R: implementing `ggplot2` when combining multiple geoms and working with inconsistent scales
Could someone explain I'm working through a tutorial and I'm trying to create a plot in R using `ggplot2` that combines a line graph and a bar chart on the same axes, but I'm working with issues with the scales not aligning correctly... The line graph represents a trend over time, while the bars show discrete counts for each month. I've attempted to use `scale_y_continuous()` to set limits, but the resulting graph still displays an inconsistent scale between the two geoms. Here's a simplified version of my code: ```R library(ggplot2) # Sample data set.seed(123) data <- data.frame( month = factor(rep(month.abb[1:12], each = 2)), count = c(rpois(12, 20), rpois(12, 100)), type = rep(c('A', 'B'), 12) ) # Base ggplot with line and bar plot <- ggplot(data, aes(x = month)) + geom_bar(data = subset(data, type == 'B'), aes(y = count), stat = 'identity', fill = 'blue', alpha = 0.5) + geom_line(data = subset(data, type == 'A'), aes(y = count * 0.2), group = 1, color = 'red', size = 1) + scale_y_continuous(sec.axis = sec_axis(~./0.2, name = 'Count for A')) + labs(title = 'Monthly Counts and Trends') print(plot) ``` Despite using the `sec.axis`, the scales don't seem to align properly, and the line graph looks squished. I've tried adjusting the transformation factors, but I need to seem to get a satisfactory outcome. Also, the legend is not clear as to which color corresponds to which geom. Is there a better approach to combine these two types of visualizations effectively? Any help with correct scaling and legend management would be greatly appreciated! I'm using `ggplot2` version 3.3.5 and have installed all dependencies properly. I'm coming from a different tech stack and learning R. Is there a simpler solution I'm overlooking? This is my first time working with R 3.11. Hoping someone can shed some light on this.