r-计算一个因子变量中每个类别的比率，按另一个因子中的类别计算

Question

这里有两列，它们都是因子变量。第一个问题是囚犯的种族，第二个问题是他们是否复习。我想画出按种族划分的累犯率。我应该如何做到这一点？

我试过这个：

df %>%
group_by(race, Recidivated) %>%
summarize(count = n()) %>%
arrange (-count) %>%
ggplot(aes(reorder(race, count, FUN = max),
count, fill = race)) + 
geom_col() +
coord_flip() +
scale_fill_manual(values=palette_9_colors) +
theme(legend.position = "none") +
labs(x = "Charge", y = "Count",
title="Recidivism by Rates",
subtitle= "Broward County - Source: Propublica",
caption="UrbanSpatialAnalysis.com") +
plotTheme()   

结果是一个计算每个种族数量的直方图。如何获得按种族划分的累犯率可视化图？非常感谢。

以下是一些数据！

> head(df)
sex age         age_cat             race priors_count two_year_recid
1 Male  69 Greater than 45            Other            0              0
2 Male  34         25 - 45 African-American            0              1
3 Male  24    Less than 25 African-American            4              1
4 Male  44         25 - 45            Other            0              0
5 Male  41         25 - 45        Caucasian           14              1
6 Male  43         25 - 45            Other            3              0
r_charge_desc                  c_charge_desc
1                                  Aggravated Assault w/Firearm
2    Felony Battery (Dom Strang) Felony Battery w/Prior Convict
3    Driving Under The Influence          Possession of Cocaine
4                                                       Battery
5 Poss of Firearm by Convic Felo      Possession Burglary Tools
6                                         arrest case no charge
c_charge_degree r_charge_degree juv_other_count length_of_stay
1               F                               0              1
2               F            (F3)               0             10
3               F            (M1)               1              1
4               M                               0              1
5               F            (F2)               0              6
6               F                               0              1
Recidivated
1 notRecidivate
2    Recidivate
3    Recidivate
4 notRecidivate
5    Recidivate
6 notRecidivate

Answer 1

race <- sample(c("A", "B", "C", "D"), size = 100, replace = T)
recidivated <- sample(c(TRUE, FALSE), size = 100, replace = T)
df <- data.frame(race, recidivated)
df %>% group_by(race) %>% summarize(recidRate = mean(recidivated)) %>% ggplot(aes(race, recidRate)) + geom_bar(stat = "identity")

如果Recidivated是逻辑变量，则应使用TRUE或FALSE；对于logicals，mean((是TRUE的比例。

希望这有帮助：(