зеркало из https://github.com/microsoft/wpa.git
80 строки
2.7 KiB
R
80 строки
2.7 KiB
R
% Generated by roxygen2: do not edit by hand
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% Please edit documentation in R/identify_nkw.R
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\name{identify_nkw}
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\alias{identify_nkw}
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\title{Identify Non-Knowledge workers in a Person Query using Collaboration
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Hours}
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\usage{
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identify_nkw(data, collab_threshold = 5, return = "data_summary")
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}
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\arguments{
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\item{data}{A Standard Person Query dataset in the form of a data frame.}
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\item{collab_threshold}{Positive numeric value representing the collaboration
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hours threshold that should be exceeded as an average for the entire
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analysis period for the employee to be categorized as a knowledge worker
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("kw"). Default is set to 5 collaboration hours. Any versions after v1.4.3,
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this uses a "greater than or equal to" logic (\code{>=}), in which case persons
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with exactly 5 collaboration hours will pass.}
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\item{return}{String specifying what to return. This must be one of the
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following strings:
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\itemize{
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\item \code{"text"}
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\item \code{"data_with_flag"}
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\item \code{"data_clean"}
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\item \code{"data_summary"}
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}
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See \code{Value} for more information.}
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}
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\value{
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A different output is returned depending on the value passed to the \code{return}
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argument:
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\itemize{
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\item \code{"text"}: string. Returns a diagnostic message.
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\item \code{"data_with_flag"}: data frame. Original input data with an additional
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column containing the \code{kw}/\code{nkw} flag.
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\item \code{"data_clean"}: data frame. Data frame with non-knowledge workers
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excluded.
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\item \code{"data_summary"}: data frame. A summary table by organization listing
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the number and \% of non-knowledge workers.
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}
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}
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\description{
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This function scans a standard query output to identify employees with
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consistently low collaboration signals. Returns the \% of non-knowledge
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workers identified by Organization, and optionally an edited data frame with
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non-knowledge workers removed, or the full data frame with the kw/nkw flag
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added.
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}
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\seealso{
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Other Data Validation:
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\code{\link{check_query}()},
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\code{\link{extract_hr}()},
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\code{\link{flag_ch_ratio}()},
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\code{\link{flag_em_ratio}()},
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\code{\link{flag_extreme}()},
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\code{\link{flag_outlooktime}()},
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\code{\link{hr_trend}()},
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\code{\link{hrvar_count_all}()},
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\code{\link{hrvar_count}()},
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\code{\link{hrvar_trend}()},
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\code{\link{identify_churn}()},
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\code{\link{identify_holidayweeks}()},
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\code{\link{identify_inactiveweeks}()},
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\code{\link{identify_outlier}()},
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\code{\link{identify_privacythreshold}()},
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\code{\link{identify_query}()},
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\code{\link{identify_shifts_wp}()},
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\code{\link{identify_shifts}()},
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\code{\link{identify_tenure}()},
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\code{\link{remove_outliers}()},
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\code{\link{standardise_pq}()},
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\code{\link{subject_validate_report}()},
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\code{\link{subject_validate}()},
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\code{\link{track_HR_change}()},
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\code{\link{validation_report}()}
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}
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\concept{Data Validation}
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