CDS-102: Lab 6 Workbook

Name: Nathaniel Sposit

March 2, 2017

In [1]:

# Run this code to install the GGally package (you only need to run this once)
install.packages("GGally", lib = "~/Rlibs")

The downloaded source packages are in
	‘/tmp/Rtmpqyi3HM/downloaded_packages’

In [2]:

# Run this code block to load the Tidyverse package
.libPaths(new = "~/Rlibs")
library(tidyverse)
library("GGally")

# This converts the iris data.frame to a tibble
iris <- as_tibble(iris)

Loading tidyverse: ggplot2
Loading tidyverse: tibble
Loading tidyverse: tidyr
Loading tidyverse: readr
Loading tidyverse: purrr
Loading tidyverse: dplyr
Conflicts with tidy packages ---------------------------------------------------
filter(): dplyr, stats
lag():    dplyr, stats

Attaching package: ‘GGally’

The following object is masked from ‘package:dplyr’:

    nasa

In [3]:

print(iris)

# A tibble: 150 × 5
   Sepal.Length Sepal.Width Petal.Length Petal.Width Species
          <dbl>       <dbl>        <dbl>       <dbl>  <fctr>
         5.1         3.5          1.4         0.2  setosa
         4.9         3.0          1.4         0.2  setosa
         4.7         3.2          1.3         0.2  setosa
         4.6         3.1          1.5         0.2  setosa
         5.0         3.6          1.4         0.2  setosa
         5.4         3.9          1.7         0.4  setosa
         4.6         3.4          1.4         0.3  setosa
         5.0         3.4          1.5         0.2  setosa
         4.4         2.9          1.4         0.2  setosa
        4.9         3.1          1.5         0.1  setosa
# ... with 140 more rows

In [4]:

petal.width.length <- ggplot(data = iris) + geom_point(mapping = aes(Petal.Length, Petal.Width))
ggsave("PetalWidthLength.png", plot = petal.width.length, device = "png", scale = 1, width = 5, height = 4)
print(petal.width.length)

In [5]:

sepal.width.length <- ggplot(data = iris) + geom_point(mapping = aes(Sepal.Length, Sepal.Width))
ggsave("SepalWidthLength.png", plot = sepal.width.length, device = "png", scale = 1, width = 5, height = 4)
print(sepal.width.length)

In [6]:

petal.width.length.species <- ggplot(data = iris) + geom_point(mapping = aes(Petal.Length, Petal.Width, color = Species))
ggsave("PetalWidthLengthSpecies.png", plot = petal.width.length.species, device = "png", scale = 1, width = 5, height = 4)
print(petal.width.length.species)

In [7]:

sepal.width.length.species <- ggplot(data = iris) + geom_point(mapping = aes(Sepal.Length, Sepal.Width, color = Species))
ggsave("SepalWidthLengthSpecies.png", plot = sepal.width.length.species, device = "png", scale = 1, width = 5, height = 4)
print(sepal.width.length.species)

In [11]:

scatter.matrix <- ggpairs(data = iris, columns=1:4, upper = list(continuous = "points"), diag = NULL, mapping = aes(color=Species), legend = 3) + theme(legend.position = "right")
ggsave("ScatterplotMatrix.png", plot = scatter.matrix, device = "png", scale = 1, width = 5, height = 4)
print(scatter.matrix)

In [9]:

sepal.histo <- ggplot(iris, aes(Sepal.Length)) + geom_histogram(binwidth=5) + facet_wrap(~Species)
ggsave("SepalHisto.png", plot = sepal.histo, device = "png", scale = 1, width = 5, height = 4)
print(sepal.histo)

In [10]:

sepal.density <- ggplot(iris, aes(Sepal.Length)) + geom_density(kernel = "gaussian") + facet_wrap(~Species)
ggsave("SepalDensity.png", plot = sepal.density, device = "png", scale = 1, width = 5, height = 4)
print(sepal.density)

In [ ]: