Basic Visualization R

Exercises from the book “https://r4ds.had.co.nz/data-visualisation.html”

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

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

  3. What does the drv variable describe? Read the help for ?mpg to find out.

  4. Make a scatterplot of hwy vs cyl.

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


install.packages("tidyverse")
library(tidyverse)
library(tidyverse)
Warning: package 'tidyverse' was built under R version 4.5.1
Warning: package 'ggplot2' was built under R version 4.5.2
Warning: package 'purrr' was built under R version 4.5.1
── Attaching core tidyverse packages ──────────────────────── tidyverse 2.0.0 ──
✔ dplyr     1.1.4     ✔ readr     2.1.5
✔ forcats   1.0.0     ✔ stringr   1.5.2
✔ ggplot2   4.0.2     ✔ tibble    3.2.1
✔ lubridate 1.9.4     ✔ tidyr     1.3.1
✔ purrr     1.1.0     
── Conflicts ────────────────────────────────────────── tidyverse_conflicts() ──
✖ dplyr::filter() masks stats::filter()
✖ dplyr::lag()    masks stats::lag()
ℹ Use the conflicted package (<http://conflicted.r-lib.org/>) to force all conflicts to become errors
mpg
# A tibble: 234 × 11
   manufacturer model      displ  year   cyl trans drv     cty   hwy fl    class
   <chr>        <chr>      <dbl> <int> <int> <chr> <chr> <int> <int> <chr> <chr>
 1 audi         a4           1.8  1999     4 auto… f        18    29 p     comp…
 2 audi         a4           1.8  1999     4 manu… f        21    29 p     comp…
 3 audi         a4           2    2008     4 manu… f        20    31 p     comp…
 4 audi         a4           2    2008     4 auto… f        21    30 p     comp…
 5 audi         a4           2.8  1999     6 auto… f        16    26 p     comp…
 6 audi         a4           2.8  1999     6 manu… f        18    26 p     comp…
 7 audi         a4           3.1  2008     6 auto… f        18    27 p     comp…
 8 audi         a4 quattro   1.8  1999     4 manu… 4        18    26 p     comp…
 9 audi         a4 quattro   1.8  1999     4 auto… 4        16    25 p     comp…
10 audi         a4 quattro   2    2008     4 manu… 4        20    28 p     comp…
# ℹ 224 more rows
#Run ggplot(data = mpg). What do you see?

ggplot(data = mpg)

# An empty plot

Creating a scatter plot

# How many rows are in mpg? How many columns?
glimpse(mpg)
Rows: 234
Columns: 11
$ manufacturer <chr> "audi", "audi", "audi", "audi", "audi", "audi", "audi", "…
$ model        <chr> "a4", "a4", "a4", "a4", "a4", "a4", "a4", "a4 quattro", "…
$ displ        <dbl> 1.8, 1.8, 2.0, 2.0, 2.8, 2.8, 3.1, 1.8, 1.8, 2.0, 2.0, 2.…
$ year         <int> 1999, 1999, 2008, 2008, 1999, 1999, 2008, 1999, 1999, 200…
$ cyl          <int> 4, 4, 4, 4, 6, 6, 6, 4, 4, 4, 4, 6, 6, 6, 6, 6, 6, 8, 8, …
$ trans        <chr> "auto(l5)", "manual(m5)", "manual(m6)", "auto(av)", "auto…
$ drv          <chr> "f", "f", "f", "f", "f", "f", "f", "4", "4", "4", "4", "4…
$ cty          <int> 18, 21, 20, 21, 16, 18, 18, 18, 16, 20, 19, 15, 17, 17, 1…
$ hwy          <int> 29, 29, 31, 30, 26, 26, 27, 26, 25, 28, 27, 25, 25, 25, 2…
$ fl           <chr> "p", "p", "p", "p", "p", "p", "p", "p", "p", "p", "p", "p…
$ class        <chr> "compact", "compact", "compact", "compact", "compact", "c…

#What does the drv variable describe? Read the help for ?mpg to find out.
?mpg
starting httpd help server ... done
#drv
#the type of drive train, where f = front-wheel drive, r = rear wheel drive, 4 = 4wd
#Make a scatterplot of hwy vs cy

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

#What happens if you make a scatterplot of class vs drv? Why is the plot not useful?
ggplot(data = mpg) +
  geom_point(mapping = aes (x = class , y = drv))

Do cars with big engines use more fuel than cars with small engines? 

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

#changing colour
ggplot(data = mpg, aes(x = displ, y = hwy)) +
  geom_point(colour = "blue")

#changing colour
ggplot(data = mpg, aes(x = displ, y = hwy)) +
  geom_point(colour = "blue") +
  geom_smooth(method = "lm" )
`geom_smooth()` using formula = 'y ~ x'

#notice how the colour doesnt change when mapped inside aestatic
ggplot(data = mpg) + 
  geom_point(mapping = aes(x = displ, y = hwy , color = "blue"))

#changing colour
ggplot(data = mpg, aes(x = displ, y = hwy, colour = class, shape = class )) +
  geom_point() 
Warning: The shape palette can deal with a maximum of 6 discrete values because more
than 6 becomes difficult to discriminate
ℹ you have requested 7 values. Consider specifying shapes manually if you need
  that many of them.
Warning: Removed 62 rows containing missing values or values outside the scale range
(`geom_point()`).

ggplot(data = mpg, aes(x = displ, y = hwy, colour = class )) +
  geom_point() +
  facet_wrap(~ trans, nrow = 4)

mpg
# A tibble: 234 × 11
   manufacturer model      displ  year   cyl trans drv     cty   hwy fl    class
   <chr>        <chr>      <dbl> <int> <int> <chr> <chr> <int> <int> <chr> <chr>
 1 audi         a4           1.8  1999     4 auto… f        18    29 p     comp…
 2 audi         a4           1.8  1999     4 manu… f        21    29 p     comp…
 3 audi         a4           2    2008     4 manu… f        20    31 p     comp…
 4 audi         a4           2    2008     4 auto… f        21    30 p     comp…
 5 audi         a4           2.8  1999     6 auto… f        16    26 p     comp…
 6 audi         a4           2.8  1999     6 manu… f        18    26 p     comp…
 7 audi         a4           3.1  2008     6 auto… f        18    27 p     comp…
 8 audi         a4 quattro   1.8  1999     4 manu… 4        18    26 p     comp…
 9 audi         a4 quattro   1.8  1999     4 auto… 4        16    25 p     comp…
10 audi         a4 quattro   2    2008     4 manu… 4        20    28 p     comp…
# ℹ 224 more rows
#The diamonds dataset comes in ggplot2 and contains information about ~54,000 diamonds, including the price, carat, color, clarity, and cut of each diamond.

ggplot(data = diamonds,mapping = aes(x = cut,y = stat(prop), group = 1)) + 
  geom_bar(fill = "blue")
Warning: `stat(prop)` was deprecated in ggplot2 3.4.0.
ℹ Please use `after_stat(prop)` instead.