R: Intro to ggplot()

On By Ben Larson Ph.D.In R

ggplot() is a powerful graphing tool in R. While it is more complex to use than qplot(), its added complexity comes with advantages.

Don’t worry about the complexity, we are going to step into it slowly.

Let’s start by getting a data set. I am going to choose airquality from the R data sets package. You can find a list of data sets from that package here: Link

ggplotIntro

We are going to manipulate some of this data, so first let us set the dataframe to a new variable.

Next, take a look at the structure – str() – we have 6 variables and 153 rows. The first thing I notice is that Month is an int – I don’t want that. I would rather have Month be a factor      (a categorical variable)

ggplotIntro1.jpg

Use factor() to set Month to a factor. Now look at str() readout again. There are 5 levels (months) represented in our data set

ggplotIntro3

ggplot()

here is the basic syntax – ggplot(data, aes(x value, y value))+geom_[type of plot]

ggplot(data = airQ,  aes(x = Wind, y = Temp)) + geom_point()

ggplotIntro4

Now let’s add some color to the chart. Inside aes() – which stands for aesthetics – we are going to add color = Month

 ggplot(data = airQ, aes(x = Wind, y = Temp, color = Month)) + geom_point()

ggplotIntro5

Now add some size. Inside aes() add size = Ozone.

ggplot(data = airQ, aes(x = Wind, y = Temp, color = Month, size = Ozone)) + geom_point()

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The Code

library(ggplot2)

head(airquality)

#-- assign data to a new variable
airQ <- airquality

#-- look at structure
str(airquality)

#-- set month as a factor
airQ$Month <- factor(airQ$Month)
str(airQ)

#-- plot wind vs temp - scatter plot
 ggplot(data = airQ, aes(x = Wind, y = Temp)) + geom_point()
 
#-- plot add factor (Month) as a color
 ggplot(data = airQ, aes(x = Wind, y = Temp, color = Month)) + geom_point()
 
#-- set Ozone as a size element
ggplot(data = airQ, aes(x = Wind, y = Temp, color = Month, size = Ozone)) + geom_point()

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