Question

我的数据框中的一个列如下所示：

> head(df$col2,n = 50)
 [1] "NA, 2015"           "November 13, 2014"  "September 27, 2014" "October 8, 2014"    "December 16, 2013" 
 [6] "February 8, 2015"   "November 2, 2014"   "November 30, 2014"  "February 18, 2015"  "August 22, 2014"   
[11] "October 26, 2014"   "January 3, 2014"    "May 5, 2015"        "February 3, 2014"   "October 15, 2014"  
[16] "September 12, 2014" "April 2, 2014"      "April 23, 2015"     "November 4, 2014"   "January 16, 2014"  
[21] "September 28, 2014" "January 14, 2014"   "February 13, 2014"  "January 17, 2014"   "January 4, 2014"   
[26] "February 1, 2015"   "January 14, 2014"   "April 18, 2014"     "October 14, 2014"   "August 20, 2014"   
[31] "January 20, 2014"   "April 11, 2015"     "July 5, 2014"       "November 29, 2013"  "March 22, 2014"    
[36] "December 29, 2014"  "February 18, 2015"  "January 13, 2014"   "January 5, 2015"    "April 19, 2014"    
[41] "November 28, 2014"  "13 August, 2014"    "14 December, 2014"  "10 January, 2014"   "3 February, 2014"  
[46] "17 March, 2014"     "3 July, 2014"       "17 October, 2014"   "28 January, 2014"   "10 October, 2014"

正如您所看到的，除了第一行（我知道是NA，这没有问题）之外，m-d-y和d-m-y之间有两种不同的日期格式。有没有推荐的方法将所有日期标准化为m-d-y？

它们都在我的数据框列中列为字符格式。我试过了

> datestest <- as.Date(df$col2)，

但我得到

Error in charToDate(x) : character string is not in a standard unambiguous format

结果。

Answer 1

parse_date_time中的lubridate函数允许您使用“orders”参数解析具有异构格式的向量：

require(lubridate)
x <- c("November 2, 2014", "13 August, 2014")

parse_date_time(x, orders = c("mdy", "dmy"))
[1] "2014-11-02 UTC" "2014-08-13 UTC"

Answer 2

以下是lubridate的解决方案：

library(lubridate)
x <- c("November 2, 2014", "13 August, 2014" )

它包括用grep选择显示日期的不同方式（例如，首先是以数字开头的那些，然后使用-选择其他日期）然后使用不同的相应方式lubridate的功能。

 ind <- grep("^\\d", x)
 dmy(x[ind])
[1] "2014-08-13 UTC"

 mdy(x[-ind])
[1] "2014-11-02 UTC"

Answer 3

我似乎记得那里用lubridate更清晰地完成了这项工作，但我无法回想起它是什么。在过去，我已经用

之类的东西确定了日期格式

date_type <- ifelse(grepl(df$col2, "\\w{3,9} \\d{1,2}, \\d{4}"), "mdy",
                    ifelse(grepl(df$cols, "\\d{1,2} \\w{3,9}, \\d{4}"), "dmy",
                           NA))

从那里，您可以运行另一个ifelse来转换日期

date <- ifelse(date_type == "mdy", 
               as.Date(df$col2, format = "%B %d, %Y"),
               as.Date(df$col2, format = "%d %B, %Y"))

这可能会返回一个数字，但您可以使用as.Date(date, origin = "1970-01-01")

进行转换

修复数据框中的混合日期格式？

3 个答案: