R: table function for objects in datetime string?

Question

I have a large matrix with a column of datetime information.

The structure is: '2022-01-01_0545'(no seconds).

I'm looking for an effective way to get the number of occurrences of each year, month and day in my matrix. What could be a good approach?

Could I use the table() function or is it better to split the string into its components?

Example:

dates <- c("2022-01-01_0545","2022-03-01_0810","2021-12-13_1003","2022-09-10_0400","2022-03-09_1802")
data <- matrix(0 , nrow = 5, ncol = 2)
data <- cbind(data, dates)
colnames(data) <- NULL

Another example using dput(data[1:5, 10:11):

structure(c("290.603961274028", "281.885433495045", "283.438215255737", 
"275.935544893146", "284.739524498582", "2018-01-01_0000", "2018-01-03_0445", 
"2018-03-07_0045", "2018-01-04_0700", "2018-02-09_0015"), dim = c(5L, 
2L))

Answer 1

Calling your matrix m, here's using substr to extract the components and table() to make tables.

years = substr(m[, 2], 1, 4)
months = substr(m[, 2], 6, 7)
days = substr(m[, 2], 9, 10)

table(years)
# years
# 2018 
#    5 
   
table(months)
# months
# 01 02 03 
#  3  1  1 
 
table(days)
# days
# 01 03 04 07 09 
#  1  1  1  1  1 

Answer 2

Normally is good to convert dates into date formats, instead of keeping them as strings. If you do that, you can use lubridate's year, month, and day for a very clean solution.

To convert your dates, use something like:

data$dates = as.POSIXct(data$dates, format = "%Y-%m-%d_%H%M")

Then, you can use a mapping function to apply the lubridate funcions all at once. I used purrr's map, but you can use lapply, amongst others.

library(lubridate)
purrr::map(list("Years" = year, "Months" = month, "Days" = day), ~ table(.x(data$dates)))

Dummy data:

data = data.frame(dates = seq(as.POSIXct("2000-01-01 00:00"), by = 60*60*8, length.out = 12000),
                  numbers = rnorm(12000))

Results:

$Years

2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 
1098 1095 1095 1095 1098 1095 1095 1095 1098 1095 1041 

$Months

   1    2    3    4    5    6    7    8    9   10   11   12 
1023  944 1023  990 1023  990 1023 1023  990 1015  987  969 

$Days

  1   2   3   4   5   6   7   8   9  10  11  12  13  14  15  16  17  18  19  20  21  22  23  24  25  26  27  28  29  30  31 
396 395 395 396 395 396 396 395 396 396 396 396 396 393 394 394 393 393 392 394 393 393 393 394 393 394 393 393 369 360 228