R语言Swimmer Plot报错：参数暗示行数不一致问题求助

报错根源分析 #

报错Error in data.frame(id_fix, start_blank, end_blank): arguments imply differing number of rows: 1, 0的核心原因有两个：

• 日期格式转换错误：原始数据中ther_start_date和ther_end_date已经是Date类型，但后续代码错误地用%m/%d/%y格式重新转换，导致日期变为NA，进而使ther_start和ther_end计算结果异常。
• 部分治疗区间长度为0：部分记录的ther_start_date与ther_end_date完全相同（如study_id=7的最后一条A治疗、study_id=8的第一条A治疗），计算后ther_start等于ther_end，函数处理空白间隔时出现行不匹配。

修复后的完整代码 #

library(swimplot)
library(ggplot2)
library(dplyr)

# 示例数据
study_7 <- data.frame(
  study_id = c(7, 7, 7, 7, 7, 7, 7, 7, 8, 8, 8, 8),
  ther_type = c("S", "S", "S", "S", 
                "E", "E", "E", 
                "A", "A", "A", 
                "A", "A"),
  ther_start_date = as.Date(c("2016-02-01", "2016-02-18", "2016-02-20", 
                               "2016-02-26", "2021-03-26", "2021-10-15", 
                               "2021-11-04", "2023-08-08", "2023-09-28", 
                               "2023-10-01", "2023-12-21", "2024-03-28")),
  ther_end_date = as.Date(c("2016-02-18", "2016-02-20", "2016-02-22", 
                             "2016-03-17", "2021-09-01", "2021-11-04", 
                             "2022-07-01", "2023-09-28", "2023-10-01", 
                             "2023-12-21", "2024-03-28", "2024-09-01"))
)

# 为每个study_id计算最早治疗起始日期
study_7 <- study_7 %>%
  group_by(study_id) %>%
  mutate(date_start_ther = min(ther_start_date, na.rm=TRUE)) %>%
  ungroup()

# 计算相对起始日期的年数差异（移除错误的日期格式转换步骤）
study_7 <- study_7 %>%
  mutate(
    ther_start = as.numeric(difftime(ther_start_date, date_start_ther, units = "days")) / 365.25,
    ther_end = as.numeric(difftime(ther_end_date, date_start_ther, units = "days")) / 365.25
  ) %>%
  # 过滤掉长度为0的无效治疗区间
  filter(ther_end > ther_start)

# 绘制Swimmer Plot
study_plot <- swimmer_plot(
  df = study_7,
  id = 'study_id',
  start = "ther_start",
  end = "ther_end",
  name_fill = "ther_type",
  width = 0.85,
  color = NA,
  id_order = sort(unique(study_7$study_id), decreasing = TRUE)
) + theme_bw(base_size = 20) +
  theme(panel.grid.major = element_blank(),
        panel.grid.minor = element_blank(),
        panel.border = element_blank(),
        axis.line = element_line(colour = "black")) +
  coord_flip(clip = 'off', expand = FALSE) +
  scale_x_continuous(expand = c(0, 0)) +
  scale_y_continuous(expand = c(0, 0))

# 查看绘图
print(study_plot)

关键修复点说明 #

• 删除错误的日期转换：原始数据创建时已经用as.Date()生成了正确的日期格式，无需再次用错误的%m/%d/%y格式转换，避免生成NA值。
• 过滤无效区间：通过filter(ther_end > ther_start)移除长度为0的治疗区间；如果需要保留这类记录，也可以用ther_end = ther_end + 0.001给区间加一个极小的长度，避免报错。
• 简化数据类型转换：无需将study_7强制转为data.frame，dplyr处理后的tibble可直接被swimmer_plot识别。

内容的提问来源于stack exchange，提问作者Alex