我在excel文件中读取,其中1列包含不同格式的日期: excel格式(例如43596)和文本(例如"01.01.2020")。要转换excel格式,可以使用as.Date(as.numeric(df$date), origin = "1899-12-30")转换文本,可以将这些工作用于单个值,但当我尝试使用as.Date(df$date, format = "%d.%m.%Y")作为:
df$date <- ifelse(length(df$date)==5,
as.Date(as.numeric(df$date), origin = "1899-12-30"),
as.Date(df$date, format = "%d.%m.%Y"))或for循环:
for (i in length(x)) {
if(nchar(x[i])==5) {
y[i] <- as.Date(as.numeric(x[i]), origin = "1899-12-30")
} else {x[i] <- as.Date(x[i], , format = "%d.%m.%Y"))}
} print(x)它不起作用是因为:
“字符串不是标准的、明确的格式”
也许您可以建议一个更好的解决方案,以便在适当的日期格式中转换/替换不同的日期格式?
发布于 2022-01-28 16:35:13
您可以使用sapply对每个值应用ifelse:
df$date <- as.Date(sapply(df$date,function(date) ifelse(nchar(date)==5,
as.Date(as.numeric(date), origin = "1899-12-30"),
as.Date(date, format = "%d.%m.%Y"))),
origin="1970-01-01")
df
# A tibble: 6 x 2
contract date
<dbl> <date>
1 231429 2019-05-11
2 231437 2020-01-07
3 231449 2021-01-01
4 231459 2020-03-03
5 231463 2020-10-27
6 231466 2011-03-17发布于 2022-01-28 15:11:04
我有两个解决方案。
> df <- tibble(date = c("01.01.2020","43596"))
>
> df$date <- as.Date(ifelse(nchar(df$date)==5,
+ as.Date(as.numeric(df$date), origin = "1899-12-30"),
+ as.Date(df$date, format = "%d.%m.%Y")), origin = "1970-01-01")
Warning message:
In as.Date(as.numeric(df$date), origin = "1899-12-30") :
NAs introducidos por coerción
>
> df$date
[1] "2020-01-01" "2019-05-11"
>readr包中的read_csv()函数。这解决了一切!发布于 2022-01-28 17:56:34
一种使用tidyverse的rowwise解决方案
library(dplyr)
library(lubridate)
df %>%
rowwise() %>%
mutate(date_new=as.Date(ifelse(grepl("\\.",date),
as.character(dmy(date)),
as.character(as.Date(as.numeric(date), origin="1899-12-30"))))) %>%
ungroup()
# A tibble: 6 × 3
contract date date_new
<dbl> <chr> <date>
1 231429 43596 2019-05-11
2 231437 07.01.2020 2020-01-07
3 231449 01.01.2021 2021-01-01
4 231459 03.03.2020 2020-03-03
5 231463 44131 2020-10-27
6 231466 40619 2011-03-17https://stackoverflow.com/questions/70894554
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