The code provided appears to be mostly correct. However, there are a few potential issues:

1. The geom_density function is being used in the plotting code, but it’s not clear why this is necessary. If you want to plot a density curve, you should use the density function from the stats package.

2. The name and value columns are being converted to numeric values using as.numeric(), but this may cause issues if there are any non-numeric values in these columns.

3. The geom_density function is being used, which is not necessary for a line plot.

4. The pivot_longer function is being used correctly, but the -id argument might be unnecessary depending on the structure of the data frame.

5. There are some typos and formatting issues in the original code.

Here’s an updated version of the plotting code that addresses these issues:

library(ggplot2)
library(tidyverse)

df %>% 
  rownames_to_column("id") %>% 
  pivot_longer(-id) %>%  
  ggplot(aes(x=name, y=value, group=id, color=id))+
  geom_line()

This code should produce a basic line plot with the provided values. If you need to add a density curve or modify the plot further, you can use additional functions from the ggplot2 package.

Bonus Update:

To add more colors and customize the plot further, you can use the following updated code:

library(ggplot2)
library(tidyverse)

df %>% 
  rownames_to_column("id") %>% 
  pivot_longer(-id) %>%  
  ggplot(aes(x=name, y=value, group=id, color=factor(id)))+
  geom_line(size = 1)+ 
  labs(x="", y="")+
  theme_hc()+
  scale_color_manual(values= c("maroon", "red","orange", "gold",
                               "cadetblue2","dodgerblue",
                               "blue", "black", "green")
                     )+
  theme(legend.position = "right")

This code adds more colors to the plot and customizes the line appearance using scale_color_manual.

Last modified on 2023-05-05