Which R package can I use to plot kernel density plots per year?-CodePudding

I measured the number of occurrences of exclamation marks in the abstract and title of papers per year. Now, I want to show the distribution of this number for each individual year using a kernel density estimation. I want to plot my data in a way that I found in another publication (Plavén-Sigray et al. eLife 2017,

Do you have any idea how I could achieve this using R? I would be glad if you could provide a package. I added some toy data along with what I tested so far.

library(ggplot2)
set.seed(176)
df = data.frame(
  id = seq(1:2000), 
  amount = sample(0:3, 2000, replace = TRUE),
  year = sample(1990:2010, 2000, replace = T)
)
ggplot(df, aes(x = year, y = amount) )  
  geom_density_2d()    
  geom_density_2d_filled()  
  geom_density_2d(colour = "black")

I get the following result which is not really what I want:

Any help would be appreciated. Thank you in advance!

CodePudding user response：

You can get a plot like this in ggplot directly without additional packages. Here's a full reprex:

set.seed(1)

df <- data.frame(year = rep(1920:2000, each = 100), 
                 amount = rnorm(8100, rep(120:200, each = 100), 20))

library(tidyverse)

df %>%
  group_by(year) %>%
  summarize(Amount = density(amount, from = min(df$amount), 
                             to = max(df$amount))$x,
            Density = density(amount, from = min(df$amount), 
                              to = max(df$amount))$y) %>%
  ggplot(aes(year, Amount, fill = Density))  
  geom_raster(interpolate = TRUE)  
  scale_fill_viridis_c(option = "magma")  
  theme_minimal(base_size = 20)  
  coord_cartesian(expand = 0)  
  theme(legend.position = "top",
        legend.key.width = unit(3, "cm"),
        legend.title = element_text(vjust = 1))