extract_hr {vivainsights} | R Documentation |
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 |
return |
String specifying what to return. This must be one of the following strings:
See |
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")