| identify_inactiveweeks {vivainsights} | R Documentation |
Identify Inactive Weeks
Description
This function scans a standard query output for weeks where collaboration hours is far outside the mean for any individual person in the dataset. Returns a list of weeks that appear to be inactive weeks and optionally an edited dataframe with outliers removed.
As best practice, run this function prior to any analysis to remove atypical collaboration weeks from your dataset.
Usage
identify_inactiveweeks(data, sd = 2, return = "text")
Arguments
data |
A Standard Person Query dataset in the form of a data frame. |
sd |
The standard deviation below the mean for collaboration hours that should define an outlier week. Enter a positive number. Default is 1 standard deviation. |
return |
String specifying what to return. This must be one of the following strings:
See |
Value
Returns an error message by default, where 'text' is returned. When
'data_cleaned' is passed, a dataset with outlier weeks removed is returned
as a dataframe. When 'data_dirty' is passed, a dataset with outlier weeks
is returned as a dataframe.
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_nkw(),
identify_outlier(),
identify_privacythreshold(),
identify_shifts(),
identify_tenure(),
track_HR_change(),
validation_report()