如何基于频率表绘制男女任务时长散点图？解决ggplot报错

问题背景 #

我通过t1 <- table(PainF$task_duration)和t2 <- table(PainM$task_duration)生成了女性和男性的任务时长频率表，表格中上方数字为任务时长（分钟），下方为对应人数的频率。尝试用ggplot绘制散点图对比男女的任务时长与频率，运行以下代码时出现报错：

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()

报错信息 #

Error in fortify():
! data must be a <data.frame>, or an object coercible by fortify(), or a valid
<data.frame>-like object coercible by as.data.frame().
Caused by error in .prevalidate_data_frame_like_object():
! dim(data) must return an of length 2.
Run rlang::last_trace() to see where the error occurred.

附t1和t2的dput结果 #

> 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")

解答 #

能否基于频率表制作散点图？ #

可以。报错原因是ggplot不支持直接使用一维table对象作为数据源，需先将其转换为二维数据框，并修正任务时长的数值类型（原table行名为字符型）。

具体操作步骤 #

1. 转换table为数据框并处理数据
   将table转为数据框后，把任务时长列从字符型转为数值型，同时添加性别标识列，最后合并两个数据集便于统一绘图：

   # 处理女性数据
   df_female <- as.data.frame(t1)
   df_female$Var1 <- as.numeric(as.character(df_female$Var1))
   df_female$gender <- "Female"
   colnames(df_female) <- c("task_duration", "frequency", "gender")
   
   # 处理男性数据
   df_male <- as.data.frame(t2)
   df_male$Var1 <- as.numeric(as.character(df_male$Var1))
   df_male$gender <- "Male"
   colnames(df_male) <- c("task_duration", "frequency", "gender")
   
   # 合并数据集
   df_combined <- rbind(df_female, df_male)
   

2. 绘制散点图
   基于合并后的数据集，用ggplot按性别区分颜色绘制散点图：

   library(ggplot2)
   
   ggplot(df_combined, aes(x = task_duration, y = frequency, color = gender)) +
     geom_point(size = 3) +
     labs(x = "任务时长（分钟）", y = "人数频率", title = "男女任务时长-频率对比散点图") +
     scale_color_manual(values = c("Female" = "blue", "Male" = "red")) +
     theme_minimal()
   

关键说明 #

• 必须将任务时长列转为数值型，否则x轴会按字符排序（如"10"会排在"2"前面），导致图表逻辑错误。
• 合并数据集后用单一geom_point()配合color = gender映射，能更清晰地管理分组，自动生成图例。

内容的提问来源于stack exchange，提问作者Large Simpsons