wpa/man/workpatterns_hclust.Rd

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% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/workpatterns_hclust.R
\name{workpatterns_hclust}
\alias{workpatterns_hclust}
\title{Create a hierarchical clustering of email or IMs by hour of day}
\usage{
workpatterns_hclust(
data,
k = 4,
return = "plot",
values = "percent",
signals = "email",
start_hour = "0900",
end_hour = "1700"
)
}
\arguments{
\item{data}{A data frame containing data from the Hourly Collaboration query.}
\item{k}{Numeric vector to specify the \code{k} number of clusters to cut by.}
\item{return}{Character vector to specify what to return.
Valid options include "plot" (default), "data", "table", "plot-area", "hclust", and "dist".
"plot" returns a bar plot, whilst "plot-area" returns an overlapping area plot.
"hclust" returns the hierarchical model generated by the function.
"dist" returns the distance matrix used to build the clustering model.}
\item{values}{Character vector to specify whether to return percentages
or absolute values in "data" and "plot". Valid values are "percent" (default)
and "abs".}
\item{signals}{Character vector to specify which collaboration metrics to use:
You may use "email" (default) for emails only, "IM" for Teams messages only,
"unscheduled_calls" for Unscheduled Calls only, or a combination, such as \code{c("email", "IM")}.}
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\item{start_hour}{A character vector specifying starting hours,
e.g. "0900"}
\item{end_hour}{A character vector specifying starting hours,
e.g. "1700"}
}
\value{
The summary table returned by \code{return == "table"} represent percentiles of signals,
e.g. x\% of signals are sent by y hour of the day.
}
\description{
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\Sexpr[results=rd]{lifecycle::badge("experimental")}
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Apply hierarchical clustering to emails sent by hour of day.
The hierarchical clustering uses cosine distance and the ward.D method
of agglomeration.
}
\details{
The hierarchical clustering is applied on the person-average volume-based (pav) level.
In other words, the clustering is applied on a dataset where the collaboration hours
are averaged by person and calculated as \% of total daily collaboration.
}
\examples{
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## Run clusters, returning plot
workpatterns_hclust(em_data, k = 5, return = "plot")
## Run clusters, return raw data
workpatterns_hclust(em_data, k = 4, return = "data")
## Run clusters for instant messages only, return hclust object
workpatterns_hclust(em_data, k = 4, return = "hclust", signals = c("IM"))
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\dontrun{
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## Run clusters with all three signal types, return plot
workpatterns_hclust(em_data,
k = 4,
return = "plot",
signals = c("IM", "email", "unscheduled_calls"))
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}
}
\seealso{
Other Work Patterns:
\code{\link{personas_hclust}()},
\code{\link{workpatterns_area}()}
}
\concept{Work Patterns}