R中导入数据调用split函数报‘对象未找到’，手动构框正常

我尝试了所有能想到的方法，但在对某列应用split函数时仍持续出现“对象未找到”错误，该问题仅在处理导入的数据文件时出现，在R Studio中手动构建的数据框上执行相同操作则完全正常。我尝试将目标列从字符型转换为数值型，且在排查过程中使用glimpse函数确认，导入数据与手动构建数据框的对应列数据类型有时是一致的。

可正常运行的测试代码 #

以下代码用于统计图书馆联盟中同一书名（图书）同时借出的最大副本数，可正常运行：

library(tidyverse)
options(scipen = 999)
options(digits = 22)

book_id <- c("A", "A", "A", "A", "A", "A", "A", "A", "A", "A", "B", "B", "B", "B", "B", "B")
start_date <- ymd(c("2017-10-28", "2017-11-17", "2018-01-16", "2018-03-10", 
            "2018-04-04", "2018-04-07", "2018-05-05", "2018-06-06", "2018-06-06", 
            "2018-06-28", "2017-11-03", "2017-11-14", "2019-04-01", "2021-05-11",
            "2022-01-09", "2022-07-11"))
end_date <- ymd(c("2017-11-17", "2018-06-06", "2018-01-30", "2018-04-25", "2018-04-10", 
          "2018-05-10", "2018-06-06", "2018-06-06", "2018-06-26", "2018-07-12", 
          "2017-12-06", "2017-12-18", "2019-04-12", "2023-01-05", "2022-12-12", 
          "2023-05-22"))
interval_date <- interval(start_date, end_date)
df_test <- data.frame(book_id, start_date, end_date, interval_date)


df_test_2 <- df_test %>%
  split(book_id) %>%
  map_dfr(\(x) mutate(x, max_overlap = max(map_int(seq(min(start_date), max(end_date), 1),
                                               \(d) sum(d %within% x$interval_date)))))

该数据框代表2个唯一书名（A和B）及其流通的起止日期。我也曾用“1”和“2”替换“A”和“B”进行测试，同样可以正常运行。

出错的导入数据处理代码 #

当我导入数据并运行以下代码时，在尝试对OCLC_Number列执行split操作时出现“对象未找到”错误，这是该列唯一出现错误的场景：

df <- read.delim("./Resource_Sharing_Lending_Sample.txt", header = T, na.strings = "", 
             quote = "", stringsAsFactors = F)

df2 <- df %>% 
  mutate(OCLC_Number = str_replace_all(OCLC_Number, regex(";.*"), "")) %>% 
  mutate(OCLC_Number = str_replace_all(OCLC_Number, regex(".*?([0-9]+).*"), "\\1")) %>%
  mutate(OCLC_Number = as.numeric(as.character(OCLC_Number))) %>% 
  mutate(Item_Sent_Date = str_replace_all(Item_Sent_Date, regex(" .*"), "")) %>%
  mutate(Item_Sent_Date = ymd(Item_Sent_Date)) %>%
  mutate(Item_Return_Date = str_replace_all(Item_Return_Date, regex(" .*"), "")) %>%
  mutate(Item_Return_Date = ymd(Item_Return_Date)) %>%
  mutate(Interval_Date = interval(Item_Sent_Date, Item_Return_Date)) %>% 
  arrange(OCLC_Number, Item_Sent_Date)

df2 %>% 
  split(OCLC_Number) %>%
  map_dfr(\(x) mutate(x, max_overlap = max(map_int(seq(min(Item_Sent_Date),
  max(Item_Return_Date), 1),
  \(d) sum(d %within% x$Interval_Date)))))

导入的制表符分隔数据 #

OCLC_Number Item_Sent_Date  Item_Return_Date
100000310   2022-11-03 21:43:09 2023-01-10 11:11:29
1000023983  2019-09-26 20:52:24 2019-11-12 10:12:30
1000023983  2021-12-09 20:38:17 2023-07-12 10:53:16
1000050643  2019-10-14 15:39:01 2020-01-03 10:01:34
1000050643  2020-08-20 16:13:00 2021-05-17 09:37:18
1000084050  2017-11-17 08:36:34 2018-06-06 15:22:18
1000084050  2018-01-16 08:23:16 2018-01-30 10:05:31
1000084050  2018-03-22 08:52:10 2018-04-05 09:56:06
1000084050  2018-05-03 21:44:42 2018-05-10 09:45:45
1000084050  2018-05-29 08:41:59 2018-06-06 13:55:03
1000084050  2018-06-06 14:16:40 2018-06-06 15:07:42
1000084050  2018-06-06 15:12:52 2018-06-26 11:15:41
1000084050  2018-06-28 08:18:35 2018-07-12 09:52:33
1000150454  2022-03-01 10:02:26 2022-04-21 10:46:02
1000150454  2022-05-15 20:32:10 2022-08-01 10:42:43

dput(df2)输出 #

structure(list(OCLC_Number = c(100000310, 1000023983, 1000023983, 
1000050643, 1000050643, 1000084050, 1000084050, 1000084050, 1000084050, 
1000084050, 1000084050, 1000084050, 1000084050, 1000150454, 1000150454
), Item_Sent_Date = structure(c(19299, 18165, 18970, 18183, 18494, 
17487, 17547, 17612, 17654, 17680, 17688, 17688, 17710, 19052, 
19127), class = "Date"), Item_Return_Date = structure(c(19367, 
18212, 19550, 18264, 18764, 17688, 17561, 17626, 17661, 17688, 
17688, 17708, 17724, 19103, 19205), class = "Date"), Interval_Date = new("Interval", 
    .Data = c(5875200, 4060800, 50112000, 6998400, 23328000, 
    17366400, 1209600, 1209600, 604800, 691200, 0, 1728000, 1209600, 
    4406400, 6739200), start = structure(c(1667433600, 1569456000, 
    1639008000, 1571011200, 1597881600, 1510876800, 1516060800, 
    1521676800, 1525305600, 1527552000, 1528243200, 1528243200, 
    1530144000, 1646092800, 1652572800), tzone = "UTC", class = c("POSIXct", 
    "POSIXt")), tzone = "UTC")), class = "data.frame", row.names = c(NA, 
-15L))

恳请各位提供帮助，另外这是我的第一篇帖子，若有需要改进之处也请告知。谢谢！

内容的提问来源于stack exchange，提问作者Joe_T