Part 1

Practice Task 1 Using either penguins or diamonds:

Create a faceted plot: Example: distribution or scatterplot Create one using facet_wrap, and one using facet_grid in the layout that makes the most sense Make sure: Labels are clear Colors are readable Theme is clean

install.packages("ggplot2")
## Installing package into '/cloud/lib/x86_64-pc-linux-gnu-library/4.5'
## (as 'lib' is unspecified)
install.packages("patchwork")
## Installing package into '/cloud/lib/x86_64-pc-linux-gnu-library/4.5'
## (as 'lib' is unspecified)
library(ggplot2)
library(patchwork)
data(diamonds)
head(diamonds)
## # A tibble: 6 × 10
##   carat cut       color clarity depth table price     x     y     z
##   <dbl> <ord>     <ord> <ord>   <dbl> <dbl> <int> <dbl> <dbl> <dbl>
## 1  0.23 Ideal     E     SI2      61.5    55   326  3.95  3.98  2.43
## 2  0.21 Premium   E     SI1      59.8    61   326  3.89  3.84  2.31
## 3  0.23 Good      E     VS1      56.9    65   327  4.05  4.07  2.31
## 4  0.29 Premium   I     VS2      62.4    58   334  4.2   4.23  2.63
## 5  0.31 Good      J     SI2      63.3    58   335  4.34  4.35  2.75
## 6  0.24 Very Good J     VVS2     62.8    57   336  3.94  3.96  2.48
pl1=ggplot(diamonds,aes(x=carat,y=price,color=cut))
pl1=pl1+geom_point()
pl1=pl1+facet_wrap(~cut)
pl1=pl1+labs(title="scatter plot that shows facet wrap by price and cut")
pl1=pl1+theme_bw()

pl1

pl2=ggplot(diamonds,aes(x=carat,y=price,color=cut))
pl2=pl2+geom_point()
pl2=pl2+facet_grid(color~cut)
pl2=pl2+labs(title="scatter plot that shows facet grid by price and cut with the gird being color by cut")
pl2=pl2+theme_bw()
pl2

# Part 2 Practice Task 2 Create 3–4 different plots (e.g., scatterplot, barplot, density plot) Combine them into a single multi-panel figure using patchwork/ggforce Make sure you collect the legends when appropriate.

Try:

Side-by-side layout Stacked layout Unequal sizes

install.packages("patchwork")
## Installing package into '/cloud/lib/x86_64-pc-linux-gnu-library/4.5'
## (as 'lib' is unspecified)
library(patchwork)
library(dplyr)
## 
## Attaching package: 'dplyr'
## The following objects are masked from 'package:stats':
## 
##     filter, lag
## The following objects are masked from 'package:base':
## 
##     intersect, setdiff, setequal, union
library(ggforce)

point_plot= diamonds %>%
  ggplot(aes(x=carat,y=price,color=cut))+
  geom_point()
point_plot

point_plot2= diamonds %>%
  ggplot(aes(x=cut,fill=cut))+
  geom_bar()
point_plot2

point_plot3=diamonds %>%
  ggplot(aes(x=cut,fill=cut))+
  geom_density()
point_plot3

p=(point_plot+point_plot2)/point_plot3
p+
  plot_layout(guides = "collect")&theme(legend.position = "top")

# Part 3 Please write code to perform each of these functions.

Export your combined figure:

As a PNG (300 dpi) As a PDF Export your dataframe as a CSV file, and your PNG as an image.

p

ggsave("patchworkplot.png")
## Saving 7 x 5 in image
ggsave("patchworkplot.pdf")
## Saving 7 x 5 in image
write.csv(diamonds,file="diamond_df.csv",row.names=FALSE)