问题
I have a data set which contains interval times of different events occurring. What I want to do, is convert the data into a numeric vector, so its easier to manipulate and run summaries/make graphs etc, while keeping its time characteristics. Here is a snippet of my data:
data <- c( "03:31", "12:17", "16:29", "09:52", "04:01", "09:00", "06:29",
"04:17", "04:42")
class(data)
[1] character
The obvious answer is :
as.numeric(data)
But I get this error:
Warning message:
NAs introduced by coercion
I thought of maybe taking the ':' out, but then it loses its time characteristics. By that, I mean that if I sum values together say 347 and 543, it would give me 890 as opposed to 930. Here is the code that I would use to take the colon out, which works fine for its purpose:
Nocolon <- gsub("[:]", "", Data, perl=TRUE)
"0331" "1217" "1629" "0952" "0401" "0900" "0629" "0417" "0442"
So essentially, what I want is for my time values to be in a form which is easy to manipulate and analyse. My idea is for it to be a numeric vector, but that is from my minimal understanding of R. My actual code has thousands of time values, and I want to create a plot that will allow me to view and determine whether the values follow a statistical distribution.
Thanks in advance!
回答1:
Here are some approaches. All convert to minutes. For example, the first component is "03:31" which is 3 * 60 + 31 = 211 minutes. (1) to (5) do not use any packages.
1) %*% It works by reading data into a 2 column data frame with hours and minutes. That is converted to a matrix so that it can be matrix multiplied by c(60, 1). Finally, unravel it with c.
c(as.matrix(read.table(text = data, sep = ":")) %*% c(60, 1))
[1] 211 737 989 592 241 540 389 257 282
2) with This variation is even shorter. It creates the same data frame but and then simply mulitiplies the first column (V1) by 60 and adds it to the second column (V2).
with(read.table(text = data, sep = ":"), 60*V1+V2)
[1] 211 737 989 592 241 540 389 257 282
3) complex This converts each component to a complex number and then performs the required arithmetic on the real and imaginary parts:
data_c <- as.complex(sub(":(\\d+)", "+\\1i", data))
60 * Re(data_c) + Im(data_c)
## [1] 211 737 989 592 241 540 389 257 282
3a) This variation of (3) also works and avoids regular expressions:
data_c <- as.complex(paste0(chartr(":", "+", data), "i"))
60 * Re(data_c) + Im(data_c)
## [1] 211 737 989 592 241 540 389 257 282
4) eval This converts each component into an arithmetic expression which evaluates to the number of minutes and then performs the evalution. Using eval is not really recommended when you can avoid it so this one is less desirable:
sapply(parse(text = sub("(\\d+):", "60*\\1+", data)), eval)
## [1] 211 737 989 592 241 540 389 257 282
5) POSIXlt We can convert to "POSIXlt" class and then use the hour and min components:
with(unclass(as.POSIXlt(data, format = "%H:%M")), 60 * hour + min)
## [1] 211 737 989 592 241 540 389 257 282
6) chron Using the chron package we can paste on the seconds, convert to "times" class and then convert to minutes:
library(chron)
24 * 60 * as.numeric(times(paste0(data, ":00")))
## [1] 211 737 989 592 241 540 389 257 282
7) lubridate Using the lubridate package we can convert it using hm and then to numeric giving seconds and finally dividing by 60 to give minutes:
as.numeric(hm(data)) / 60
## [1] 211 737 989 592 241 540 389 257 282
回答2:
Use the as.difftime function designed for this:
as.difftime(data, format="%H:%M", units="mins")
#Time differences in mins
#[1] 211 737 989 592 241 540 389 257 282
来源：https://stackoverflow.com/questions/41581164/convert-time-values-to-numeric-while-keeping-time-characteristics