View source: R/workpatterns_classify_pav.R
| workpatterns_classify_pav | R Documentation |
Apply a rule based algorithm to emails or instant messages sent by hour of day. This uses a person-average volume-based ('pav') method.
workpatterns_classify_pav(
data,
values = "percent",
signals = c("email", "IM"),
start_hour = "0900",
end_hour = "1700",
return = "plot"
)
data |
A data frame containing data from the Hourly Collaboration query. |
values |
Character vector to specify whether to return percentages or absolute values in "data" and "plot". Valid values are:
|
signals |
Character vector to specify which collaboration metrics to use:
|
start_hour |
A character vector specifying starting hours, e.g. "0900" |
end_hour |
A character vector specifying starting hours, e.g. "1700" |
return |
Character vector to specify what to return. Valid options include:
|
A different output is returned depending on the value passed to the return
argument:
"plot": returns a bar plot of signal distribution by hour and
archetypes (default). A 'ggplot' object.
"data": returns a data frame of the raw data with the classified archetypes.
"table": returns a data frame of a summary table of the archetypes.
"plot-area": returns an overlapping area plot. A 'ggplot' object.
Ainize Cidoncha ainize.cidoncha@microsoft.com
Other Working Patterns:
flex_index(),
identify_shifts(),
identify_shifts_wp(),
plot_flex_index(),
workpatterns_area(),
workpatterns_classify(),
workpatterns_classify_bw(),
workpatterns_hclust(),
workpatterns_rank(),
workpatterns_report()
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