R Notebook

Download an install the current version of R and RStudio.

Do 3.2.4 Exercises 1, 2, 3, 4, 5 Do 3.3.1 Exercises 1, 2, 3, 4, 6 Do 3.5.1 Exercises 1, 2, 4

3.2.4 Excercises

1. Run ggplot(data = mpg). What do you see?

When you plot ggplot(data=mpg) you see nothing because the rest of the filters (aesthetics) were not added yet.

ggplot(data=mpg)

2. How many rows are in mpg? How many columns?

234 rows and 11 columns.

mpg

3. When you plot ggplot(data=mpg) you see nothing because the rest of the filter are not added yet.

Drv stands for F= front wheel drive, R= Rear wheel drive, and 4= 4wd.

4. Make a scatterplot of hwy vs cyl.

ggplot(data = mpg) + 
  geom_point(mapping = aes(x = hwy, y = cyl))

5. What happens if you make a scatterplot of class vs drv? Why is the plot not useful?

It is not very useful because most of the points overlap each other and makes it not a very good visualization tool.

ggplot(data = mpg) + 
  geom_point(mapping = aes(x = class, y = drv))

3.3.1 Excercises

1. What is gone wrong with this code? Why are the points not blue?

The reason that this code was wrong was due to the parenthesis being in the wrong location.

ggplot(data = mpg) + 
  geom_point(mapping = aes(x = displ, y = hwy, color = "blue"))

ggplot(data = mpg) + 
  geom_point(mapping = aes(x = displ, y = hwy), color = "blue")

2. Which variables in mpg are categorical? Which variables are continuous?

?mpg

glimpse(mpg)

Error in glimpse(mpg) : could not find function "glimpse"

3. Map a continuous variable to color, size, and shape. How do these aesthetics behave differently for categorical vs. continuous variables?

Continuous variables are not suggested to be used with shape aesthetics, shows error. When using color it shows a darker color for smaller values. When using size, the bigger the size the larger the value.

4. What happens if you map the same variable to multiple aesthetics?

It is define not advised.

6. What happens if you map an aesthetic to something other than a variable name, like aes(colour = displ < 5)?

It states the color to be true or false.

3.5.1 Excercises

1.What happens if you facet on a continuous variable?

R will try to separate each facet to the point where it wouldn’t be that useful.

ggplot(data = mpg) + 
  geom_point(mapping = aes(y = hwy, x = cyl)) + 
  facet_wrap(~ displ, nrow = 2)

2. What do the empty cells in plot with facet_grid(drv ~ cyl) mean? How do they relate to this plot?

Empty cells mean there are no observations in the data that have that unique combination of values.

ggplot(data = mpg) + 
  geom_point(mapping = aes(x = displ, y = hwy)) + 
  facet_grid(drv ~ cyl)

4. Take the first faceted plot in this section:

ggplot(data = mpg) + 
  geom_point(mapping = aes(x = displ, y = hwy, color = class)) + 
  facet_wrap(~ class, nrow = 2)

What are the advantages to using faceting instead of the color aesthetic? What are the disadvantages? How might the balance change if you had a larger data set?

Any advantage to using faceting instead of color aesthetics is helps visualize individual trends and some disadvantages can be due to not seeing both variables correlation.The color aesthetic is fine when your data set is small, but with larger data sets points may begin to overlap with one another.