R/identify_tenure.R
identify_tenure.Rd
This function calculates employee tenure based on different input dates.
identify_tenure
uses the latest Date available if user selects "Date",
but also have flexibility to select a specific date, e.g. "1/1/2020".
identify_tenure(
data,
end_date = "Date",
beg_date = "HireDate",
maxten = 40,
return = "message"
)
A Standard Person Query dataset in the form of a data frame.
A string specifying the name of the date variable representing the latest date. Defaults to "Date".
A string specifying the name of the date variable representing the hire date. Defaults to "HireDate".
A numeric value representing the maximum tenure. If the tenure exceeds this threshold, it would be accounted for in the flag message.
String specifying what to return. This must be one of the following strings:
"message"
"text"
"plot"
"data_cleaned"
"data_dirty"
"data"
See Value
for more information.
A different output is returned depending on the value passed to the return
argument:
"message"
: message on console with a diagnostic message.
"text"
: string containing a diagnostic message.
"plot"
: 'ggplot' object. A line plot showing tenure.
"data_cleaned"
: data frame filtered only by rows with tenure values
lying within the threshold.
"data_dirty"
: data frame filtered only by rows with tenure values
lying outside the threshold.
"data"
: data frame with the PersonId
and a calculated variable called
TenureYear
is returned.
Other Data Validation:
check_query()
,
extract_hr()
,
flag_ch_ratio()
,
flag_em_ratio()
,
flag_extreme()
,
flag_outlooktime()
,
hr_trend()
,
hrvar_count_all()
,
hrvar_count()
,
hrvar_trend()
,
identify_churn()
,
identify_holidayweeks()
,
identify_inactiveweeks()
,
identify_nkw()
,
identify_outlier()
,
identify_privacythreshold()
,
identify_query()
,
identify_shifts_wp()
,
identify_shifts()
,
remove_outliers()
,
standardise_pq()
,
subject_validate_report()
,
subject_validate()
,
track_HR_change()
,
validation_report()