 16.04
00:55	R version 3.4.4
01:00	RStudio version 1.1.456
01:06	Install R version 3.2.0 or higher.
01:12	For this tutorial, we will use,
01:15	five data frames in different formats and
01:20	a script file myDataSet.R.
01:24	Please download these files from the Code files link of this tutorial.
01:30	I have downloaded these files from Code files link and moved them to DataMerging folder in myProject folder on the Desktop.
01:42	I have also set this folder as my Working Directory.
01:48	Let us switch to RStudio.
01:51	Open the script myDataSet.R in RStudio.
01:57	For this, click on the script myDataSet.R.
02:03	Script myDataSet.R opens in Rstudio.
02:09	Run this script by clicking on Source button.
02:14	captaincyOne appears in the Source window.
02:18	We will use some built-in functions of R to explore captaincyOne.
02:24	For all the built-in functions used in this tutorial, please refer to the Additional Material.
02:31	First, we will use summary function.
02:35	Click on the script myDataSet.R
02:39	In the Source window, type summary and then captaincyOne in parentheses.
02:46	Save the script and run the current line by pressing Ctrl+Enter keys simultaneously.
02:55	In the Console window, scroll up to locate the output.
03:02	Statistical parameters for each column of captaincyOne are shown on the Console.
03:09	In the Source window, press Enter.
03:13	Press Enter at the end of every command.
03:17	Now, let us look at class function.
03:21	In the Source window, type class and then captaincyOne in parentheses.
03:29	Save the script and run the current line.
03:34	class function returns the class of captaincyOne, which is data frame.
03:41	Next let us look at typeof function.
03:45	In the Source window, type typeof and then captaincyOne in parentheses.
03:53	Save the script and run the current line.
03:58	typeof function returns the storage type of captaincyOne, which is list.
04:05	To know more about typeof function, we will access the help section of RStudio.
04:12	In the Console window, type help, within parentheses typeof. Press Enter.
04:20	typeof determines the R internal type or storage mode of any object.
04:27	Click on the Files tab.
04:30	Clear the Console window by clicking on the broom icon.
04:35	Click on the data frame captaincyOne.
04:39	Now, let us extract two rows from top of captaincyOne.
04:45	For this, we will use head function.
04:49	Click on the script myDataSet.R
04:53	In the Source window, type head within parentheses captaincyOne comma space 2.
05:02	Save the script and run the current line.
05:07	The top two rows of captaincyOne are shown on the Console window.
05:13	Click on the data frame captaincyOne.
05:17	Suppose we want to extract two rows from bottom of captaincyOne.
05:24	For this, we will use the tail function.
05:28	Click on the script myDataSet.R
05:32	In the Source window, type tail within parentheses captaincyOne comma space 2.
05:41	Save the script and run the current line.
05:46	The last two rows of captaincyOne are shown on the Console window.
05:52	Next, let us learn about str function.
05:57	This function is used to display the structure of an R object.
06:03	In the Source window, type str within parentheses captaincyOne.
06:10	Save the script and run the current line.
06:15	The structural details of captaincyOne are shown on the Console.
06:21	Now, we will look at merging of data frames.
06:26	Merging data frames has advantages like:
06:30	It makes data more available.
06:33	It helps in improving data quality.
06:37	Combining similar data also reduces data complexity.
06:42	Let us switch to RStudio.
06:45	We will learn how to merge two data frames CaptaincyData.csv and CaptaincyData2.csv.
06:55	We will declare a variable captaincyTwo to store and read CaptaincyData2.csv.
07:03	In the Source window, type the following command and press Enter.
07:11	Now, type View within parentheses captaincyTwo.
07:17	Save the script and run the last two lines.
07:23	The contents of captaincyTwo appear in the Source window.
07:28	This data frame has the same captains as that in captaincyOne.
07:34	However, it has different information about them like the number of matches drawn.
07:40	Now, we will update captaincyOne by adding information from captaincyTwo.
07:48	For this, we use merge function.
07:52	Click on the script myDataSet.R
07:56	I am resizing the Source window.
07:59	In the Source window, type the following command.
