R Under development (unstable) (2023-10-08 r85282 ucrt) -- "Unsuffered Consequences"
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Platform: x86_64-w64-mingw32/x64

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> library(testthat)
> library(timeplyr)
> 
> test_check("timeplyr")
Storing counts in `nn`, as `n` already present in input
i Use `name = "new_name"` to pick a new name.
Storing counts in `nn`, as `n` already present in input
i Use `name = "new_name"` to pick a new name.
Storing counts in `nn`, as `n` already present in input
i Use `name = "new_name"` to pick a new name.
Storing counts in `nn`, as `n` already present in input
i Use `name = "new_name"` to pick a new name.
Storing counts in `nn`, as `n` already present in input
i Use `name = "new_name"` to pick a new name.
Adding missing grouping variables: 'Sepal.Length', 'Species'
Adding missing grouping variables: `Sepal.Length`, `Species`
Adding missing grouping variables: 'Sepal.Length', 'Species'
Adding missing grouping variables: `Sepal.Length`, `Species`
Adding missing grouping variables: 'Sepal.Length'
Adding missing grouping variables: `Sepal.Length`
Adding missing grouping variables: 'Sepal.Length', 'Species'
Adding missing grouping variables: `Sepal.Length`, `Species`
Adding missing grouping variables: 'Sepal.Length', 'Species'
Adding missing grouping variables: `Sepal.Length`, `Species`
The below stat functions are available for use in stat_summarise
n
nmiss
min
max
mean
median
sd
var
mode
first
last
sum
prop_complete
This message is displayed once per session.
Assuming a time granularity of 1 hour(s)
Assuming a time granularity of 1 hour(s)
Assuming a time granularity of 1 hour(s)
Assuming a time granularity of 1 hour(s)
Joining with `by = join_by(x, interval, n)`
Joining with `by = join_by(x, interval, n)`
Assuming a time granularity of 1 hour(s)
Assuming a time granularity of 1 day(s)
Assuming a time granularity of 1 hour(s)
Assuming a time granularity of 1 hour(s)
Assuming a time granularity of 1 day(s)
Assuming a time granularity of 1 day(s)
Storing counts in `nn`, as `n` already present in input
i Use `name = "new_name"` to pick a new name.
Assuming a time granularity of 1 day(s)
Assuming a time granularity of 1 hour(s)
Assuming a time granularity of 1 hour(s)
Assuming a time granularity of 1 numeric unit(s)
Assuming a time granularity of 1 numeric unit(s)
Assuming a time granularity of 1 hour(s)
Assuming a time granularity of 1 hour(s)
Assuming a time granularity of 1 hour(s)
Joining with `by = join_by(origin, dest, tailnum, time_hour, n)`
Joining with `by = join_by(origin, dest, tailnum, time_hour, n)`
Assuming a time granularity of 0.1 numeric unit(s)
Joining with `by = join_by(origin, dest, time_hour, year, month, day, dep_time, sched_dep_time, dep_delay, arr_time, sched_arr_time, arr_delay, flight, air_time, distance, hour, minute)`
Joining with `by = join_by(origin, dest, time_hour, year, month, day, dep_time, sched_dep_time, dep_delay, arr_time, sched_arr_time, arr_delay, flight, air_time, distance, hour, minute)`
[ FAIL 0 | WARN 0 | SKIP 0 | PASS 927 ]
> 
> proc.time()
   user  system elapsed 
 111.17   18.50  129.37