How do I group my date variable into month/year in

Question

I have a "date" vector, that contains dates in mm/dd/yyyy format:

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

I am trying to plot a frequency variable against the date, but I want to group the dates that it is by month or year. As it is now, there is a frequency per day, but I want to plot the frequency by month or year. So instead of having a frequency of 1 for 1/5/1998, 1 for 1/7/1998, and 3 for 1/8/1998, I would like to display it as 5 for 1/1998. It is a relatively large data set, with dates from 1998 to present, and I would like to find some automated way to accomplish this.

> 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

Maybe you just add a column in your data like this:

Year <- format(as.Date(Entered_Date, "%d/%m/%Y"), "%Y")

Answer 2

The floor_date from lubridate does this nicely.

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

Thanks to Roman Cheplyaka

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

Answer 3

There is a super easy way using the cut() function:

    list = as.Date(c("1998-5-2", "1993-4-16", "1998-5-10"))
    cut(list, breaks = "month")

and you will get this:

    [1] 1998-05-01 1993-04-01 1998-05-01
    62 Levels: 1993-04-01 1993-05-01 1993-06-01 1993-07-01 1993-08-01 ... 1998-05-01

Answer 4

Here is an example using dplyr. You simply use the corresponding date format string for month %m or year %Y in the format statement.

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 5

Dont need dplyr. Look at ?as.POSIXlt

df$date<-as.POSIXlt(df$date)
mon<-df$date$mon
yr<-df$date$year
monyr<-as.factor(paste(mon,yr,sep="/"))
df$date<-monyr

Don't need to use ggplot2 but its nice for this kind of thing.

c <- ggplot(df, aes(factor(date)))
c + geom_bar()

If you want to see the actual numbers

aggregate(. ~ date,data = df,FUN=length )
df2<-aggregate(. ~ date,data = df,FUN=length )
df2
    date value
1   0/98    31
2   0/99    31
3   1/98    28
4   1/99    28
5  10/98    30
6  10/99    30
7  11/97     1
8  11/98    31
9  11/99    31
10  2/98    31
11  2/99    31
12  3/98    30
13  3/99    30
14  4/98    31
15  4/99    31
16  5/98    30
17  5/99    30
18  6/98    31
19  6/99    31
20  7/98    31
21  7/99    31
22  8/98    30
23  8/99    30
24  9/98    31
25  9/99    31