08:04	Press Enter.
08:06	In the merge function, we use column names by which we want to merge two data frames.
08:13	Here, it is names.
08:16	Now, type View and captaincyOne in parentheses.
08:22	Save the script and run these two lines.
08:28	The contents of the updated captaincyOne appear in the Source window.
08:35	Close the two tabs captaincyOne and captaincyTwo.
08:41	Now, we will learn how to import data of different formats in R.
08:47	We shall add one comment first.
08:50	In the Source window, type # hash space Importing data in different formats.
08:58	Now, let us import CaptaincyData.xml file.
09:04	For that, we need to install XML package.
09:09	Make sure that you are connected to Internet.
09:13	We need to install Ubuntu package libxml2-dev before installing XML package.
09:23	Information on how to install this package, is provided in the Additional Material.
09:29	I have already installed libxml2-dev package.
09:35	Hence, I will proceed for installing XML package now.
09:41	On the Console window, type install dot packages.
09:47	Now, type XMLinside double quotes and in parentheses.
09:53	Press Enter. We will wait until R installs the package.
10:00	Then, we load this package using library function.
10:05	Click on the script myDataSet.R
10:09	Since we are loading a package, we will add it at the top of the script.
10:15	In the Source window, scroll up.
10:18	Now, at the top of the script myDataSet.R, type library and XML in parentheses.
10:29	Save the script and run this line.
10:34	Now, in the Source window, click on the next line after the comment Importing data in different formats.
10:43	Type the following command and press Enter.
10:49	Then type View and xmldata in parentheses.
10:56	Save the script and run these two lines.
11:00	The contents of the xml file are shown here.
11:05	Next let us learn how to import CaptaincyData.txt.
11:12	Click on the script myDataSet.R
11:16	In the Source window, type the following command
11:21	and press Enter.
11:24	Next, type View and txtdata in parentheses.
11:30	Save the script and run these two lines.
11:35	The contents of the txt file are shown.
11:40	Now, we will learn how to import data from user interface of Rstudio.
11:47	I am resizing the Source window.
11:51	We will import the Excel file CaptaincyData.xlsx using this method.
12:00	Please ensure that you have packages like readxl and Rcpp installed in your system.
12:08	In the top right corner of RStudio, click on the Environment tab.
12:15	In the Environment tab, click on Import Dataset.
12:20	From the drop-down menu, select From Excel.
12:25	A window named Import Excel Data appears.
12:30	You can select a file on your computer or type the URL from which you want to load an Excel file.
12:39	We will select a file on our computer.
12:43	In the upper right corner of this window, near File/Url text field, click on Browse.
12:52	I will select the file CaptaincyData.xlsx located in DataMerging folder.
13:01	This folder is in myProject folder on the Desktop.
13:06	Click Open to load this file.
13:10	Below the field File/Url, RStudio shows the preview of the Excel file being imported.
13:17	At the bottom right corner of this window, you can see the code for importing this Excel file.
13:24	Finally, click on the Import button.
13:28	The contents of the Excel file are shown here.
13:32	Let us summarize what we have learnt.
13:36	In this tutorial, we have learnt how to:
13:40	Use built-in functions for exploring a data frame
13:45	Merge two data frames
13:48	Import data in different formats in R
13:53	We now suggest an assignment.
13:57	Using built-in dataset iris, implement all the functions we have learnt in this tutorial.
14:04	The video at the following link summarises the Spoken Tutorial project.
14:09	Please download and watch it.
14:12	We conduct workshops using Spoken Tutorials and give certificates.
14:18	Please contact us.
14:21	Please post your timed queries in this forum.
14:25	Please post your general queries in this forum.
14:29	The FOSSEE team coordinates the TBC project. For more details, please visit these sites.
14:37	The Spoken Tutorial project is funded by NMEICT, MHRD, Govt. of India
14:44	The script for this tutorial was contributed by Shaik Sameer (FOSSEE Fellow 2018).
14:52	This is Sudhakar Kumar from IIT Bombay signing off. Thanks for watching.

Contributors and Content Editors

Sakinashaikh