我正在尝试在ggplot上绘制一个显示比例的条形图。我用以下方式调用情节:
v2 <- ggplot(data = Visual2_Data,
mapping = aes(x = violation, y = ..prop.., group = 1, fill = violation)) +
geom_bar() +
facet_grid(~driver_race) +
scale_fill_manual(values = c("red", "green", "yellow", "blue", "pink", "purple"))+
theme(axis.text.x = element_text(angle=90))
我的结果如下:
尽管使用了fill
和scale_fill_manual
,但这些条仍然是默认颜色。
只要我使用..count..
作为y变量而不是..prop..
并删除group = 1
:
v2 <- ggplot(data = Visual2_Data,
mapping = aes(x = violation, y = ..count.., fill = violation)) +
geom_bar() +
facet_grid(~driver_race) +
scale_fill_manual(values = c("red", "green", "yellow", "blue", "pink", "purple"))+
theme(axis.text.x = element_text(angle=90))
我得到以下内容:
这就是我想要的,除了我想在第一个图中使用y = ..prop..
和group = 1
而不是y = ..counts..
使用这些颜色。
有没有办法做到这一点?
提前致谢
重现性:
我必须注意到它是一个相对较大的数据集。
我使用来自此来源的科罗拉多州数据:
https://openpolicing.stanford.edu/data/
我整理了一下:
data <- read_csv() #insert data here
Visual2_Data <- data %>%
subset(out_of_state == FALSE) %>%
select(county_name, county_fips, police_department, driver_gender,
driver_age, driver_race, violation, search_conducted,
contraband_found, stop_outcome, is_arrested) %>%
drop_na(county_name) %>%
filter(driver_race != "Other",
violation %in% c("Lights", "Speeding", "Safe movement", "License",
"Seat belt", "Registration/plates"))
# After this I used the code for v2 which already is described above.
v2 <- ggplot(data = Visual2_Data, etcetera)
答案 0 :(得分:1)
如果您将fill = ...
替换为fill = factor(..x..)
,则会获得所需的结果:
ggplot(diamonds, aes(x = color, y = ..prop.., fill = factor(..x..), group = 1)) +
geom_bar() +
facet_grid(~cut)+
scale_fill_manual(values = c("red", "green", "yellow", "blue", "pink", "purple", "black")) +
theme(axis.text.x = element_text(angle=90))
或者,我总是喜欢事先进行预处理。你可以这样做:
library(data.table)
df <- setDT(copy(diamonds))[, .(N = .N), by = .(cut, color)][, .(prop = N/sum(N), color = color), by = cut]
ggplot(data = df,
mapping = aes(x = color, y = prop, fill = color)) +
geom_col() +
facet_grid(~cut) +
scale_fill_manual(values = c("red", "green", "yellow", "blue", "pink", "purple", "black"))+
theme(axis.text.x = element_text(angle=90))