| hrvar_count_all {vivainsights} | R Documentation |
Create count of distinct fields and percentage of employees with missing values for all HR variables
Description
This function enables you to create a summary table to validate
organizational data. This table will provide a summary of the data found in
the Viva Insights Data sources page. This function will return a summary
table with the count of distinct fields per HR attribute and the percentage
of employees with missing values for that attribute. See hrvar_count()
function for more detail on the specific HR attribute of interest.
Usage
hrvar_count_all(
data,
n_var = 50,
return = "message",
threshold = 100,
maxna = 20
)
Arguments
data |
A Standard Person Query dataset in the form of a data frame. |
n_var |
number of HR variables to include in report as rows. Default is set to 50 HR variables. |
return |
String to specify what to return |
threshold |
The max number of unique values allowed for any attribute. Default is 100. |
maxna |
The max percentage of NAs allowable for any column. Default is 20. |
Value
Returns an error message by default, where 'text' is passed in return.
-
'table': data frame. A summary table listing the number of distinct fields and percentage of missing values for the specified number of HR attributes will be returned. -
'message': outputs a message indicating which values are beyond the specified thresholds.
See Also
Other Data Validation:
check_query(),
extract_hr(),
flag_ch_ratio(),
flag_em_ratio(),
flag_extreme(),
flag_outlooktime(),
hr_trend(),
hrvar_count(),
hrvar_trend(),
identify_churn(),
identify_holidayweeks(),
identify_inactiveweeks(),
identify_nkw(),
identify_outlier(),
identify_privacythreshold(),
identify_shifts(),
identify_tenure(),
track_HR_change(),
validation_report()
Examples
# Return a summary table of all HR attributes
hrvar_count_all(pq_data, return = "table")