Identify shifts based on outlook time settings for work day start and end time
Source:R/identify_shifts.R
identify_shifts.Rd
This function uses outlook calendar settings for start and end time of work
day to identify work shifts. The relevant variables are
WorkingStartTimeSetInOutlook
and WorkingEndTimeSetInOutlook
.
Value
A different output is returned depending on the value passed to the return
argument:
"plot"
: ggplot object. A bar plot for the weekly count of shifts."table"
: data frame. A summary table for the count of shifts."data
: data frame. Input data appended with theShifts
columns.
See also
Other Data Validation:
check_query()
,
extract_hr()
,
flag_ch_ratio()
,
flag_em_ratio()
,
flag_extreme()
,
flag_outlooktime()
,
hr_trend()
,
hrvar_count()
,
hrvar_count_all()
,
hrvar_trend()
,
identify_churn()
,
identify_holidayweeks()
,
identify_inactiveweeks()
,
identify_nkw()
,
identify_outlier()
,
identify_privacythreshold()
,
identify_tenure()
,
track_HR_change()
,
validation_report()
Examples
# Demo with `pq_data` example where Outlook Start and End times are imputed
spq_df <- pq_data
spq_df$WorkingStartTimeSetInOutlook <- "6:30"
spq_df$WorkingEndTimeSetInOutlook <- "23:30"
# Return plot
spq_df %>% identify_shifts()
# Return summary table
spq_df %>% identify_shifts(return = "table")
#> # A tibble: 1 × 3
#> Shifts WeekCount PersonCount
#> <chr> <int> <int>
#> 1 6:30-23:30 1000 100