Combine Line and Area Plot
R
# Load the ggplot2 librarylibrary(ggplot2)# Sample datatime <- 1:10values <- c(3, 5, 9, 12, 7, 15, 20, 18, 25, 30)data <- data.frame(Time = time, Values = values)# Create a combined area plot and line chartcombined_plot <- ggplot(data, aes(x = Time, y = Values)) + geom_area(fill = "blue", alpha = 0.3) + geom_line(color = "red", size = 1.5) + labs(title = "Combined Area Plot and Line Chart", x = "Time", y = "Values") + theme_minimal()# Display the combined plotprint(combined_plot) |
Output:
Combined Area & Line Plot
- We define some sample data in a data frame with two columns: Time and Values.
- We create a combined plot using ggplot with two geometries.
- geom_area creates the area plot with a blue fill (fill = “blue”) and a transparency level of 0.3 (alpha = 0.3).
- geom_line adds the line chart on top of the area plot, making it red (color = “red”) and with a thicker line (size = 1.5).
- We add a title, x-axis label, and y-axis label using labs.
- Finally, you apply a minimal theme to the plot with theme_minimal().
A Data Visualization Duel: Line Charts vs. Area Charts
In R Programming Language Data visualization is a crucial tool for conveying information effectively. When it comes to representing data trends and patterns over time, two popular choices are line charts and area charts. In this article, we’ll stage a “duel” between line charts and area charts, exploring their characteristics, use cases, advantages, and potential pitfalls to help you choose the right visualization technique for your data.