Find dates that fail to parse in R Lubridate - r

Question

As a R novice I'm pulling my hair out trying to debug cryptic R errors. I have csv that containing 150k lines that I load into a data frame named 'date'. I then use lubridate to convert this character column to datetimes in hopes of finding min/max date.
dates <- csv[c('datetime')]
dates$datetime <- ymd_hms(dates$datetime)
Running this code I receive the following error message:
Warning message:
3 failed to parse.
I accept this as the CSV could have some janky dates in there and next run:
min(dates$datetime)
max(dates$datetime)
Both of these return NA, which I assume is from the few broken dates still stored in the data frame. I've searched around for a quick fix, and have even tried to build a foreach loop to identify the problem dates, but no luck. What would be a simple way to identify the 3 broken dates?
example date format: 2015-06-17 17:10:16 +0000

Answer 1

Credit to LawyeR and Stibu from above comments:
I first sorted the raw csv column and did a head() & tail() to find
which 3 dates were causing trouble
Alternatively which(is.na(dates$datetime)) was a simple one liner to also find the answer.

Answer 2

Lubridate will throw that error when attempting to parse dates that do not exist because of daylight savings time.
For example:
library(lubridate)
mydate <- strptime('2020-03-08 02:30:00', format = "%Y-%m-%d %H:%M:%S")
ymd_hms(mydate, tz = "America/Denver")
[1] NA
Warning message:
1 failed to parse.
My data comes from an unintelligent sensor which does not know about DST, so impossible (but correctly formatted) dates appear in my timeseries.

Answer 3

If the indices of where lubridate fails are useful to know, you can use a for loop with stopifnot() and print each successful parse.
Make some dates, throw an error in there at a random location.
library(lubridate)
set.seed(1)
my_dates<-as.character(sample(seq(as.Date('1900/01/01'),
as.Date('2000/01/01'), by="day"), 1000))
my_dates[sample(1:length(my_dates), 1)]<-"purpleElephant"
Now use a for loop and print each successful parse with stopifnot().
for(i in 1:length(my_dates)){
print(i)
stopifnot(!is.na(ymd(my_dates[i])))
}

Answer 4

To provide a more generic answer, first filter out the NAs, then try and parse, then filter only the NAs. This will show you the failures. Something like:
dates2 <- dates[!is.na(dates2$datetime)]
dates2$datetime <- ymd_hms(dates2$datetime)
Warning message:
3 failed to parse.
dates2[is.na(dates2$datetime)]

Answer 5

Here is a simple function that solves the generic problem:
parse_ymd = function(x){
d=lubridate::ymd(x, quiet=TRUE)
errors = x[!is.na(x) & is.na(d)]
if(length(errors)>0){
cli::cli_warn("Failed to parse some dates: {.val {errors}}")
}
d
}
x = c("2014/20/21", "2014/01/01", NA, "2014/01/02", "foobar")
my_date = lubridate::ymd(x)
#> Warning: 2 failed to parse.
my_date = parse_ymd(x)
#> Warning: Failed to parse some dates: "2014/20/21" and "foobar"
Created on 2022-09-29 with reprex v2.0.2
Of course, replace ymd() with whatever you want.

Answer 6

Use the truncate argument. The most common type of irregularity in date-time data is the truncation due to rounding or unavailability of the time stamp.
Therefore, try truncated = 1, then potentially go up to truncated = 3:
dates <- csv[c('datetime')]
dates$datetime <- ymd_hms(dates$datetime, truncated = 1)