使用 date_parser 格式化日期

Question

我正在使用 R 从多个 pdf 文件中提取数据。提取这些数据后，我需要格式化日期类型的字段。日期来自各种格式的 pdf 文件

data = c( "1/10/2022 2:36:00 pm",
  "1/11/2022 12:47:00 pm",
  "1/12/2022 9:47:00 am",
  "1/13/2022 9:21:00 am",
  "1/14/2022 12:59:00 pm",
  "1/10/2022 2:39:00 pm",
  "1/11/2022 12:46:00 pm",
  "1/12/2022 9:48:00 am",
  "1/13/2022 9:22:00 am",
  "1/14/2022 1:00:00 pm",
  "1/10/2022 2:40:00 pm",
  "1/11/2022 12:45:00 pm",
  "1/12/2022 9:49:00 am",
  "1/13/2022 9:23:00 am",
  "1/14/2022 1:01:00 pm",
  "1/10/2022 2:42:00 pm",
  "1/11/2022 12:44:00 pm",
  "1/12/2022 9:50:00 am",
  "1/13/2022 9:24:00 am",
  "1/14/2022 1:02:00 pm",
  "1/10/2022 2:44:00 pm",
  "1/11/2022 12:43:00 pm",
  "1/12/2022 9:51:00 am",
  "1/13/2022 9:25:00 am",
  "1/14/2022 1:03:00 pm",
  "10/01/2022 14:36:00",
  "11/01/2022 12:47:00",
  "12/01/2022 09:47:00",
  "13/01/2022 09:21:00",
  "14/01/2022 12:59:00",
  "10/01/2022 14:39:00",
  "11/01/2022 12:46:00",
  "12/01/2022 09:48:00",
  "13/01/2022 09:22:00",
  "14/01/2022 13:00:00",
  "10/01/2022 14:40:00",
  "11/01/2022 12:45:00",
  "12/01/2022 09:49:00",
  "13/01/2022 09:23:00",
  "14/01/2022 13:01:00",
  "10/01/2022 14:42:00")
df <- data.frame(data)

我尝试如下

date_parser <- function(d) {
  if (endsWith(d, "m")) {
    as.POSIXct(d, format = "%m/%d/%Y %I:%M %p")
  } else {
    as.POSIXct(d, format = "%d/%m/%Y %H:%M")
  }
}

df = df%>%
  rowwise %>%
  mutate(data = date_parser(data)) 

我收到此错误消息

mutate 中的错误：参数中：data_hora_leitura_coc08 = date_parser(data_hora_leitura_coc08)。在第 1732 行中。由 `if (endsWith(d, "m")) 中的错误导致，其中需要 TRUE/FALSE

另外，有些日期显示为“NA”，如何解决？

Answer 1

您的示例数据有几秒钟，因此您需要为每种格式添加

%S

。

date_parser <- function(d) {
  if (endsWith(d, "m")) {
    as.POSIXct(d, format = "%m/%d/%Y %I:%M:%S %p")
  } else {
    as.POSIXct(d, format = "%d/%m/%Y %H:%M:%S")
  }
}

df %>%
  rowwise() %>%
  mutate(data = date_parser(data))
# # A tibble: 41 × 1
# # Rowwise: 
#    data               
#    <dttm>             
#  1 2022-01-10 14:36:00
#  2 2022-01-11 12:47:00
#  3 2022-01-12 09:47:00
#  4 2022-01-13 09:21:00
#  5 2022-01-14 12:59:00
#  6 2022-01-10 14:39:00
#  7 2022-01-11 12:46:00
#  8 2022-01-12 09:48:00
#  9 2022-01-13 09:22:00
# 10 2022-01-14 13:00:00
# # ℹ 31 more rows
# # ℹ Use `print(n = ...)` to see more rows

Answer 2

lubridate

正是您想要的。尝试一下

df %>% 
   mutate(parsed_data = if_else(endsWith(data, "m"), mdy_hms(data), dmy_hms(data)))

Answer 3

与

parse_date_time

library(lubridate)

df %>% mutate(new = parse_date_time(data, orders=c("mdY IMS p", "dmY HMS")))