Несколько Boxplots в R - 3 переменных

Question

Я пытаюсь создать график, используя r, на котором есть несколько прямоугольников на одном графике. Однако когда я запускаю этот блок кода, я получаю только один боксплот, а не другой 11. Я пробовал ggplot и продолжаю получать ошибки, а также принимаю только два «ответа». Ниже приведен код, с которым я работаю:

Are people with dependents judged more reckless than people without dependents, even when they do the same activity?


# #Dependents vs no dependents in the sport and their associated risk - climbing
# #------------------------------------------------------------------
ans1F <-sportrisks %>%
  filter(sport=="climbing")%>%
  filter(dependents=="TRUE")%>%
  select("dependents","recklessness")
ans1F

ans1M <-sportrisks %>%
  filter(sport=="climbing")%>%
  filter(dependents=="FALSE")%>%
  select("recklessness","dependents")
ans1M



#dependents vs no dependents in the sport and their associated risk - golf
#--------------------------------------------------------------
ans2F <-sportrisks %>%
  filter(sport=="golf")%>%
  filter(dependents=="TRUE")%>%
  select("recklessness","dependents")
ans2F



ans2M <-sportrisks %>%
  filter(sport=="golf")%>%
  filter(dependents=="FALSE")%>%
  select("recklessness","dependents")
ans2M



#Dependents vs no dependents in the sport and their associated risk - running
#-----------------------------------------------------------------
ans3F <-sportrisks %>%
  filter(sport=="running")%>%
  filter(dependents=="TRUE")%>%
  select("recklessness","dependents")
ans3F

ans3M <-sportrisks %>%
  filter(sport=="running")%>%
  filter(dependents=="FALSE")%>%
  select("recklessness","dependents")
ans3M




#dependents vs no dependents in the sport and their associated risk - skitouring
#--------------------------------------------------------------------
ans4F <-sportrisks %>%
  filter(sport=="skitouring")%>%
  filter(dependents=="TRUE")%>%
  select("recklessness","dependents")
ans4F

ans4M <-sportrisks %>%
  filter(sport=="skitouring")%>%
  filter(dependents=="FALSE")%>%
  select("recklessness","dependents")
ans4M



#Dependents vs no depenents in the sport and their associated risk - surfing
#-----------------------------------------------------------------
ans5F <-sportrisks %>%
  filter(sport=="surfing")%>%
  filter(dependents=="TRUE")%>%
  select("recklessness","dependents")
ans5F

ans5M <-sportrisks %>%
  filter(sport=="surfing")%>%
  filter(dependents=="FALSE")%>%
  select("recklessness","dependents")
ans5M



# #dependents vs no dependents in the sport and their associated risk - hillwalking
# #---------------------------------------------------------------------
ans6F <-sportrisks %>%
  filter(sport=="hillwalking")%>%
  filter(dependents=="TRUE")%>%
  select("recklessness","dependents")
ans6F

ans6M <-sportrisks %>%
  filter(sport=="hillwalking")%>%
  filter(dependents=="FALSE")%>%
  select("recklessness","extreme_risk")

ans6M


boxplot(c(ans1F$recklessness,ans1M$recklessness, ans2F$recklessness, ans2M$recklessness,ans3M$recklessness,ans3F$recklessness,ans4F$recklessness, ans4M$recklessness, ans5F$recklessness, ans5M$recklessness,ans6M$recklessness,ans6F$recklessness),
     main = "Multiple boxplots for comparision",
     las = 2,
     col = c("pink","blue"),
     border = "brown",
     horizontal = FALSE,
     ylim = c(0,100)
)

Вот структура данных:

Classes ‘tbl_df’, ‘tbl’ and 'data.frame':   2060 obs. of  27 variables:
 $ Q1               : num  1 1 1 1 1 1 1 1 1 1 ...
 $ Q3               : num  1 1 3 1 1 2 1 2 1 2 ...
 $ Q4               : num  4 2 1 2 2 1 2 2 4 2 ...
 $ Q5               : num  NA NA NA NA NA NA NA NA NA NA ...
 $ Dangerous        : num  3 4 2 6 5 2 3 5 3 3 ...
 $ Q5_a             : num  NA NA NA NA NA NA NA NA NA NA ...
 $ Judgement        : num  3 4 5 3 3 5 4 4 3 3 ...
 $ Q6               : num  NA NA NA NA NA NA NA NA NA NA ...
 $ recklessness     : num  1 3 2 8 9 1 2 3 3 4 ...
 $ Q6_a             : num  NA NA NA NA NA NA NA NA NA NA ...
 $ Q6_a_1           : num  4 4 4 4 5 5 4 4 3 3 ...
 $ Q7               : num  2 1 2 2 1 2 1 1 1 1 ...
 $ Insurance_premium: num  NA 25 NA NA 150 NA 100 200 100 150 ...
 $ Q8_1             : num  0 0 0 0 0 1 1 1 1 0 ...
 $ Q8_2             : num  0 0 0 0 0 1 0 0 0 0 ...
 $ Q8_3             : num  0 0 0 0 0 0 0 0 0 0 ...
 $ Q8_4             : num  0 0 0 0 0 1 0 0 0 0 ...
 $ Q8_5             : num  0 0 0 0 0 0 0 0 0 0 ...
 $ Q8_6             : num  1 1 1 1 1 0 0 0 0 1 ...
 $ Q8_7             : num  0 0 0 0 0 0 0 0 0 0 ...
 $ sport            : chr  "climbing" "climbing" "climbing" "climbing" ...
 $ gender           : chr  "male" "male" "male" "male" ...
 $ dependents       : logi  FALSE FALSE FALSE FALSE FALSE FALSE ...
 $ charity          : logi  FALSE FALSE FALSE FALSE FALSE FALSE ...
 $ low_competence   : logi  FALSE FALSE FALSE FALSE FALSE FALSE ...
 $ guide            : logi  FALSE FALSE FALSE FALSE FALSE FALSE ...
 $ extreme_risk     : logi  FALSE FALSE FALSE FALSE FALSE FALSE ...