Prints diagnostic data about the data query to the R console, with information such as date range, number of employees, HR attributes identified, etc.
check_query(data, return = "message", validation = FALSE)A person-level query in the form of a data frame. This includes:
Standard Person Query
Ways of Working Assessment Query
Hourly Collaboration Query
All person-level query have a PersonId column and a Date column.
String specifying what to return. This must be one of the following strings:
"message" (default)
"text"
See Value for more information.
Logical value to specify whether to show summarized version. Defaults to FALSE. To hide checks on variable
names, set validation to TRUE.
A different output is returned depending on the value passed to the return
argument:
"message": a message is returned to the console.
"text": string containing the diagnostic message.
This can be used with any person-level query, such as the standard person query, Ways of Working assessment query, and the hourly collaboration query. When run, this prints diagnostic data to the R console.
Other Data Validation:
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(),
identify_tenure(),
remove_outliers(),
standardise_pq(),
subject_validate_report(),
subject_validate(),
track_HR_change(),
validation_report()
check_query(sq_data)
#>
#> The data used is a Person Query
#>
#> There are 1034 employees in this dataset.
#>
#> Date ranges from 2019-11-03 to 2020-01-26.
#>
#> Unique identifiers include: `Domain` is CONTOSO.COM; `IsInternal` is TRUE; `Region` is US; `TimeZone` is Pacific Standard Time
#>
#> There are 4 (estimated) HR attributes in the data:
#> `FunctionType`, `LevelDesignation`, `Organization`, `IsActive`
#>
#> There are 1034 active employees out of all in the dataset.
#>
#> Variable name check:
#>
#> `Collaboration_hours` is used instead of `Collaboration_hrs` in the data.
#>
#> `Instant_Message_hours` is used instead of `Instant_message_hours` in the data.