使用dplyr/ ggplot创建频率表和图表直方图

Question

我是新的管道和dplyr在R和需要一些帮助。请注意-我有一个解决这个问题使用剪切功能。

在R中绘制分类值直方图

我想用dplyr解决这个问题。我希望使用dplyr来创建一个频率表(不想存储这个频率表)，并使用ggplot绘制数据。

问题:我有两个传感器的数据-参考数据和传感器数据(这是我正在评估的传感器)。传感器数据是分类数据(1或2或3)。我试图为不同的参考值绘制传感器状态直方图。例如:当参考值为1-5时，我希望看到传感器1状态(1、2或3)的频率分布。同样，对于6-10个参考数据和95-100个参考值，我想要传感器状态的频率分布。请参阅下面的样本数据。感谢你的帮助。

dput(sample1)
structure(list(test_data = c(1.2, 0.2, 0.6, 1.6, 1, 1, 0.4, 
0.4, 0.8, 0.8, 0.4, 0.2, 15.8, 59.2, 55.4, 54.8, 54.6, 54.2, 
49, 53, 47.2, 44, 40.2, 39, 34.2, 35.8, 33.4, 30.6, 29.4, 29.2, 
27.6, 24.8, 24, 22, 21.2, 20.6, 18.6, 18, 17, 17.2, 14.8, 15.2, 
13.2, 13.4, 12, 11.8, 11, 10.8, 10, 9.2, 8.8, 8.8, 8.4, 7.8, 
7.6, 6.6, 6.4, 6.2, 6, 5.8, 5.4, 5, 4.8, 4.4, 4.2, 4, 3.8, 3.6, 
3.6, 3.6, 3, 2.8, 3, 2.8, 2.6, 2.4, 2.4, 2.2, 2, 2.2, 2.2, 1.8, 
1.8, 1.6, 1.8, 1.8, 2.2, 71.2, 75.8, 74.6, 74.6, 74.2, 67.2, 
66.2, 60.6, 60.6, 54.8, 53.6, 48.4, 45.2), status = c(1, 
1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 3, 3, 3, 3, 3, 3, 3, 3, 
3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 
2, 2, 2, 2, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 
1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 
1, 1, 1, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3)), row.names = 113:212, class = "data.frame")

Answer 1

library(dplyr)
library(ggplot2)
dat %>%
  mutate(bin = cut(dusttrak_conc, breaks=seq(0,100,by=10))) %>%
  count(bin, sensor1_status) %>%
  ggplot(aes(bin, sensor1_status)) +
  geom_tile(aes(fill = n))

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Answer 2

这里没有必要使用dplyr：

library('ggplot2')

# create ggplot; specify data frame and x-axis variable
ggplot(sample1, aes(x = sensor1_status)) +
  
  # geom_bar() counts the number of cases at each x position
  geom_bar(stat = "count") +
  
  # facet_wrap() creates a square-ish grid of multiple panels
  # - facets defines the "grouping" per panel; cut creates the bins
  # - scales chooses to keep all x/y-axes the same or not
  # - drop chooses if empty groups should be dropped
  facet_wrap(facets = vars(reference_bin = cut(dusttrak_conc, seq(0,100,5), right = F, include.lowest = T)),
             scales = "free_y",
             drop = F) +
  
  # format y axis: desire ± 4 ticks; round() + unique() to prevent fractions on the ticks
  # I used (the new base R) piping because you were interested in it :)
  scale_y_continuous(breaks=\(x) pretty(x, n = 4) |> round() |> unique() )

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