Module 5: Apply 4

Import data

# Load Excel file
data <- read_excel("GDP_vs_PlasticWaste_Analysis.xlsx")
colnames(data) <- c("Country", "GDP", "Waste", "Recycling")

State one question

How does a country’s GDP per capita relate to its per capita plastic waste generation, and do higher-income countries manage waste more sustainably through recycling?

View the dataset

datatable(data, options = list(pageLength = 10, scrollX = TRUE), rownames = FALSE)

Plot data

GDP vs Plastic Waste per Capita

ggplot(data, aes(x = GDP, y = Waste, color = Recycling, size = Recycling)) +
  geom_point(alpha = 0.7) +
  geom_smooth(method = "lm", se = TRUE, color = "darkred", linetype = "dashed") +
  scale_color_gradient(low = "blue", high = "orange") +
  labs(title = "GDP vs Plastic Waste per Capita",
       subtitle = "Point color and size represent recycling rate",
       x = "GDP per Capita (USD)",
       y = "Plastic Waste per Capita (kg)",
       color = "Recycling Rate (%)",
       size = "Recycling Rate (%)") +
  theme_minimal()

GDP vs Recycling Rate

ggplot(data, aes(x = GDP, y = Recycling, label = Country)) +
  geom_point(color = "forestgreen", size = 3) +
  geom_text(check_overlap = TRUE, vjust = -0.5, size = 3) +
  geom_smooth(method = "lm", se = TRUE, color = "black", linetype = "dotted") +
  labs(title = "GDP vs Recycling Rate",
       subtitle = "Countries with higher GDP tend to recycle more",
       x = "GDP per Capita (USD)",
       y = "Recycling Rate (%)") +
  theme_light()

Interpret

Based on the plots and data:

• Higher GDP is associated with higher plastic waste generation, but also higher recycling rates, which is visualized by both the positive slope and color gradient in the first scatter plot.
• The second plot suggests that wealthier nations invest more in sustainable waste management, reflected in higher recycling percentages.