Grouped Stacked Bar Plot

R

# Load the ggplot2 package
library(ggplot2)
 
# Sample data
sales_data <- data.frame(
  Category = c("Electronics", "Clothing", "Books", "Furniture"),
  North = c(250, 180, 90, 450),
  South = c(220, 150, 140, 310),
  West = c(280, 100, 100, 380)
)
 
# Create a visually appealing grouped stacked bar plot
ggplot(sales_data, aes(x = Category)) +
  geom_bar(aes(y = North, fill = "North"), stat = "identity") +
  geom_bar(aes(y = South, fill = "South"), stat = "identity") +
  geom_bar(aes(y = West, fill = "West"), stat = "identity") +
  labs(
    title = "Sales by Product Category and Region",
    y = "Total Sales",
    fill = "Region"
  ) +
  scale_fill_manual(
    values = c("North" = "#1f77b4", "South" = "#ff7f0e", "West" = "#2ca02c"),
    labels = c("North Region", "South Region", "West Region")
  ) +
  theme_minimal() +
  theme(legend.position = "top")

Output:

Sales by Product Category and Region

In this example, we use sales data for four product categories (Electronics, Clothing, Books, Furniture) across three regions (North, South, West). We create a grouped stacked bar plot to visualize how sales are divided within each category and region.
Different fill colors (blue, orange, green) are used to represent the three regions (North, South, West).
The bars are stacked for each product category, showing the total sales for each category.
The legend is positioned at the top for better readability.
Custom fill colors and labels are specified using scale_fill_manual for improved aesthetics.

Clustered Bar Plot in R

One of the most popular packages for data visualisation is ggplot2, which can be used to create a clustered bar plot in R.

Table of Content

Clustered Bar Plot
Simple Clustered Bar Plot
Grouped Stacked Bar Plot
Clustered Bar Plot with Multiple Groups
Clustered Bar Plot in R using Plotly
Conclusion

Grouped Stacked Bar Plot

R

Clustered Bar Plot in R

Table of Content

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