Is this what you are trying to accomplish?
library(tidyverse)
library(scales)
Liam_2013.df <- data.frame(
row.names = c("9369", "9865","10652","11419"),
year = c(2013L, 2013L, 2013L, 2013L),
count = c(72L, 94L, 192L, 140L),
rank = c(10L, 10L, 11L, 21L),
total = c(498L, 498L, 498L, 498L),
perc = c(0.144578313253012,0.188755020080321,
0.385542168674699,0.281124497991968),
gender = as.factor(c("MALE","MALE","MALE",
"MALE")),
ethnicity = as.factor(c("ASIAN AND PACIFIC ISLANDER",
"BLACK NON HISPANIC","HISPANIC",
"WHITE NON HISPANIC")),
name = as.factor(c("Liam","Liam","Liam",
"Liam"))
)
blank_theme <- theme_minimal()+
theme(
axis.title.x = element_blank(),
axis.title.y = element_blank(),
panel.border = element_blank(),
panel.grid = element_blank(),
axis.ticks = element_blank(),
plot.title = element_text(size = 14, face = "bold")
)
ggplot(Liam_2013.df, aes(x = "", y = perc, fill = ethnicity))+
geom_bar(width = 1, stat = "identity") +
coord_polar("y", start = 0) +
scale_fill_brewer("Blues")+
blank_theme +
theme(axis.text.x=element_blank())+
geom_text(aes(x = 1.1, label = percent(perc)),
position = position_stack(vjust = 0.5),
size = 5) +
labs(title = "William in New York by Ethnicity",
x = "",
y = "Percentage of Total",
caption = "Source: Data from the New York Department of Health")

Created on 2020-03-15 by the reprex package (v0.3.0.9001)