频率散点图？

Question

我有一个女性和男性的频率表。

t1 <- table(PainF$task_duration)

t2 <- table(PainM$task_duration)

女性

30 40 45 60 65 70 75 78 80 90 95 100 101 120 144 150 180 185 240

3 3 2 5 1 2 1 1 1 5 1 1 1 3 1 1 1 1 2

男性：

2 10 15 20 30 38 40 45 50 55 60 70 72 73 75 80 90 95 100 105 110 120 130

2 2 1 2 3 1 4 4 3 2 11 1 1 1 1 2 10 1 1 1 1 11 2

150 180 200 240 300 500

2 5 1 3 3 1

这是表格，上面的数字是任务的持续时间（以分钟为单位），下面是人员的频率，我如何将这些数据放在散点图中，可能吗？我想比较女性和男性的数据（频率）和持续时间。

我尝试使用ggplot。

ggplot() +
  geom_point(data = t1, aes(x = x, y = "column2"), color = "blue", size = 3) +
  geom_point(data = t2, aes(x = x, y = "column2"), color = "red", size = 3) +
  labs(x = "X", y = "Y", title = "Female and Male task duration") +
  theme_minimal()

但我不断收到以下错误消息。

fortify()

中的错误： ！

data

必须是 ，或可被

fortify()

强制转换的对象，或有效的 类似 的对象可被

as.data.frame()

强制。 由

.prevalidate_data_frame_like_object()

中的错误引起： ！

dim(data)

必须返回长度为 2 的值。 运行

rlang::last_trace()

查看错误发生的位置。

所以我的问题是我可以根据频率表制作散点图吗？如果是的话我该怎么做？

> dput(t1)
structure(c(`30` = 3L, `40` = 3L, `45` = 2L, `60` = 5L, `65` = 1L, 
`70` = 2L, `75` = 1L, `78` = 1L, `80` = 1L, `90` = 5L, `95` = 1L, 
`100` = 1L, `101` = 1L, `120` = 3L, `144` = 1L, `150` = 1L, `180` = 1L, 
`185` = 1L, `240` = 2L), dim = 19L, dimnames = list(c("30", "40", 
"45", "60", "65", "70", "75", "78", "80", "90", "95", "100", 
"101", "120", "144", "150", "180", "185", "240")), class = "table")

> dput(t2)
structure(c(`2` = 2L, `10` = 2L, `15` = 1L, `20` = 2L, `30` = 3L, 
`38` = 1L, `40` = 4L, `45` = 4L, `50` = 3L, `55` = 2L, `60` = 11L, 
`70` = 1L, `72` = 1L, `73` = 1L, `75` = 1L, `80` = 2L, `90` = 10L, 
`95` = 1L, `100` = 1L, `105` = 1L, `110` = 1L, `120` = 11L, `130` = 2L, 
`150` = 2L, `180` = 5L, `200` = 1L, `240` = 3L, `300` = 3L, `500` = 1L
), dim = 29L, dimnames = structure(list(c("2", "10", "15", "20", 
"30", "38", "40", "45", "50", "55", "60", "70", "72", "73", "75", 
"80", "90", "95", "100", "105", "110", "120", "130", "150", "180", 
"200", "240", "300", "500")), names = ""), class = "table")

Answer 1

使用

dplyr

创建汇总数据可能会更容易。

但是，从您拥有的表格开始，我建议将它们组合成这样的数据框：

library(dplyr)
library(ggplot2)

counts <- rbind(
  data.frame(t1) %>% mutate(gender = "F"),
  data.frame(t2) %>% mutate(gender = "M")
) %>%
  rename(
    duration = Var1,
    frequency = Freq
  ) %>%
  mutate(
    duration = as.integer(duration)
  )

结果数据的顶部如下所示：

  duration frequency gender
1        1         3      F
2        2         3      F
3        3         2      F
4        4         5      F
5        5         1      F
6        6         2      F

现在绘制。在这里使用单个数据框使事情变得更加简单。

ggplot(counts) +
  geom_point(aes(x = duration, y = frequency, col = gender)) +
  labs(x = "X", y = "Y", title = "Female and Male task duration") +
  theme_minimal() +
  scale_colour_manual(values = c("blue", "red"))