无法使用带有NA值的ggplot进行可视化

Question

我正在尝试创建一个堆积条形图，显示按组发生的频率百分比

library(dplyr)
library(ggplot2)

brfss_2013 %>%
  group_by(incomeLev, mentalHealth) %>%
  summarise(count_mentalHealth=n()) %>%
  group_by(incomeLev) %>%
  mutate(count_inc=sum(count_mentalHealth)) %>%
  mutate(percent=count_mentalHealth / count_inc * 100) %>%
  ungroup() %>%
  ggplot(aes(x=forcats::fct_explicit_na(incomeLev),
             y=count_mentalHealth,
             group=mentalHealth)) +
  geom_bar(aes(fill=mentalHealth), 
           stat="identity") +
  geom_text(aes(label=sprintf("%0.1f%%", percent)),
            position=position_stack(vjust=0.5))

但是，这是我收到的追溯：

1. dplyr::group_by(., incomeLev, mentalHealth)
8. plyr::summarise(., count_mentalHealth = n())
9. [ base::eval(...) ] with 1 more call
11. dplyr::n()
12. dplyr:::from_context("..group_size")
13. `%||%`(...)
In addition: Warning message:
  Factor `incomeLev` contains implicit NA, consider using `forcats::fct_explicit_na` 
> 

这是我的数据样本

brfss_2013 <- structure(list(incomeLev = structure(c(2L, 3L, 3L, 2L, 2L, 3L, 
NA, 2L, 3L, 1L, 3L, NA), .Label = c("$25,000-$35,000", "$50,000-$75,000", 
"Over $75,000"), class = "factor"), mentalHealth = structure(c(3L, 
1L, 1L, 1L, 1L, 1L, 2L, 1L, 1L, 1L, 1L, 1L), .Label = c("Excellent", 
"Ok", "Very Bad"), class = "factor")), row.names = c(NA, -12L
), class = "data.frame")

更新：

str的输出（brfss_2013）：

'data.frame':   491775 obs. of  9 variables:
 $ mentalHealth: Factor w/ 5 levels "Excellent","Good",..: 5 1 1 1 1 1 3 1 1 1 ...
 $ pa1min_     : int  947 110 316 35 429 120 280 30 240 260 ...
 $ bmiLev      : Factor w/ 6 levels "Underweight",..: 5 1 3 2 5 5 2 3 4 3 ...
 $ X_drnkmo4   : int  2 0 80 16 20 0 1 2 4 0 ...
 $ X_frutsum   : num  413 20 46 49 7 157 150 67 100 58 ...
 $ X_vegesum   : num  53 148 191 136 243 143 216 360 172 114 ...
 $ sex         : Factor w/ 2 levels "Male","Female": 2 2 2 2 1 2 2 2 1 2 ...
 $ X_state     : Factor w/ 55 levels "0","Alabama",..: 2 2 2 2 2 2 2 2 2 2 ...
 $ incomeLev   : Factor w/ 4 levels "$25,000-$35,000",..: 2 4 4 2 2 4 NA 2 4 1 ...

Answer 1

首先，当您将所有内容转换为字符时，您的代码工作得非常好。所以你可以做到

brfss_2013[c("incomeLev", "mentalHealth")] <- 
  lapply(brfss_2013[c("incomeLev", "mentalHealth")], as.character)

然后在你弄清楚的时候运行你的代码。

但是，让我们用因子来做（在这种情况下不要运行lapply(.)线！）。

你想要一个"missing"类别，你可以通过为"missing"s添加一个新的级别NA来获得。

levels(brfss_2013$incomeLev) <- c(levels(brfss_2013$incomeLev), "missing")
brfss_2013$incomeLev[is.na(brfss_2013$incomeLev)] <- "missing"

然后，你的聚合（以基础R方式）。

b1 <- with(brfss_2013, aggregate(list(count_mentalHealth=incomeLev), 
                        by=list(mentalHealth=mentalHealth, incomeLev=incomeLev), 
                        length))
b2 <- aggregate(mentalHealth ~ ., brfss_2013, length)
names(b2)[2] <- "count_inc"   
brfss_2013.agg <- merge(b1, b2)
rm(b1, b2)  # just to clean up

添加"percent"列。

brfss_2013.agg$percent <- with(brfss_2013.agg, count_mentalHealth / count_inc)

情节。

library(ggplot2)
ggplot(brfss_2013.agg, aes(x=incomeLev, y=count_mentalHealth, group=mentalHealth)) +
  geom_bar(aes(fill=mentalHealth), stat="identity") +
  geom_text(aes(label=sprintf("%0.1f%%", percent)), 
            position=position_stack(vjust=0.5))

结果

Answer 2

所以你的代码实际上对我来说很好。看起来它可能是包版本的问题，因为你使用plyr summarise函数似乎很奇怪。

但是，这里有一个更简洁的方法来创建该图形（希望这对你想要添加到这个图中的任何内容都有帮助）

brfss_2013 %>%
  # Add count of income levels first (note this only adds a variable)
  add_count(incomeLev) %>%
  rename(count_inc = n) %>% 
  # Count observations per group (this transforms data)
  count(incomeLev, mentalHealth, count_inc) %>%
  rename(count_mentalHealth = n) %>% 
  mutate(percent= count_mentalHealth / count_inc) %>%
  ggplot(aes(x= incomeLev,
             y= count_mentalHealth,
             # Technically you don't need this group here but groups can be handy
             group= mentalHealth)) + 
  geom_bar(aes(fill=mentalHealth), 
           stat="identity")+ 
  # Using the scales package does the percent formatting for you
  geom_text(aes(label = scales::percent(percent)), vjust = 1)+
  theme_minimal()