Difference between revisions of "R/C2/Aesthetic-Mapping-in-ggplot2/English"
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Download Files | Download Files | ||
| − | || For this tutorial, we will use* A '''data frame''' '''moviesData.csv''', and | + | || For this tutorial, we will use |
| + | * A '''data frame''' '''moviesData.csv''', and | ||
* A '''script''' file '''aesPlots.R'''. | * A '''script''' file '''aesPlots.R'''. | ||
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What is Aesthetics | What is Aesthetics | ||
| − | || * '''Aesthetic '''is a visual property of the objects in a plot. | + | || |
| + | * '''Aesthetic '''is a visual property of the objects in a plot. | ||
* It includes lines, points, symbols, colors, and position. | * It includes lines, points, symbols, colors, and position. | ||
* It is used to add '''customization '''to our plots. | * It is used to add '''customization '''to our plots. | ||
Revision as of 16:35, 11 July 2019
Title of the script: Aesthetic Mapping in ggplot2
Author: Varshit Dubey (CoE Pune) and Sudhakar Kumar (IIT Bombay)
Keywords: R, RStudio, ggplot, aesthetic, mapping, video tutorial, spoken tutorial
| Visual Cue | Narration |
| Show slide
Opening Slide |
Welcome to this tutorial on Aesthetic Mapping in ggplot2. |
| Show slide
Learning Objective |
In this tutorial, we will learn,
|
|
Show slide Pre-requisites |
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
Please download these files from the Code files link of this tutorial. |
| [Computer screen]
Highlight moviesData.csv and aesPlots.R in the folder aesPlots Point to aesPlots folder. |
I have downloaded and moved these files to aesPlots folder.
This folder is located in myProject folder on my Desktop. I have set aesPlots folder as my Working Directory. |
| Now let us see what is Aesthetic? | |
| Show slide
What is Aesthetics |
|
| Let us switch to RStudio. | |
| Highlight aesPlots.R in the Files window of RStudio | Open the script aesPlots.R in RStudio. |
| Highlight ggplot function in the Source window | Here, we are plotting a scatter plot between critics_score and audience_score of movies. |
| Highlight the Source button | Run this script by clicking on the Source button. |
| Highlight Plots window | Scatter plot appears in the Plots window. |
| Highlight movies in the Source window | movies data frame opens in the Source window. |
| Highlight the plot in the Plots window | In this scatter plot, each point refers to a particular movie.
Suppose we want to color these points according to the genre of the movies. |
| Highlight the scroll bar in the Source window | In the Source window, scroll from left to right. |
| Highlight genre in the Source window | As we can see that there are different genres like
So, we will assign a unique color to each genre. |
| Highlight the script aesPlots.R in the Source window | Click on the script aesPlots.R |
| [RStudio]
ggplot(data = movies, mapping = aes(x = critics_score, y = audience_score, color = genre)) + geom_point() |
In the Source window, type the following commands. |
| Highlight aes in the Source window | Inside aes, we have added color argument and set it to genre. |
| Highlight run button in the Source window | Save the script and run the current line by pressing Ctrl+Enter keys simultaneosuly. |
| Highlight Plots window | Modified scatter plot appears in the Plots window. |
| Click on Zoom button to maximize the plot.
Highlight Plots window |
In the Plots window, click on the Zoom button to maximize the plot. |
| Highlight the plot | We can see that each point is assigned a unique color according to its genre.
In the right side of the plot, we can view the mapping of genres with their colors. |
| Click on X button to close the plot. | Close this plot. |
| Highlight ggplot in the Source window | Now, we will learn how to draw a bar chart using ggplot function. |
| Highlight movies in the Source window | In the Source window, click on movies. |
| Highlight the scroll bar in the Source window | In the Source window, scroll from left to right. |
| Highlight mpaa_rating in the Source window | Let us inspect the object named mpaa underscore rating in movies. |
| Highlight the script aesPlots.R in the Source window | Click on the script aesPlots.R |
| [RStudio]
str(movies$mpaa_rating) levels(movies$mpaa_rating) |
In the Source window, type the following commands. |
| Highlight run button in the Source window | Run the last two lines of code. |
| Highlight output in the Console window | mpaa_rating is a factor.
It has 6 levels like
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| Highlight output in the Console window | So, our bar chart will have 6 different bars.
|
| [RStudio]
ggplot(data = movies, mapping = aes(x = mpaa_rating)) + geom_bar() |
In the Source window, type the following command. |
| Highlight aes in the Source window | Here, we have mapped mpaa underscore rating on X-axis. |
| Highlight geom_bar in the Source window | Next, we have used geom underscore bar as we are plotting a bar chart.
|
| Highlight run button in the Source window | Run the current line. |
| Highlight Plots window | The bar chart appears in the Plots window. |
| Highlight plot in the Plots window | Now, we will learn how to add labels to this bar chart. |
| Point to geom_bar().
Type Space plus sign >> press Enter. |
In the Source window, after geom_bar(), type space plus sign and press Enter. |
| [RStudio]
labs(y = "Rating count", title = "Count of mpaa_rating") |
Now type the following command. |
| Highlight labs in the Source window | Here, we have used labs argument to add label and title to the bar chart. |
| Highlight run button in the Source window | Run the current line. |
| Highlight Plots window | The modified bar chart appears in the Plots window. |
| Highlight fifth bar in the Plots window | We can see that most of the movies have been rated as R in mpaa_rating.
Suppose, in this bar chart, we want to view the distribution of movies by genre. |
| [RStudio]
ggplot(data = movies, mapping = aes(x = mpaa_rating, fill = genre)) + geom_bar() + labs(y = "Rating count", title = "Count of mpaa_rating by genre") |
In the Source window, type the following command. |
| Highlight fill in the Source window | Inside aes, we have added fill argument and set it to genre. |
| Highlight run button in the Source window | Run the current line. |
| Highlight Plots window | The modified bar chart appears in the Plots window. |
| Highlight Plots window | In the Plots window, click on the Zoom button to maximize the plot. |
| Highlight fifth bar in the Plots window | There are seven different colors in each bar. Besides the plot, the meaning of each color has been given |
| Click on X button to close the plot. | Close the plot. |
| Highlight movies in the Source window | In the Source window, click on movies data frame. |
| Highlight runtime in the Source window | Now we will plot a histogram for the object named as runtime in movies.
Recall that, we have already learned how to plot a histogram using hist function. Now we will use ggplot2 package to plot a histogram. |
| Highlight the script aesPlots.R in the Source window. | Click on the script aesPlots.R |
| [RStudio]
ggplot(data = movies, mapping = aes(x = runtime)) + geom_histogram() + labs(x = "Runtime of movies", title = "Distribution of movies' runtime") |
In the Source window, type the following command. |
| Highlight run button in the Source window | Save the script and run the current line. |
| Highlight output in the Console window | There are some warning messages, which we will ignore for now. |
| Highlight Plots window | The histogram appears in the Plots window. |
| Let us summarize what we have learnt. | |
| Show slide
Summary |
In this tutorial, we have learnt,
|
| Show slide
Assignment |
We now suggest an assignment.
|
| 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.
|
| 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
Acknowledgment |
The Spoken Tutorial project is funded by NMEICT, MHRD, Govt. of India |
| Show Slide
Thank You |
The script for this tutorial was contributed by Varshit Dubey (CoE Pune).
|
