very best plots

Load libraries and dataset

Code

library(tidyverse)
library(ggplot2)
library(ggridges)
cleanbooks <- read_csv("CLEANBOOKS.csv")

goodreads vs amazon ratings

Code

cleanbooks %>% 
  filter(numgoodreads > 200000) %>% 
  ggplot(aes(y = title)) +
  geom_segment(aes(x = goodreads,
                   y = reorder(title, numgoodreads),
                   xend = amazon,
                   yend = title), color = "#A79E9E") +
  geom_point(aes(x = goodreads, color = "Goodreads"), alpha = 0.6, size = 3) +
  geom_point(aes(x = amazon,
                 color = "Amazon"), alpha = 0.6, size = 3) +
  geom_point(aes(x = personalrate, color = "Personal rating"), alpha = 0.6, size = 3) +
  scale_color_manual(values = c(
    "Goodreads" = "#33a302",
    "Amazon" = "#f3a3a3",
    "Personal rating" = "#87BFFF"
  )) +
  labs(
    title = "Book ratings, Amazon vs Goodreads (and myself)",
    x = "Rating (0-5)",
    y = "Book",
    caption = "only using books I have read and that are highly popular on Goodreads"
  ) +
  theme(
    panel.grid = element_line(color = "#ECE8E8"),
    panel.background = element_rect(color = "#f3a3a3", linewidth = 0.55, fill = "#fff"),
    axis.line = element_line(color = "#33a302"),
    axis.text.y = element_text(hjust = -0.0),
    axis.title.y = element_blank(),
    panel.grid.minor.y = element_line(color = "#D7DADA"),
    panel.grid.major.y = element_line(color = "#D7DADA"),
    panel.grid.minor.x = element_line(color = "#F9FAFA"), # make much paler than y
    panel.grid.major.x = element_line(color = "#F9FAFA"), # make much paler than y
    # why do those go on top of the y lines no matter what I do!!!!
    legend.position = "bottom",
    legend.background = element_blank(),
    legend.title = element_blank()
  )

geom_point and geom_segment together to create lollipop plot
- Used geom_point three times with the color for each specified as the names in the key (“Goodreads”, “Amazon”, “Personal rating”), then used scale_color_manual and scale_fill_manual to name the colors
In theme(): used panel.background with element_rect to make the overall plot outline pink
- Used axis.line with element_line to make the x and y axis lines green
- Typed axis.line after panel.background to have the green line appear on top of the pink line
Used axis.text.y with element_text() only specifying hjust to make the y-axis labels be left aligned

genres I like

Code

cleanbooks %>% 
  filter(genre != "Romance") %>%  # this will serve for now
  # plotting romance gives an empty bar lol
  ggplot() +
  geom_density_ridges(aes(x = enjoyment, 
                          y = genre,
                          color = genre, fill = genre), alpha = 0.5) + 
  labs(
    title = "Enjoyment distribution per book genre",
    x = "Enjoyment rating",
    # DO NOT FUCK with the color key
    caption = "1-10 rating by me of how much I enjoyed books I've read in the past 2 years"
  )  +
  scale_color_manual(values = c(
    "Unrealistic Fiction" = "#BC1B68",
    "Science Fiction" = "#C44579",
    "Realistic Fiction" = "#CB6E8A",
    "Fantasy" = "#D3989B"
  ), aesthetics = "color") +
  scale_fill_manual(values = c(
    "Unrealistic Fiction" = "#440021",
    "Science Fiction" = "#824050",
    "Realistic Fiction" = "#C17F7F",
    "Fantasy" = "#FFBFAE"
  ), aesthetics = "fill")+
  scale_alpha(guide = "none") +
  theme(
    axis.line = element_line(linewidth = .25, color = "#440021"),
    panel.background = element_rect(fill = "#FFF1ED"),
    panel.grid.y = element_line(color = "#F5D2D2"),
    panel.grid.x = element_line(color = "#8FC6C9"),
    axis.title.y = element_blank(),
    plot.background = element_rect(fill = "#FEF5F2"
  ))

Color palettes and gradients made manually with coolors.co
Library ggridges used for genre ridgeline plot