如何将我的日期变量分组到R中的月/年？

Question

我有一个"日期"向量,其中包含以mm/dd/yyyy格式表示的日期:

 head(Entered_Date,5)
[1] 1/5/1998 1/5/1998 1/5/1998 1/5/1998 1/5/1998

我试图根据日期绘制频率变量,但我想按月或年分组日期.就像现在一样,每天有一个频率,但我想按月或年绘制频率.因此,对于1/5/1998,1为1/7/1998和3为1/8/1998,频率为1,我想将其显示为1为1/1998.这是一个相对较大的数据集,从1998年到现在的日期,我想找到一些自动化的方法来实现这一目标.

> dput(head(Entered_Date))
structure(c(260L, 260L, 260L, 260L, 260L, 260L), .Label = c("1/1/1998", 
"1/1/1999", "1/1/2001", "1/1/2002", "1/10/2000", "1/10/2001", 
"1/10/2002", "1/10/2003", "1/10/2005", "1/10/2006", "1/10/2007", 
"1/10/2008", "1/10/2011", "1/10/2012", "1/10/2013", "1/11/1999", 
"1/11/2000", "1/11/2001", "1/11/2002", "1/11/2005", "1/11/2006", 
"1/11/2008", "1/11/2010", "1/11/2011", "1/11/2012", "1/11/2013", 
"1/12/1998", "1/12/1999", "1/12/2001", "1/12/2004", "1/12/2005", ...

Answer 1

这是一个使用的例子dplyr.您只需在语句中使用月份%m或年份的相应日期格式字符串.%Yformat

set.seed(123)
df <- data.frame(date = seq.Date(from =as.Date("01/01/1998", "%d/%m/%Y"), 
                                 to=as.Date("01/01/2000", "%d/%m/%Y"), by="day"),
                 value = sample(seq(5), 731, replace = TRUE))

head(df)
        date value
1 1998-01-01     2
2 1998-01-02     4
3 1998-01-03     3
4 1998-01-04     5
5 1998-01-05     5
6 1998-01-06     1

library(dplyr)

df %>%
mutate(month = format(date, "%m"), year = format(date, "%Y")) %>%
group_by(month, year) %>%
summarise(total = sum(value))

Source: local data frame [25 x 3]
Groups: month [?]

   month  year total
   (chr) (chr) (int)
1     01  1998   105
2     01  1999    91
3     01  2000     3
4     02  1998    74
5     02  1999    77
6     03  1998    96
7     03  1999    86
8     04  1998    91
9     04  1999    95
10    05  1998    93
..   ...   ...   ...

Answer 2

lubridate的floor_date很好地做到了这一点。

data %>% 
    group_by(month=floor_date(date, "month")) %>%
    summarize(summary_variable=sum(value))

感谢Roman Cheplyaka

https://ro-che.info/articles/2017-02-22-group_by_month_r

Answer 3

只需添加到 @cdeterman 答案，您可以使用lubridatewith 来dplyr使这变得更加容易：

df <- data.frame(date = seq.Date(from =as.Date("01/01/1998", "%d/%m/%Y"), 
                                 to=as.Date("01/01/2000", "%d/%m/%Y"), by="day"),
                 value = sample(seq(5), 731, replace = TRUE))

library(dplyr)
library(lubridate)

df %>%
mutate(month = month(date), year = year(date)) %>%
group_by(month, year) %>%
summarise(total = sum(value))