Calculating new column based on input from existing columns - r

Question

I have a data frame with start and stop times for an experiment and I want to calculate the duration of each experiment (one line per experiment). Data frame:
start_t stop_t
7:35 7:48
23:50 00:15
11:22 12:06
I created a function to convert the time to POSIX format and calculate the duration, testing if start and stop crosses midnight:
TimeDiff <- function(t1,t2) {
if (as.numeric(as.POSIXct(paste("2016-01-01", t1))) > as.numeric(as.POSIXct(paste("2016-01-01", t2)))) {
t1n <- as.numeric(as.POSIXct(paste("2016-01-01", t1)))
t2n <- as.numeric(as.POSIXct(paste("2016-01-02", t2)))
}
if (as.numeric(as.POSIXct(paste("2016-01-01", t1))) < as.numeric(as.POSIXct(paste("2016-01-01", t2)))) {
t1n <- as.numeric(as.POSIXct(paste("2016-01-01", t1)))
t2n <- as.numeric(as.POSIXct(paste("2016-01-01", t2)))
}
#calculate time-difference in seconds
t2n - t1n
}
Then I wanted to apply this function to my data frame using either the 'mutate' function in 'dplyr' or an 'apply' function, e.g.:
mutate(df, dur = TimeDiff(start_t, stop_t))
But the result is that the 'dur' table is filled with just the same value. I ended up using a clunky for-loop to apply my function to the dataframe, but would want a more elegant solution. Help wanted!

Answer 1

Day can be incremented when the time stamp passes midnight. I am not sure if that is necessary to just to test if start and stop crosses midnight. Hope this helps!
df = data.frame(start_t = c("7:35", "23:50","11:22"), stop_t=c("7:48", "00:15", "12:06"), stringsAsFactors = F)
myfun = function(tvec1, tvec2, units_args="secs") {
tvec1_t = as.POSIXct(paste("2016-01-01", tvec1))
tvec2_t = as.POSIXct(paste("2016-01-01", tvec2))
time_diff = difftime(tvec2_t, tvec1_t, units = units_args)
return( time_diff )
}
# append new columns (base R)
df$time_diff = myfun(df$start_t, df$stop_t)
df$cross = ifelse(df$time_diff < 0, 1, 0)
output:
start_t stop_t time_diff cross
1 7:35 7:48 780 secs 0
2 23:50 00:15 -84900 secs 1
3 11:22 12:06 2640 secs 0

Answer 2

Since you don't have dates but only times, there is indeed the problem of experiments crossing midnight. Your function does not work, because it is not vectorized, i.e. it doesn't compute the difference for each element on its own.
The following works but is still not perfectly elegant:
If the start happened before the end, we simply subtract to get the duration.
If we cross midnight (the heuristic for this is not very stable), we calculate the difference until midnight and add the duration on the next day.
library(tidyverse)
diff_time <- function(start, end) {
case_when(start < end ~ end - start,
start > end ~ parse_time("23:59") - start + end + parse_time("0:01")
)
}
df %>%
mutate_all(parse_time) %>%
mutate(duration = diff_time(start_t, stop_t))
#> start_t stop_t duration
#> 1 07:35:00 07:48:00 780 secs
#> 2 23:50:00 00:15:00 1500 secs
#> 3 11:22:00 12:06:00 2640 secs
If you had dates, you could simply do:
df %>%
mutate(duration = stop_t - start_t)
Data
df <- read.table(text = "start_t stop_t
7:35 7:48
23:50 00:15
11:22 12:06", header = T)

Answer 3

The simplest way I can think of involves lubridate:
library(lubridate)
library(dplyr)
#make a fake df
df <- data.frame(start = c('7:35', '23:50', '11:22'), stop = c('7:48', '00:15', '12:06'), stringsAsFactors = FALSE)
#convert to lubridate minutes/seconds format, then subtract
df %>%
mutate(start = ms(start), stop = ms(stop)) %>%
mutate(dur= stop - start)
Output:
start stop dur
1 7M 35S 7M 48S 13S
2 23M 50S 15S -23M -35S
3 11M 22S 12M 6S 1M -16S
The problem with your circumstance is that the second line will confuse lubridate - it will show 23 hours and some minutes because it will assume all of these times are on the same day. You should probably add the day:
library(lubridate)
library(dplyr)
#make a fake df
df <- data.frame(start = c('2017/10/08 7:35', '2017/10/08 23:50', '2017/10/08 11:22'), stop = c('2017/10/08 7:48', '2017/10/09 00:15', '2017/10/08 12:06'), stringsAsFactors = FALSE)
#convert to lubridate minutes/seconds format, then subtract
df %>%
mutate(start = ymd_hm(start), stop = ymd_hm(stop)) %>%
mutate(dur= stop - start)
Output:
start stop dur
1 2017-10-08 07:35:00 2017-10-08 07:48:00 13 mins
2 2017-10-08 23:50:00 2017-10-09 00:15:00 25 mins
3 2017-10-08 11:22:00 2017-10-08 12:06:00 44 mins