R/C2/Aesthetic-Mapping-in-ggplot2/English-timed

Time	Narration
00:01	Welcome to this tutorial on Aesthetic Mapping in ggplot2.
00:06	In this tutorial, we will learn,
00:10	What is aesthetic
00:12	How to create plots using aesthetic
00:16	Tuning parameters in aesthetic
00:20	To understand this tutorial, you should know,
00:24	Basics of statistics
00:27	Basics of ggplot2 package
00:30	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, and
01:10	A script file aesPlots.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 aesPlots folder.
01:30	This folder is located in myProject folder on my Desktop.
01:36	I have set aesPlots folder as my Working Directory.
01:42	Now let us see what is Aesthetic?
01:46	Aesthetic is a visual property of the objects in a plot.
01:50	It includes lines, points, symbols, colors, and position.
01:57	It is used to add customization to our plots.
02:01	Let us switch to RStudio.
02:05	Open the script aesPlots.R in RStudio.
02:11	Here, we are plotting a scatter plot between critics_score and audience_score of movies.
02:19	Run this script by clicking on the Source button.
02:24	Scatter plot appears in the Plots window.
02:28	movies data frame opens in the Source window.
02:33	In this scatter plot, each point refers to a particular movie.
02:39	Suppose we want to color these points according to the genre of the movies.
02:45	In the Source window, scroll from left to right.
02:49	As we can see that there are different genres like
02:54	Drama
02:56	Comedy
02:58	Horror
03:00	Documentary, etc.
03:03	So, we will assign a unique color to each genre.
03:08	Click on the script aesPlots.R
03:12	In the Source window, type the following commands.
03:18	Inside aes, we have added color argument and set it to genre.
03:26	Save the script and run the current line by pressing Ctrl+ Enter keys simultaneously.
03:36	Modified scatter plot appears in the Plots window.
03:41	In the Plots window, click on the Zoom button to maximize the plot.
03:47	We can see that each point is assigned a unique color according to its genre.
03:54	In the right side of the plot, we can view the mapping of genres with their colors.
04:01	Close this plot.
04:03	Now, we will learn how to draw a bar chart using ggplot function.
04:09	In the Source window, click on movies.
04:13	In the Source window, scroll from left to right.
04:17	Let us inspect the object named mpaa underscore rating in movies.
04:26	Click on the script aesPlots.R
04:31	In the Source window, type the following commands.
04:36	Run the last two lines of code.
04:40	mpaa_rating is a factor.
04:45	It has 6 levels like
04:47	G NC-17 PG PG-13 R, and Unrated.
04:55	So, our bar chart will have 6 different bars.
05:00	Each bar will represent the number of movies in each level.
05:06	In the Source window, type the following command.
05:11	Here, we have mapped mpaa underscore rating on X-axis.
05:18	Next, we have used geom underscore bar as we are plotting a bar chart.
05:25	Similarly, we can use
05:27	geom_line to draw a line chart
05:31	geom_boxplot to draw a box plot
05:36	Run the current line.
05:39	The bar chart appears in the Plots window.
05:43	Now, we will learn how to add labels to this bar chart.
05:49	In the Source window, after geom_bar(), type space plus sign and press Enter.
05:58	Now type the following commands.
06:02	Here, we have used labs argument to add label and title to the bar chart.
06:09	Run the current line.
06:12	The modified bar chart appears in the Plots window.
06:17	We can see that most of the movies have been rated as R in mpaa_rating.
06:26	Suppose, in this bar chart, we want to view the distribution of movies by genre.
06:33	In the Source window, type the following command.
06:37	Inside aes, we have added fill argument and set it to genre.
06:44	Run the current line.
06:47	The modified bar chart appears in the Plots window.
06:52	In the Plots window, click on the Zoom button to maximize the plot.
06:58	There are seven different colors in each bar.
07:03	Besides the plot, the meaning of each color has been given.
07:09	Close the plot.
07:12	In the Source window, click on movies data frame.
07:17	Now we will plot a histogram for the object named as runtime in movies.
07:25	Recall that, we have already learned how to plot a histogram using hist function.
07:32	Now we will use ggplot2 package to plot a histogram.
07:38	Click on the script aesPlots.R
07:43	In the Source window, type the following command.
07:48	Save the script and run the current line.
07:53	There are some warning messages, which we will ignore for now.
07:58	The histogram appears in the Plots window.
08:02	Let us summarize what we have learnt.
08:06	In this tutorial, we have learnt,
08:09	What is aesthetic
08:11	How to create plots using aesthetic
08:15	Tuning parameters in aesthetic
08:19	We now suggest an assignment.
08:22	Using built-in data set mtcars, draw a bar chart from the object cyl.
08:30	Add suitable labels to this bar chart.
08:34	The video at the following link summarises the Spoken Tutorial project.
08:39	Please download and watch it.
08:42	We conduct workshops using Spoken Tutorials and give certificates.
08:47	Please contact us.
08:49	Please post your timed queries in this forum.
08:53	Please post your general queries in this forum.
08:57	The FOSSEE team coordinates the TBC project.
09:01	For more details, please visit these sites.
09:05	The Spoken Tutorial project is funded by MHRD, Govt. of India
09:12	The script for this tutorial was contributed by Varshit Dubey (CoE Pune).
09:19	This is Sudhakar Kumar from IIT Bombay signing off. Thanks for watching.

Contributors and Content Editors

Sakinashaikh