Using group_by with difftime

Question

I\'ve created a dataframe with data :

idCol <- c(\'1\',\'1\',\'2\',\'2\')
stepCol <- c(\'step1\' , \'step2\' , \'step1\' , \'step2\')
timestampCol <- c         


        

Answer 1

I did some minor editing to your code but basically you need to associate the results of ymd_hms with your mydata:

mydata$diffTime <- c(0, difftime(lubridate::ymd_hms(mydata$timestamp[-1]), 
                          lubridate::ymd_hms(mydata$timestamp[-nrow(mydata)]), units="hours"))
diffTime <- mydata %>% group_by(id) %>% summarize(mean(diffTime))

Returns:

R> diffTime
# A tibble: 2 x 2
     id `mean(diffTime)`
  <chr>            <dbl>
1     1         0.008333
2     2         0.033333

Answer 2

Please note there is inconsistencies in the sample data timestamp column for the time nomenclature

timestampCol <- c('01-01-2017:09.00', '01-01-2017:10.00', '01-01-2017:09.00', '01-01-2017:14.00')

Converting strings to time values (accounting for factors)

mydata$timestamp <- as.POSIXct(strptime(levels(mydata$timestamp)[mydata$timestamp], format="%m-%d-%Y:%H.%M"))

library(dplyr)
mydata %>%
  group_by(id) %>%
  mutate(diff = difftime(timestamp, lag(timestamp))) %>%
  summarise(na.omit(diff))

# A tibble: 2 x 2
      id `na.omit(diff)`
  <fctr>          <time>
1      1         1 hours
2      2         5 hours