View source: R/identify_shifts.R
identify_shifts | R Documentation |
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
.
identify_shifts(data, return = "plot")
data |
A data frame containing data from the Hourly Collaboration query. |
return |
String specifying what to return. This must be one of the following strings:
See |
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 the Shifts
columns.
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_query()
,
identify_shifts_wp()
,
identify_tenure()
,
remove_outliers()
,
standardise_pq()
,
subject_validate()
,
subject_validate_report()
,
track_HR_change()
,
validation_report()
Other Working Patterns:
flex_index()
,
identify_shifts_wp()
,
plot_flex_index()
,
workpatterns_area()
,
workpatterns_classify()
,
workpatterns_classify_bw()
,
workpatterns_classify_pav()
,
workpatterns_hclust()
,
workpatterns_rank()
,
workpatterns_report()
# Return plot
dv_data %>% identify_shifts()
# Return summary table
dv_data %>% identify_shifts(return = "table")
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