【发布时间】:2021-02-23 19:32:44
【问题描述】:
【问题讨论】:
-
试试
df$Date <- as.Date(df$Date, "X%Y.%m.%d")(记得用df替换你的数据框)
标签: r date format data-cleaning
【问题讨论】:
df$Date <- as.Date(df$Date, "X%Y.%m.%d")(记得用df替换你的数据框)
标签: r date format data-cleaning
这里有一些关于如何提供正确的reproducible example 的信息。
这是使用dplyr 和lubridate 包的解决方案。
数据:
df <- tibble::tibble(
Country = c("Afghanistan",
"Algeria",
"Andorra",
"Angola",
"Antigua and Barbuda",
"Argentina",
"Armenia",
"Australia",
"Austria",
"Azerbaijan"),
Date = c("X2020.01.22",
"X2020.01.22",
"X2020.01.22",
"X2020.01.22",
"X2020.01.22",
"X2020.01.22",
"X2020.01.22",
"X2020.01.22",
"X2020.01.22",
"X2020.01.22"),
Recovered = c(0,
0,
0,
0,
0,
0,
0,
0,
0,
0)
)
代码:
library(lubridate)
library(dplyr)
df %>%
mutate(
Date = as_date(Date, format = "X%Y.%m.%d")
)
输出:
#> # A tibble: 10 x 3
#> Country Date Recovered
#> <chr> <date> <dbl>
#> 1 Afghanistan 2020-01-22 0
#> 2 Algeria 2020-01-22 0
#> 3 Andorra 2020-01-22 0
#> 4 Angola 2020-01-22 0
#> 5 Antigua and Barbuda 2020-01-22 0
#> 6 Argentina 2020-01-22 0
#> 7 Armenia 2020-01-22 0
#> 8 Australia 2020-01-22 0
#> 9 Austria 2020-01-22 0
#> 10 Azerbaijan 2020-01-22 0
由reprex package (v0.3.0) 于 2020 年 11 月 11 日创建
【讨论】: