Question

我正在尝试将日期信息从.csv文件转换为R中的日期格式，以便创建两周的时间间隔来对数据进行分类。但是，当使用as.Date时，它仅在某些日期正常工作，其余日期为NA。我已经尝试在excel中编辑日期单元格的格式，我尝试从头开始重写excel中的每个日期单元格。我试过改变我的语言环境。我已经尝试了所有可以找到的在线解决方案。请帮忙！

    > lions <- read.csv("Lions_30m.csv")
    > dates<-as.character(lions$Date)
    > typeof(dates)
    [1] "character"
    > dates
     [1] "5/1/2017"  "5/9/2017"  "5/21/2017" "4/17/2017" "4/21/2017" "5/12/2017" 
    "3/27/2017" "3/13/2017"
     [9] "4/10/2017" "4/26/2017" "4/23/2017" "3/7/2017"  "5/28/2017" "4/27/2017" 
    "5/16/2017" "4/5/2017" 
    [17] "2/16/2017" "2/18/2017" "4/26/2017" "2/26/2017" "2/26/2017" "5/18/2017" 
    "3/4/2017"  "4/14/2017"
    [25] "3/3/2017"  "3/31/2017" "3/11/2017" "3/19/2017" "3/22/2017" "3/23/2017" 
    "3/25/2017" "4/13/2017"
    [33] "4/14/2017" "4/15/2017" "4/17/2017" "4/19/2017" "4/23/2017" "4/29/2017" 
    "5/15/2017" "3/26/2017"
    [41] "5/6/2017" 
    > date <-as.Date(dates, format='%d/%m/%Y')
    > date
    [1] "2017-01-05" "2017-09-05" NA           NA           NA           "2017-12-05" NA          
    [8] NA           "2017-10-04" NA           NA           "2017-07-03" NA           NA          
    [15] NA           "2017-05-04" NA           NA           NA           NA           NA          
    [22] NA           "2017-04-03" NA           "2017-03-03" NA           "2017-11-03" NA          
    [29] NA           NA           NA           NA           NA           NA           NA          
    [36] NA           NA           NA           NA           NA           "2017-06-05"

Answer 1

你想要%m/%d/%Y，而不是%d/%m/%Y，除非你住在一个每年有21个月的奇怪国家......

Answer 2

我们也可以使用anytime自动执行此操作，该library(anytime) anydate(c("4/26/2017", "2/26/2017", "2/26/2017" )) #[1] "2017-04-26" "2017-02-26" "2017-02-26"根据输入

选择格式

PreparedStatement pstmt=con.prepareStatement("select * from headwy where unmae=? " );

Answer 3

像这样

dates  <- c("5/1/2017", "5/9/2017", "5/21/2017", "4/17/2017", "4/21/2017", "5/12/2017",
           "3/27/2017", "3/13/2017", "4/10/2017", "4/26/2017", "4/23/2017", "3/7/2017",
           "5/28/2017", "4/27/2017", "5/16/2017", "4/5/2017", "2/16/2017", "2/18/2017",
           "4/26/2017", "2/26/2017", "2/26/2017", "5/18/2017", "3/4/2017", "4/14/2017",
           "3/3/2017", "3/31/2017", "3/11/2017", "3/19/2017", "3/22/2017", "3/23/2017",
           "3/25/2017", "4/13/2017", "4/14/2017", "4/15/2017", "4/17/2017", "4/19/2017",
           "4/23/2017", "4/29/2017", "5/15/2017", "3/26/2017", "5/6/2017")

使用class()查看它是什么，所以说话

class(dates)
#> [1] "character"

as_date_dates <- as.Date(dates, "%m/%d/%Y") 
class(as_date_dates)
#> [1] "Date"

或以lubridate方式避免%m/%d/%Y - %d/%m/%Y混淆。 Kinda same idea akrun is going with，

# install.packages(c("lubridate"), dependencies = TRUE) 
library(lubridate)
as_lubridate_dates <- mdy(dates)
class(as_lubridate_dates)
#> [1] "Date"

使用as.Date主要返回NAs，但是一些正确的日期

3 个答案: