I have a column (ride_length) in variable(trips) in factor datatype exported from excel as HH:MM:SS-CodePudding

#using the glimpse function ride_length : Factor w/ 21865 levels #using the str function $ ride_length 0:12:57, 0:18:29, 1:37:18, 0:13:52, 0:37:17, 0:47:21

I would like the new output to read below as

$ ride_length 12.95, 18.4833, 97.3, 13.8666, 37.2833, 47.35

CodePudding user response：

We may convert to hms and divide by 60

as.numeric(hms::as_hms(as.character(trips$ride_length))/60)
[1] 12.95000 18.48333 97.30000 13.86667 37.28333 47.35000

data

trips <- structure(list(ride_length = structure(c(1L, 3L, 6L, 2L, 4L, 
5L), .Label = c("0:12:57", "0:13:52", "0:18:29", "0:37:17", "0:47:21", 
"1:37:18"), class = "factor")), class = "data.frame", row.names = c(NA, 
-6L))

CodePudding user response：

With base R, you can do

with(strptime(as.character(trips$ride_length), "%H:%M:%OS"), 60 * hour   min   sec / 60)

though there are limitations, as strptime requires hours from 0 to 23, minutes from 0 to 59, and seconds from 0 to 60. If that constraint isn't satisfied, then, with lubridate, you can do

library("lubridate")
as.numeric(hms(as.character(trips$ride_length)), "minutes")

CodePudding user response：

With chron package we could (data from akrun many thanks):

library(chron)
library(dplyr)
trips %>% 
  mutate(ride_length_minutes = 60 * 24 * as.numeric(times(ride_length)))

  ride_length ride_length_minutes
1     0:12:57            12.95000
2     0:18:29            18.48333
3     1:37:18            97.30000
4     0:13:52            13.86667
5     0:37:17            37.28333
6     0:47:21            47.35000