R/C2/More-Functions-in-dplyr-Package/English-timed

Time	Narration
00:01	Welcome to this tutorial on More functions in the dplyr package.
00:07	In this tutorial,we will learn about the following functions in the dplyr package:
00:14	select
00:16	rename
00:18	mutate
00:20	To understand this tutorial, you should know,
00:24	Basics of statistics
00:27	Basics of ggplot2 package
00:31	Data frames
00:33	If not, please locate the relevant tutorials on R on this website.
00:40	This tutorial is recorded on
00:43	Ubuntu Linux OS version 16.04
00:48	R version 3.4.4
00:52	RStudio version 1.1.463
00:57	Install R version 3.2.0 or higher.
01:03	For this tutorial, we will use
01:06	A data frame moviesData.csv
01:11	A script file myVis.R.
01:16	Please download these files from the Code files link of this tutorial.
01:23	I have downloaded and moved these files to DataVis folder.
01:29	This folder is located in myProject folder on my Desktop.
01:36	I have also set the DataVis folder as my Working Directory.
01:42	Let us switch to RStudio.
01:45	Open the script myVis.R in RStudio.
01:50	We have already learnt how to use the filter and arrange functions in the dplyr package.
02:01	Run this script by clicking on the Source button.
02:06	movies data frame and other filtered data frames open in the Source window.
02:13	We will close all the data frames except movies.
02:19	In the Source window, scroll from left to right.
02:24	This will enable us to see the remaining objects of the movies data frame.
02:30	To select the required variables of a data frame we will use the select function.
02:37	It helps us to select only those variables that are required.
02:43	Here, we will use the select function to select title, genre, and imdb rating for all the movies.
02:56	Click on the script myVis.R
03:00	In the Source window, type the following command.
03:05	The first argument in the select function is the name of the data frame. Here it is movies.
03:14	Other arguments are the variables which we will select for all the movies.
03:20	Save the script and run the last two lines of code by pressing Ctrl + Enter keys simultaneously.
03:31	moviesTGI opens in the Source window.
03:36	Here, title, genre, and imdb rating of all the movies are displayed.
03:46	Let us close moviesTGI data frame for now.
03:52	In the Source window, click on movies data frame.
03:57	Scroll the data frame from right to left to see other columns.
04:04	In the data frame, we can see the variables like thtr_rel_day, thtr_rel_month, thtr_rel_year.
04:27	These variables provide information about the day, month and year of the theater release of the movies.
04:38	Let us select these three variables along with the title of all the movies.
04:45	Please note that all the theater-related variable names start with t h t r.
04:53	Click on the script myVis.R.
04:57	In the Source window, type the following command.
05:02	Here, we have used starts_with function.
05:08	It selects all the variables in the movies data frame, whose names start with t h t r.
05:16	Run the last two lines of code.
05:20	moviesTHT opens in the Source window.
05:25	Movies with their titles and theater-release information are shown.
05:33	Let us close moviesTHT data frame for now.
05:38	In the Source window, click on movies.
05:42	Let us change the name of the variable thtr_rel_year.
05:52	For that, we will use the rename function.
05:56	Click on the script myVis.R
06:00	In the Source window, type the following command.
06:05	Here, we are changing the name of the variable thtr_rel_year.
06:14	Run the last two lines of code.
06:19	moviesR opens in the Source window.
06:23	In the Source window, scroll from left to right.
06:28	Observe that the name of the variable thtr_rel_year has changed to rel_year.
06:41	Let us close the data frame moviesR for now.
06:46	In the Source window, click on movies.
06:50	In the Source window, scroll from left to right.
06:55	Suppose we want to add a new variable named CriAud to our movies data frame.
07:04	This variable should contain the difference between critics_score and audience_score. For this, we will use the mutate function.
07:16	mutate function is used to add a new variable and preserve the existing one.
07:23	For simplicity let us remove the variables appearing after audience_score in the movies data frame.
07:33	In the Source window, scroll from right to left.
07:38	We need to select the variables from title to audience_score.
07:46	For this, we will use the select function.
07:50	Click on the script myVis.R
07:54	In the Source window, type the following command.
07:59	Run the current line.
08:02	Now, we will use the mutate function to add a new variable.
08:08	In the Source window, type the following command.
08:13	Remember, we are adding a new variable named CriAud in the movies data frame.
08:22	This is to store the difference of critics score and audience score.
08:29	Run the last two lines of code.
08:33	moviesMu opens in the Source window.
08:37	In the Source window, scroll from left to right.
08:42	A new variable named CriAud is added.
08:48	Let us summarize what we have learnt.
08:52	In this tutorial, we have learnt about the following functions available in the dplyr package:
09:00	select
09:01	rename
09:02	mutate
09:04	We now suggest an assignment.
09:08	Use the built-in data set airquality. Using select function select the variables Ozone, Wind, and Temp in this data set.
09:20	Use the built-in data set mtcars. Rename the variables mpg and cyl with MilesPerGallon and Cylinder, respectively.
09:33	The video at the following link summarises the Spoken Tutorial project.
09:37	Please download and watch it.
09:41	We conduct workshops using Spoken Tutorials and give certificates.
09:46	Please contact us.
09:49	Please post your timed queries in this forum.
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09:59	The FOSSEE team coordinates the TBC project.
10:02	For more details, please visit these sites.
10:07	The Spoken Tutorial project is funded by NMEICT, MHRD, Govt. of India
10:13	The script for this tutorial was contributed by Varshit Dubey (CoE Pune).
10:20	This is Sudhakar Kumar from IIT Bombay signing off. Thanks for watching.

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