Classify working pattern personas using a rule based algorithm, using the person-average volume-based ('pav') method.

Source: R/workpatterns_classify_pav.R

[Experimental]

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"
)

Arguments

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:

  • "percent": percentage of signals divided by total signals (default)

  • "abs": absolute count of signals

signals

Character vector to specify which collaboration metrics to use:

  • "email" (default) for emails only

  • "IM" for Teams messages only,

  • "unscheduled_calls" for Unscheduled Calls only

  • "meetings" for Meetings only

  • or a combination of signals, such as c("email", "IM")

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:

  • "plot": returns a bar plot of signal distribution by hour and archetypes (default)

  • "data": returns the raw data with the classified archetypes

  • "table": returns a summary table of the archetypes

  • "plot-area": returns an overlapping area plot

Value

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.

Author

Ainize Cidoncha ainize.cidoncha@microsoft.com