wk10

 

hotdogs <- read.csv("http://datasets.flowingdata.com/hot-dog-contest-winners.csv")
head(hotdogs)

##   Year                       Winner Dogs.eaten       Country New.record
## 1 1980 Paul Siederman & Joe Baldini       9.10 United States          0
## 2 1981              Thomas DeBerry       11.00 United States          0
## 3 1982               Steven Abrams       11.00 United States          0
## 4 1983                 Luis Llamas       19.50        Mexico          0
## 5 1984               Birgit Felden        9.50       Germany          0
## 6 1985             Oscar Rodriguez       11.75 United States          0

library("ggplot2")
#find color codes
my_colors <- c("#4285F4", "#DB4437", "#F4B400", "#0F9D58", "#AB47BC", "#00ACC1", "#FF7043", "#9E9D24", "#5E35B1", "#EF6C00")

# Assign colors to each bar based on their value
colors <- my_colors[cut(hotdogs$Dogs.eaten, breaks = length(my_colors), labels = FALSE)]

# Create the barplot
barplot(hotdogs$Dogs.eaten, names.arg = hotdogs$Year, col=colors, border="white",
        main = "Nathan's Hot Dog Eating Contest Results, 1980-2010",  xlab="Year", ylab="Hot dogs and buns (HDBs) eaten",
        ylim = c(0, 80), xlim = c(0, length(hotdogs$Year) + 1), las = 2, cex.axis = 0.8, cex.lab = 0.9, font.lab = 2)

#2

my_colors <- c("#F44336", "#9C27B0", "#3F51B5", "#4CAF50", "#FFC107")

# Define a custom theme with a white background and no gridlines
my_theme <- theme(panel.background = element_rect(fill = "white"),
                  panel.grid.major = element_blank(),
                  panel.grid.minor = element_blank())

# Create the plot. change geom_bar to geom_col
ggplot(hotdogs) +
  geom_col(aes(x = Year, y = Dogs.eaten, fill = factor(New.record)), width = 0.8) +
  scale_fill_manual(values = my_colors) +
  labs(title = "Nathan's Hot Dog Eating Contest Results, 1980-2010",
       x = "Year",
       y = "Hot dogs and buns (HDBs) eaten",
       fill = "New Record") +
  my_theme +
  coord_flip() +
  theme(plot.title = element_text(face = "bold", size = 20),
        axis.title = element_text(face = "bold", size = 16),
        axis.text = element_text(size = 14),
        legend.position = "bottom",
        legend.title = element_text(face = "bold", size = 14),
        legend.text = element_text(size = 12))

#This code creates a horizontal bar chart using the ggplot2 package in R to visualize the results of Nathan's hot dog eating contest between 1980 and 2010. The my_colors variable is used to set custom colors for each bar. A custom theme is defined with a white background and no gridlines. The plot includes a title, x and y labels, and a legend showing whether a new record was set. The coord_flip() function is used to flip the x and y axes.


#4
library(gridExtra)

## Warning: package 'gridExtra' was built under R version 4.2.3

# First plot
plot1 <- qplot(unemploy/pop, uempmed, data = economics, geom = c("point", "path"), color = "darkred") +
  xlab("Unemployment rate") +
  ylab("Median duration of unemployment") +
  ggtitle("Unemployment rate and median duration of unemployment") +
  theme_classic() +
  theme(legend.position = "none")

## Warning: `qplot()` was deprecated in ggplot2 3.4.0.

# Second plot
plot2 <- qplot(unemploy/pop, uempmed, data = economics, geom = c("point", "path"), color = I("blue")) +
  xlab("Unemployment rate") +
  ylab("Median duration of unemployment") +
  ggtitle("Unemployment rate and median duration of unemployment by year") +
  theme_classic() +
  theme(legend.position = "none")

# Arrange the plots in a grid
grid.arrange(plot1, plot2, ncol = 2)

#This code creates two plots side-by-side using the R package gridExtra. Both plots show the relationship between unemployment rate and median duration of unemployment using the economics dataset. The plots have different color schemes and titles. The theme() function is used to remove the legend.