Wise_Asynchronous 4/9

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

library(ggplot2)
library(tidyverse)

## ── Attaching core tidyverse packages ──────────────────────── tidyverse 2.0.0 ──
## ✔ dplyr     1.1.2     ✔ readr     2.1.4
## ✔ forcats   1.0.0     ✔ stringr   1.5.0
## ✔ lubridate 1.9.2     ✔ tibble    3.2.1
## ✔ purrr     1.0.2     ✔ tidyr     1.3.0
## ── 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

data(diamonds)

library(ggplot2)

#facet wrap chart for distribution using the diamonds dataset
ggplot(diamonds, aes(x = price, fill = cut)) +
  geom_histogram(bins = 5, color = "white", alpha = 0.8) +
  facet_wrap(~ cut) +
  labs(
    title = "Distribution of Diamond Prices by Cut",
    x = "Price (USD)",
    y = "Count",
    fill = "Cut Quality"
  ) +
  theme_classic() + 
  theme(axis.text.x = element_text(angle = 30, hjust = 1))

#facet grid chart for distribution using the diamonds dataset

ggplot(diamonds, aes(x = price, fill = cut)) +
  geom_histogram(bins = 5, color = "white", alpha = 0.8) +
  facet_grid(~ cut) +
  labs(
    title = "Distribution of Diamond Prices by Cut",
    x = "Price (USD)",
    y = "Count",
    fill = "Cut Quality"
  ) +
  theme_classic() + 
  theme(axis.text.x = element_text(angle = 30, hjust = 1))

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.

p1 = ggplot(mpg, aes(displ, hwy )) + 
  geom_point(color = "purple") + 
  labs(
    title = "Engine Size vs Highway MPG", 
    x = "Engine Displacement",
    y = "Highway MPG"
  ) + 
  theme_classic()

p2 = ggplot(mpg, aes(hwy,fill= class )) + 
  geom_histogram(bins = 10, position = "dodge") + 
  labs(
    title = "Distribution of Highway MPG by Class",
    x = "Highway MPG",
    y = "Count",
    fill = "Vehicle Class") + 
  theme_classic() +
  scale_fill_brewer(palette = "Set2")


p3 = ggplot(mpg, aes(class,hwy, fill = class)) +
  geom_violin(trim = FALSE, alpha = 0.7, color = "white") +
  geom_boxplot(width = 0.15, fill = "white", outlier.size = 0.8) +
  labs(
    title = "Highway MPG Distribution by Vehicle Class",
    x = "Vehicle Class",
    y = "Highway MPG",
    fill = "Class"
  ) +
  scale_fill_brewer(palette = "Set2") +
  theme_classic()
    
install.packages("gridExtra")  # run once

## Installing package into '/cloud/lib/x86_64-pc-linux-gnu-library/4.3'
## (as 'lib' is unspecified)

library(gridExtra)

## 
## Attaching package: 'gridExtra'

## The following object is masked from 'package:dplyr':
## 
##     combine

combined_figure = grid.arrange(p1, p2, p3, ncol = 2)

Try: Side-by-side layout Stacked layout Unequal sizes

Practice Task 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.

# Save PNG
ggsave(
  "combined_figure.png",
  plot = grid.arrange(p1, p2, p3, ncol = 2),
  dpi = 300
)

## Saving 7 x 5 in image

# Save PDF
ggsave(
  "combined_figure.pdf",
  plot = grid.arrange(p1, p2, p3, ncol = 2),
)

## Saving 7 x 5 in image

ggsave("combined_figure.png", combined_figure, dpi = 300)

## Saving 7 x 5 in image

ggsave("combined_figure.pdf", combined_figure)

## Saving 7 x 5 in image

write.csv(mpg, "mpg.csv", row.names = FALSE)