extract_hr: Extract HR attribute variables

In vivainsights: Analyze and Visualize Data from 'Microsoft Viva Insights'

Extract HR attribute variables

Description

This function uses a combination of variable class, number of unique values, and regular expression matching to extract HR / organisational attributes from a data frame.

Usage

extract_hr(data, max_unique = 50, exclude_constants = TRUE, return = "names")

Arguments

data	A data frame to be passed through.
max_unique	A numeric value representing the maximum number of unique values to accept for an HR attribute. Defaults to 50.
exclude_constants	Logical value to specify whether single-value HR attributes are to be excluded. Defaults to TRUE.
return	String specifying what to return. This must be one of the following strings: "names" "vars" See Value for more information.

Value

A different output is returned depending on the value passed to the return argument:

• "names": character vector identifying all the names of HR variables present in the data.

• "vars": data frame containing all the columns of HR variables present in the data.

See Also

Other Support: any_idate(), camel_clean(), check_inputs(), cut_hour(), extract_date_range(), heat_colours(), is_date_format(), maxmin(), pairwise_count(), read_preamble(), rgb2hex(), totals_bind(), totals_col(), tstamp(), us_to_space(), wrap()

Other Data Validation: check_query(), 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_shifts(), identify_tenure(), track_HR_change(), validation_report()

Examples

pq_data %>% extract_hr(return = "names")

pq_data %>% extract_hr(return = "vars")

vivainsights documentation built on Aug. 8, 2025, 6:21 p.m.