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r - 按另一个因子中的类别计算因子变量中每个类别的比率

问题描述

这里有两列，都是因子变量。第一个是囚犯的种族，第二个是他们是否再犯。我想按种族绘制累犯率。我应该如何实现这一目标？

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()

结果是计算每场比赛数量的直方图。我怎样才能得到一个按种族可视化累犯率的图？谢谢！！！

以下是部分数据！

    > 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

标签： rggplot2group-by

解决方案

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，对于逻辑，mean() 是 TRUE 的比例。

希望这可以帮助 ：）

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