A Spaghetti plot is a line plot with many lines displayed together. With more than a few (~5?) groups this kind of graphic gets really hard to read, and thus provides little insight about the data. Let’s make an example with the evolution of baby names in the US from 1880 to 2015.

# Libraries
library(tidyverse)
library(hrbrthemes)
library(kableExtra)
options(knitr.table.format = "html")
library(babynames)
library(streamgraph)
library(viridis)
library(DT)
library(plotly)

# Load dataset from github
data <- babynames %>% 
  filter(name %in% c("Mary","Emma", "Ida", "Ashley", "Amanda", "Jessica",    "Patricia", "Linda", "Deborah",   "Dorothy", "Betty", "Helen")) %>%
  filter(sex=="F")

# Plot
data %>%
  ggplot( aes(x=year, y=n, group=name, color=name)) +
    geom_line() +
    scale_color_viridis(discrete = TRUE) +
    theme(
      legend.position="none",
      plot.title = element_text(size=14)
    ) +
    ggtitle("A spaghetti chart of baby names popularity") +
    theme_ipsum()