Box Plots - Sheet 2

# Load necessary libraries
library(ggplot2)
library(tidyr)

# Read data from CSV file
Sheet2 <- read.csv("Sheet2.csv")

# Convert `% Improved`, `% Unchanged`, `% Worsened` to numeric
Sheet2$X..Improved <- as.numeric(sub("%", "", Sheet2$X..Improved))
Sheet2$X..Unchanged <- as.numeric(sub("%", "", Sheet2$X..Unchanged))
Sheet2$X..Worsened <- as.numeric(sub("%", "", Sheet2$X..Worsened))

# Reshape the data for plotting
Sheet2_long <- pivot_longer(Sheet2, cols = c(`X..Worsened`, `X..Unchanged`, `X..Improved`), names_to = "Status", values_to = "Percentage")

# Box plot showing distribution of percentages for each measure (monochrome)
box_plot <- ggplot(Sheet2_long, aes(x = Measure, y = Percentage)) +
  geom_boxplot() +
  facet_wrap(~ Status) +  # Facet by Status (3 separate plots)
  labs(title = "Distribution of Percentages for Each Measure",
       x = "Measure",
       y = "Percentage") +
  theme() +
  theme(axis.text.x = element_text(angle = 45, hjust = 1),
        legend.position = "none")  # Remove legend

# Display the plot
print(box_plot)